As domestic environments are increasingly required to meet diverse and changing human needs within constrained spaces, physical reconfigurability offers a promising solution. We developed a full-scale, manipulable room prototype as an exploratory co-design instrument, enabling participants to bodily explore and reflect on reconfigurable living spaces. Through 12 sessions with 30 participants involving brainstorming, bodystorming, and interviews, we identified spatial design patterns and elicited perspectives on reconfigurable domestic environments. Our findings contribute a design pattern catalogue for reconfigurable spaces, alongside insights into the lived experience of reconfigurability. We also discuss design principles, three affordance-based design dimensions that capture value tensions: empowering vs. restrictive, utilitarian vs. hedonic, and futuristic vs. practical, as well as lessons from co-design with a room-scale prototype. We demonstrate agile, room-scale prototyping as a methodological approach for spatial HCI research, advancing toward human-computer habitation, where interactive systems become inhabited built environments that support human values, creativity, and autonomy.

While robots are traditionally envisioned as physical entities that move through, sense, and act upon the environment, a new category is emerging: the inhabitable robot, or "robot-room," which redefines human-robot interaction by immersing us within the robot itself. As a first step in exploring this novel design space, we developed a full-scale, rapid-prototyped robot-room—not a simulation or scale model—and conducted a co-design study with 30 participants. Inside this immersive space, participants explored new forms of human-robot interaction, engaging their perceptual faculties for "knowing spaces." Our findings inform our ongoing development of a fully operational robot-room and offer valuable insights into expanding the concept of human-robot interaction to one of human-robot cohabitation.

We propose, examine prototypes of, and collect user input on morphing robotic surfaces, "robot-room" elements that, individually or in combination, change the functionality of the rooms we live in, directly controlled by the room’s occupants engaging with it. Robot-rooms represent an advance in human-robot interaction whereby human interaction is within a machine that physically envelops us. We discuss the motivation for such robot-rooms, present initial work aimed at their physical realization, and report on a user study of 80 participants to learn what people might want of and expect from robot rooms, the results of which will inform both the iterative design of the robot room and the thinking of our community as it grapples with how we want to live with (and "in") robots.

Dynamic capture is one of the most challenging issues to be solved in the field of robotics. Although robotic hands/grippers have emerged for decades, there are still few of them that can dynamically capture moving targets because the process is strongly accompanied by impact force and uncertainties in relative gripper/target locations and velocities. In this article, we present the novel design of a multitentacle gripper inspired by the motions of sea anemones. It is found that each tentacle of the sea anemone is not individually able to capture a fish but the collaboration of a larger number of tentacles can greatly enhance the overall capture ability. Based on this concept, 12 continuum arms including active and passive types are proposed and evaluated for their deformation to external forces. In addition, a deployable base, inspired by origami and Sarrus mechanisms, is utilized to change the posture of the continuum arms and drive the active arms. An inertial measurement unit is equipped to sense the impact of the dynamic targets. Finally, a series of experiments proved that the proposed multitentacle gripper could capture dynamic targets with different shapes, velocities, and collision angles, showing satisfactory capture robustness.

This paper discusses the effect of axial backbone compression on tendon-driven continuum robots. A new mechanics model for compensating for this effect that does not require tendon tension sensing or knowledge of manipulator material properties/stiffnesses is introduced and analyzed. In addition, we provide an analytical expression for the minimum preload on the tendons to achieve a given bend, a quantity determined empirically thus far. Our model is computationally efficient and achieves real time control on low cost hardware. The analysis is supported by experimental results demonstrating significant improvement over kinematics in open loop control of a tendon-driven continuum hose robot.

In this paper, we present a new approach to the control of continuum robot sections using IMU quaternion feedback. We use a discrete time root finding algorithm to steer a continuum section in the desired shape space direction. We found that the approach lacks end effector positioning accuracy when used by itself, however, when used in conjunction with a feedforward model it actively counters the influence of unmodeled factors. The approach is implemented on a single section of a continuum hose robot developed for 3D printing of concrete in construction applications. The results demonstrate significant improvements in positioning accuracy compared to standalone kinematics/mechanics-based position control of tendon lengths. Additionally, this approach can be implemented using low cost sensing and control hardware.

We present a novel application of continuum robots acting as concrete hoses to support 3D printing of cementitious materials. An industrial concrete hose was fitted with a cable harness and remotely actuated via tendons. The resulting continuum hose robot exhibited non constant curvature. In order to account for this, a new geometric approach to modeling variable curvature inverse kinematics using Euler curves is introduced herein. The new closed form model does not impose any additional computational cost compared to the constant curvature model and results in a marked improvement in the observed performance. Experiments involving 3D printing with cementitious mortar using a continuum hose robot were also conducted.

Robots are typically designed as occupants of rooms, adapting to, and navigating within them. “Robot surfaces,” an emerging robot typology, are not occupants of but integral with rooms, physically shaping rooms to support human activity. We report on an advancement of robot surfaces formed by weaving McKibben Pneumatic Air Muscles that, when actuated, morph a 2D planar surface to generate 3D geometries including a “spherical cap.” Following our foundational study at different scales with different materials, we developed a full-scale prototype that offers an intimate and private space for people meeting in open plan environments. We report on our research, focusing on a design case, and validate the full-scale prototype as compared to our Non-Uniform Rational B-Splines (NURBS) model for three useful configurations. Our quantitative and qualitative results suggest that our robot surface can support human activity as envisioned. This research contributes foundational understanding of an emerging category of robotics from which our team and peers can build.

Tendon actuated multisection continuum arms have high potential for inspection applications in highly constrained spaces. They generate motion by axial and bending deformations. However, because of the high mechanical coupling between continuum sections, variable length-based kinematic models produce poor results. A new mechanics model for tendon actuated multisection continuum arms is proposed in this paper. The model combines the continuum arm curve parameter kinematics and concentric tube kinematics to correctly account for the large axial and bending deformations observed in the robot. Also, the model is computationally efficient and utilizes tendon tensions as the joint space variables thus eliminating the actuator length related problems such as slack and backlash. A recursive generalization of the model is also presented. Despite the high coupling between continuum sections, numerical results show that the model can be used for generating correct forward and inverse kinematic results. The model is then tested on a thin and long multisection continuum arm. The results show that the model can be used to successfully model the deformation.

In this paper, a novel strategy is designed for trajectory control of a multi-section continuum robot in three-dimensional space to achieve accurate orientation, curvature, and section length tracking. The formulation connects the continuum manipulator dynamic behavior to a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section. Based on this connection, a computed torque control architecture is developed for the virtual robot, for which inverse kinematics and dynamic equations are constructed and exploited, with appropriate transformations developed for implementation on the continuum robot. The control algorithm is implemented on a six degree-of-freedom two-section OctArm continuum manipulator. Experimental results show that the proposed method managed simultaneous extension/contraction, bending, and torsion actions on multi-section continuum robots with decent tracking performance (steady state arc length and curvature tracking error of merely 3.3mm and 0.13m-1, respectively). These results demonstrate that the proposed method can be applied to multi-section continuum manipulators and perform complex maneuvers within a nonlinear setting.

Continuum robots have long held a great potential for applications in inspection of remote, hard-to-reach environments. In future environments such as the Deep Space Gateway, remote deployment of robotic solutions will require a high level of autonomy due to communication delays and unavailability of human crews. In this work, we explore the application of policy optimization methods through Actor-Critic gradient descent in order to optimize a continuum manipulator's search method for an unknown object. We show that we can deploy a continuum robot without prior knowledge of a goal object location and converge to a policy that finds the goal and can be reused in future deployments. We also show that the method can be quickly extended for multiple Degrees-of-Freedom and that we can restrict the policy with virtual and physical obstacles. These two scenarios are highlighted using a simulation environment with 15 and 135 unique states, respectively.

Tendrils are common stable structures in nature and are used for sensing, actuation, and geometrical stiffness modulation. In this paper, for the first time we exploit the helical geometry of a shape memory alloy (SMA) tendril as a simple to fabricate highly dexterous robotic continuum tentacle that we called Active Tendril-Backbone Robot (ATBR). This is achieved via partial (120 deg) activation of single helix turns resulting in backbone directional bendings. A 141.5 mm prototype (130 mm when fully compressed) has been fabricated and a simple theoretical framework is proposed and experimentally validated for modeling of the tentacle configuration. The manipulator has five 2-DOF joints capable of reaching bending angles of up to 54.5 deg and angular speed of up to 6.8 deg/s. The dexterity of the manipulator is showcased empirically in reaching complex configurations and simple navigation through confined space of a curving path.

In this paper, we propose and investigate a new approach to modeling variable curvature continuum robot sections, based on Euler spirals. Euler spirals, also termed Clothoids, or Cornu spirals, are those curves in which the curvature increases linearly with their arc length. In this work, Euler spirals are applied to the kinematic modeling of continuum robots for the first time. The approach was evaluated using the sections of numerous continuum robots, including two novel parallel continuum robots. Each robot consists of three parallel sections, each with three thin, long McKibben actuators. These sections are poorly modeled by the widely used constant curvature kinematic model. The constant curvature and Euler spiral models were compared and the Euler spiral method was seen to be a significantly better match for a wide range of configurations of the robot hardware.

We describe the design and physical realization of a novel branching continuum robot, aimed at inspection and cleaning operations in hard-to-reach environments at depths greater than human arm lengths. The design, based on a hybrid concentric-tube/tendon actuated continuum trunk core, features two pairs of fully retractable continuum branches. The retractable nature of the branches allows the robot to actively change its topology, allowing it to penetrate narrow openings and expand to adaptively engage complex environmental geometries. We detail and discuss the realization of a physical prototype of the design, and its testing in a simulated glove box environment.

Developments of robot arms are countless, but there has been little focus on robot surfaces for the reshaping of a habitable space—especially compliant surfaces. In this paper we introduce a novel, tendon-driven, robot surface comprised of aggregated, overlapping panels organized in a herringbone pattern. The individual 3D-printed panels and their behavior as an aggregation are inspired by the form and behavior of a pinecone. This paper presents our concept, design, and realization of this robot, and compares our prototype to simulations of four physical configurations that are formally distinct and suggestive of how the surface might be applied to habitable, physical space in response to human needs and wants. For the four configurations studied, we found a validating match between prototype and simulations. The paper concludes with a consideration of potential applications for robot surfaces like this one.

We discuss motion planning in the configuration spaces of robots containing continuum elements. The configuration space structure of extensible continuum sections is first analyzed, with practical constraints unique to continuum elements identified. The results are applied to generate the configuration space of a hybrid continuum lamp/mobile base robot. A conventional motion planning RRT/A* approach is subsequently applied for the robot in an aging in place application scenario.

Multisection continuum arms offer complementary characteristics to those of traditional rigid-bodied robots. Inspired by biological appendages, such as elephant trunks and octopus arms, these robots trade rigidity for compliance and accuracy for safety and, therefore, exhibit strong potential for applications in human-occupied spaces. Prior work has demonstrated their superiority in operation in congested spaces and manipulation of irregularly shaped objects. However, they are yet to be widely applied outside laboratory spaces. One key reason is that, due to compliance, they are difficult to control. Sophisticated and numerically efficient dynamic models are a necessity to implement dynamic control. In this paper, we propose a novel numerically stable center-of-gravity-based dynamic model for variable-length multisection continuum arms. The model can accommodate continuum robots having any number of sections with varying physical dimensions. The dynamic algorithm is of O (n2) complexity, runs at 9.5 kHz, simulates six to eight times faster than real time for a three-section continuum robot, and, therefore, is ideally suited for real-time control implementations. The model accuracy is validated numerically against an integral-dynamic model proposed by the authors and experimentally for a three-section pneumatically actuated variable-length multisection continuum arm. This is the first sub-real-time dynamic model based on a smooth continuous deformation model for variable-length multisection continuum arms.

Illiteracy is a global problem impacting the growth and development of individuals and society. Studies indicate that picturebook reading within a facilitated storytime setting is an important tool for children's language acquisition. In the research reported here, we hypothesized that literacy, in an increasingly digital society, can be cultivated in a robot-embedded environment that is physical, digital and evocative of the picturebook being read. Words become worlds. To test our hypothesis, we designed, prototyped, and implemented the LIT ROOM, a cyber-physical room for literacy. As a Research through Design [RtD] exemplar for interactive systems at habitable scale, the LIT ROOM featured a multi-phase, iterative process of design and evaluation for usability and efficacy. Evaluations with 35 children and 6 librarians in a public library serving a population with grave literacy challenges suggest that our reconfigurable learning environment facilitates a diversity of children's literary responses during the dialogical reading of picturebooks.

In this paper, we describe a novel nonlinear control strategy for the closed-loop control of extensible continuum robots. Previous attempts at controlling continuum robots have proved difficult due to the complexity of their system dynamics. Taking advantage of a previously developed dynamic model for a three-section, planar, continuum manipulator, we develop an adaptation-based control law. We present simulation results of a set-point tracking between a rigid-link control device and an extensible continuum manipulator. Experimental results of the controller implemented on a six degree-of-freedom continuum robot are also presented.

In this paper, we show how structures and strategies employed by thin-stemmed plants can be adapted to improve robot access to unstructured and congested environments. Specifically, we show how the use of vine-inspired movement strategies can enhance long thin continuum robot exploration and inspection operations. We introduce a new theoretical plant growth-inspired approach for modeling and motion generation of continuum robot backbones. The approach is demonstrated in numerous experiments including inspection within a high fidelity, full-scale mock-up of the International Space Station at NASA Johnson Space Center, using novel robot tendril hardware.

Continuum (continuous backbone) robots are suitable for operation in unstructured environments thanks to their inherent compliance. They can adjust their shape to navigate through complex environments and grasp a wide variety of payloads with their compliant backbones. However, controller design for continuum robots is challenging due to their complex dynamics. In this paper, we introduce a new and novel strategy for trajectory control of continuum robot sections. The approach is based on a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section. A conventional control strategy is developed for the virtual robot, for which inverse kinematics and dynamic equations are formulated and exploited, with appropriate transformations developed for implementation on the continuum robot. Simulations of the virtual robot computed torque control were executed and results indicate that the control method has good trajectory tracking performance. The control algorithm was implemented on a three degree of freedom section of the OctArm continuum manipulator, with decent tracking performance (steady state tracking error of merely 3mm during extension).

Precise actuation of continuum surfaces in combination with continuum robotic arms that undergo large deformation is of high interest in soft robotics but of limited model-based study to date. This work develops this area towards enabling the robust design and control of large deformation continuum surfaces (LDCS) across multiple industrial applications in the healthcare, aerospace, manufacturing, and automotive domains. It introduces an actuation based dynamic model of LDCSs to accurately determine their deflection due to application of concentrated external forces while maintaining many physical characteristics and constraints on actuation elements and surface structure such as gravity, inertia, damping, elasticity, and interactive forces between actuators and LDCS. Using the lumped-mass methodology, a 3D integrated surface-arm model is developed, simulated and then validated experimentally where a pair of parallel arms are attached to the surface to actuate and deform it. The surface is then simultaneously subjected to a concentrated constant external force at its top center between the two arms. Comparing measured displacements between the experimental and modelling results over actuation time yielded the maximum error is less than 1% of the length of the surface's side at its final deflected profile despite the limited number of nodes (masses) used in the LDCS model while it is exposed to a significant external force.

The outcome of a multidisciplinary and iterative process, CyberPLAYce is a tangible, interactive, cyber-physical learning tool for children supporting computational thinking and, particularly, playful storytelling. CyberPLAYce finds inspiration in the concept of child-computer interaction, where meaning is constructed through spatially reconfiguring the physical environment. The novel aspect of CyberPLAYce is its extension of cyber-learning to the dimension of space where children construct meaning at a larger physical scale. This paper outlines the motivations for CyberPLAYce, focuses on the full arc of design and evaluation activities concerning computational thinking (CT) practices that engaged 8-12-year-old storytellers, and concludes with a consideration of future work focusing on spatial thinking with CyberPLAYce. Results from our empirical study suggest that cyber-physical play afforded by CyberPLAYce scaffolds computational thinking, creating, and sharing in children. Particularly for IDC researchers in the educational domain, CyberPLAYce represents a Research-through-design exemplar supporting children's enjoyment of learning and meaning-construction.

We present a novel approach to teleoperation of continuum robots. In contrast to previous approaches restricted to three Degree-of-Freedom (DoF) joysticks, a six degree-of-freedom rigid-link manipulator is used as the input device. Mappings from the rigid-link arm to the continuum robot are synthesized and analyzed, focusing on their potential for creating a more intuitive operational interface. The approach was implemented using a six degree-of-freedom rigid-link manipulator as input device for teleoperation of a three section, nine degree-of-freedom continuum robot. Tests were conducted across a range of planar and spatial tasks, using fifteen participant operators. The results demonstrate the feasibility of the approach, and suggest that it can be effective independent of the prior robotics, gaming, or teleoperative experience of the operator.

The complexity of soft continuum manipulators with hybrid and tuneable structures poses a challenging task to achieve an inverse kinematics model which is both precise and computationally efficient for control and optimization purposes. In this paper, a new method based on the principle of virtual work and a geometry deformation approach is presented for the inverse kinematics model of the STIFF-FLOP arm which is a pneumatically actuated continuum manipulator. We propose a novel simplified and computationally efficient yet accurate analytical solution to analyse the static behaviour of a compound soft manipulator in the presence of external and body forces which is verified against experimental data, showing promising agreement with 10% mean error for planar movements. In the process, we present a new modelling approach for braided soft extensor actuators with no braid-surface relative slip constraint. For the first time, our model predicts a simple analytical solution for the cross section deformation which is essential to control soft manipulators with regional tunable stiffness structure.

This paper presents general modal dual Quaternion (DQ) kinematics for multisection continuum arms. DQ's produce higher accuracy than homogeneous transformation matrices (HTM) when transformed to modal shape functions (MSF) of similar order and are numerically stable. Thus, the model is compact, more accurate and computationally efficient than the modal kinematics proposed by the author based on HTM's. Also, DQ kinematics does not suffer from singularity related limitations of Euler angle based inverse orientation kinematics. Recursive schemes for deriving DQ's and DQ Jacobians are also presented and can be extended arbitrarily. Both modal HTM and modal DQ kinematics are then applied to solve illustrative spatial inverse position and orientation tracking problems. Based on the results, this paper quantitatively compares both methods and highlights the advantages of modal DQ kinematics. The proposed DQ kinematics are easily extensible to variable length multisection continuum arm with general actuator configurations.

In this paper, we present a new forward kinematic model for a novel class of long and thin continuum robots for operation in spatial workspace. Such robots are well suited for navigation through unstructured environments with superior reach using their flexible and thin profile, especially for inspection applications. This cable-like continuum robot design [1] has a concentric backbone arrangement but is spring-loaded and tendon-actuated, has improved compliance with a light and compact motor-encoder actuation mechanism. To account for the spring-loading, a compression factor is introduced on top of the established constant curvature continuum kinematics. The resulting continuum or shape variables are then estimated as a function of the measurable encoder variables. The effectiveness of the model is validated by performing experiments with the robot prototype.

In an effort to improve sailor safety during underway replenishment on the open sea, a robotic refueling system has been developed to autonomously refuel unmanned surface vehicles (USVs). The Rapid Autonomous Fuel Transfer (RAFT) project has demonstrated a methodology that could be used on the open water to autonomously refuel Navy vessels at significant sea states. The prototype refueling system is made up of two robotic arms: a rigid and precise industrial robotic manipulator to pinpoint the location of the target fuel tank and a novel soft pneumatic arm (Octarm) to provide compliant and safe contact with the USV. At the end of the Octarm, a magnetic end effector was designed (patent pending) to transfer a refueling “puck” from the robotic system to the target fuel tank. Acting under manual control or autonomously through visual tracking techniques, the robotic refueling system was shown to effectively transfer fuel to the target US Navy Sea Fox vessel under sea state 3.25 conditions at the US Army Aberdeen Test Center. The results demonstrate the feasibility of using a robotic solution to allow autonomous shore-to-ship or ship-to-USV refueling. It also illustrates the benefits and challenges of future robotic ship-to-USV refueling operations. This represents the first demonstrated use of a robotic system for fluid transfer to vessels in active sea states. This paper describes the design, development, and demonstration of the prototype autonomous refueling system.

As we come to live, work and play in an increasingly digital society, the future of interactive systems research, design, and practice will be shaped partly by larger-scale, cyber-physical systems. The cyber-physical LIT KIT enhances children's picturebook reading, both during and after interactive read-alouds, creating a multi-media, mixed-reality experience that transforms everyday environments into an environment evocative of the picturebook being read. The room-filled audio-visual-spatial effects of the LIT KIT contextualize language and provide feedback to the participants. The LIT KIT also acts as a story-extension tool, allowing children to customize environmental effects towards interpreting picturebooks for themselves. This paper offers a scenario of the child-computer interaction afforded by the LIT KIT, elucidates the motivations for its design, and focuses on an evaluation activity and its results. Particularly for DIS researchers in the educational domain, the LIT KIT represents a design exemplar that supports children's enjoyment of learning and meaning-making.

An inevitable new frontier for the CHI community is the development of complex, larger-scale, cyber-physical artifacts where advancements in design, computing and robotics converge. Presented here is a design exemplar: the Assistive, Robotic Table (ART), the key component of our envisioned home suite of networked, robotic furnishings for hospitals and homes, promoting wellbeing and independent living. We begin with the motivations for ART, and present our iterative, five-phase, participatory design-and-evaluation process involving clinicians at a rehabilitation hospital, focusing here on the final usability study. From our wide-ranging design-research activities, which may be characterized as research through design, we found ART to be promising but also challenging. As a design exemplar, ART offers invaluable lessons to the CHI community as it comes to design larger-scale, cyber-physical artifacts cultivating interactions across people and their surroundings that define places of social, cultural and psychological significance.

Soft limb locomotion is a relatively new and challenging research field. However, soft limbs can not yet transition to practical application due to difficulties associated with control methods. Motivated by this research problem, in this paper, we investigate the performance of energy based control of underactuated soft limbed systems. We augment the previously reported energy shaping function for rigid bipeds with a new set of functions for the novel class of underactuated compass gait soft bipeds. We evaluate the controller performance and identify desired features and characteristics for better speed performance of such a biped. The proposed energy shaping functions are compared through controlled Lagrangian (CL) method for Euler-Lagrangian (EL) models and interconnection and damping assignment passivity-based control (IDA-PBC) methods for port-controlled Hamiltonian (PCH) models. Results for system stability, speed performance, and input torque profiles are compared. The IDA-PBC controllers are observed to produce better input torque and performance over the CL methods.The findings assist in extending and developing novel controllers to implement on soft limbed robots for practical control applications of soft multi-continuum limbed robots.

This paper details closed-loop control experiments that were conducted on an extensible continuum manipulator, the OctArm. The performance of three controllers are shown here. The controllers can be classified into two categories: Closed-loop configuration-space control and closed-loop task-space teleoperation. Two controllers were tested in the configuration-space control experiments: a proportional-derivative (PD) controller and a nonlinear sliding-mode controller. The third controller is also shown in which the redundant extensible continuum manipulator tip tracks the motion of a kinematically-dissimilar non-redundant rigid-link master system. The results of these experiments confirm the ability of the control strategies to effectively control continuum robot hardware.

In this paper, we present a novel design for constructing multi-section continuum robots with a special focus on thin (less than 1 cm diameter) and relatively longer length (more than 100 cm), along with its new kinematic modeling and performance evaluation. This spring-loaded, tendon-actuated cable-like continuum robot incorporates key features of a concentric tube style design with added local compression to most sections and actively controllable bending along its entire backbone. It also avoids a complicated and large actuator system. Such robotic cables can be well suited for current space and terrestrial applications like exploration, teleoperation, surveillance, maintenance activities, etc., benefiting from these unique structural properties.

Recognition of human gestures is an active area of research integral for the development of intuitive human-machine interfaces for ubiquitous computing and assistive robotics. In particular, such systems are key to effective environmental designs that facilitate aging in place. Typically, gesture recognition takes the form of template matching in which the human participant is expected to emulate a choreographed motion as prescribed by the researchers. A corresponding robotic action is then a one-to-one mapping of the template classification to a library of distinct responses. In this paper, we explore a recognition scheme based on the growing neural gas (GNG) algorithm that places no initial constraints on the user to perform gestures in a specific way. Motion descriptors extracted from sequential skeletal depth data are clustered by GNG and mapped directly to a robotic response that is refined through reinforcement learning. A simple good/bad reward signal is provided by the user. This paper presents results that show that the topology-preserving quality of GNG allows generalization between gestured commands. Experimental results using an automated reward are presented that compare learning results involving single nodes versus results involving the influence of node neighborhoods. Although separability of input data influences the speed of learning convergence for a given neighborhood radius, it is shown that learning progresses toward emulation of an associative memory that maps input gesture to desired action.

Illiteracy is a global problem that impacts societal and economic growth and development, and is directly correlated with the financial success, health and overall well-being of individuals. Studies indicate that picture-book reading within a facilitated story-time setting is an important tool for language acquisition in children. The proposed research hypothesizes that in an increasingly digital society, literacy can be cultivated in a robot-embedded environment that is, at once, physical, digital and evocative of the picture-book being read. Inspired by concepts of embodied interaction, the research team proposes the design, implementation and evaluation of an intelligent, fine-tunable suite of architectural-robotic artifacts -- the LIT ROOM - distributed at room-scale in a public library setting. Through a reconfigurable, co-adaptive learning environment, the LIT ROOM aims to augment the dialogical reading of picture-books within an engaging and exploratory space for the advancement of literacy and learning.

The outcome of a multidisciplinary and iterative process, the LIT KIT is a portable, cyber-physical artifact supporting children's picture-book reading. The LIT KIT follows from the hypothesis that children's literacy can be advanced in a tangible, co-creative environment that is both physical and digital. The LIT KIT employs color, sound and movement to scaffold meaning-making through the creation of an environment that is evocative of the picture-book being read. Designed with a Sifteo™ cube [16] interface, the LIT KIT creates room-scaled audio-visual and spatial effects to both contextualize language and provide feedback during dialogical interactions between a child and an adult reader. Children can customize the LIT KIT settings to actively interpret the ideas, concepts and environments inherent in the picture-book's words and images. The LIT KIT is an outreach component, for home or classroom use, of our developing room-scaled LIT ROOM for a major public library. Presented here are motivations for the LIT KIT, and an elaboration of its design and development. Usability evaluations have begun and continue, as we further the prototype with expected completion in Summer 2013.

While the field of continuum manipulators has been the subject of increasing attention from the robotics community, knowledge of their inherent capabilities is still limited. Controllers have been proposed that exploit the null-space of redundant continuum manipulators, however studies of the nature of continuum robot null-spaces have not yet been done. In this paper, we first develop a convenient set of extensible, continuum manipulator forward kinematics and resolved-motion rate inverse kinematics. This allows us to analyze the null-space of 2-section, planar, extensible, redundant continuum manipulators to consider the underlying structure of general continuum robot self-motions and discuss their importance to real-world examples and applications.

We propose an algorithm, that extends our previous work, to estimate the current configuration of a non-rigid object using energy minimization and graph cuts. Our approach removes the need for feature correspondence or texture information and extends the boundary energy term. The object segmentation process is improved by using graph cuts along with a skin detector. We introduce an automatic mesh generator that provides a triangular mesh encapsulating the entire non-rigid object without predefined values. Our approach also handles in-plane rotation by reinitializing the mesh after data has been lost in the image sequence. Results display the proposed algorithm over a dataset consisting of seven shirts, two pairs of shorts, two posters, and a pair of pants.

We present a novel approach for classifying items from a pile of laundry. The classification procedure exploits color, texture, shape, and edge information from 2D and 3D local and global information for each article of clothing using a Kinect sensor. The key contribution of this paper is a novel method of classifying clothing which we term L-M-H, more specifically L-C-S-H using characteristics and selection masks. Essentially, the method decomposes the problem into high (H), low (L) and multiple mid-level (characteristics(C), selection masks(S)) layers and produces “local” solutions to solve the global classification problem. Experiments demonstrate the ability of the system to efficiently classify and label into one of three categories (shirts, socks, or dresses). These results show that, on average, the classification rates, using this new approach with mid-level layers, achieve a true positive rate of 90%.

A continuum manipulator, such as a multi-section trunk/tentacle robot, is promising for deft manipulation of a wide range of objects of different shapes and sizes. Given an object, a continuum manipulator tries to grasp it by wrapping tightly around it. Autonomous grasping requires realtime determination of whether an object can be grasped after it is identified, and if so, the feasible whole-arm wrapping around configurations of the robot to grasp it, which we call grasping configurations, as well as the path leading to a grasping configuration. In this paper, we describe the process for autonomous grasping from object detection to executing the grasping motion and achieving force-closure grasps, with a focus on a general analysis of all possible types of planar grasping configurations of a three-section continuum manipulator. We further provide conditions for existence of solutions and describe how to find a valid grasping configuration and the associated path automatically if one exists. Experimental results with the OctArm manipulator validate our approach, and shows that the entire process to determine an autonomous grasping operation, which includes automatic detection of the target object and determination of a grasping configuration and a path to the grasping configuration that avoids obstacles, can take just a small fraction of a second. Once a grasping configuration is reached, the manipulator can lift the object stably, i.e., a force-closure grasp can be achieved.

Illiteracy is a global problem that impacts societal and economic growth and development, and is directly correlated with the financial success, health and overall well-being of individuals. Studies indicate that picture-book reading within a facilitated story-time setting is an important tool for language acquisition in children. We hypothesize that in an increasingly digital society, literacy can be cultivated in a robot-embedded environment that is, at once, physical, digital and evocative of the picture-book being read. Inspired by concepts of embodied interaction, our developing LIT ROOM is an intelligent, fine-tunable suite of architectural-robotic artifacts distributed at room-scale in a public library setting. Presented here are motivations for and design overview of this developing interactive artifact. Through a reconfigurable, co-adaptive learning environment, the LIT ROOM aims to augment the dialogical reading of picture-books within an engaging and exploratory space for the advancement of literacy and learning.

We present a method to recover complete 3D models of articulated objects. Structure-from-motion techniques are used to capture 3D point cloud models of the object in two different configurations. A novel combination of Procrustes analysis and RANSAC facilitates a straightforward geometric approach to recovering the joint axes, as well as classifying them automatically as either revolute or prismatic. With the resulting articulated model, a robotic system is able to manipulate the object along its joint axes at a specified grasp point in order to exercise its degrees of freedom. Because the models capture all sides of the object, they are occluded-aware, enabling the robotic system to plan paths to parts of the object that are not visible in the current view. Our algorithm does not require prior knowledge of the object, nor does it make any assumptions about the planarity of the object or scene. Experiments with a PUMA 500 robotic arm demonstrate the effectiveness of the approach on a variety of objects with both revolute and prismatic joints.

In this paper, teleoperated control of a kinematically redundant, continuum slave manipulator with a non-redundant, rigid-link master system is considered. This problem is novel because the self-motion of the redundant robot can be utilized to achieve secondary control objectives while allowing the user to concentrate on controlling only the tip of the slave system. To that end, feedback linearizing controllers are proposed for both the master and slave systems, whose effectiveness is demonstrated using numerical simulations for the case of singularity avoidance as a subtask.

In this paper, we consider the modeling of robotic continuous “continuum” two-dimensional surfaces. We discuss the fundamental differences between such robot surfaces and traditional rigid link and continuum robots. We then introduce new kinematic models for continuum robotic surfaces. We compare the kinematic models to physical continuum surfaces and validate their performance.

Healthcare is becoming more digital and technological, but healthcare environments have not yet become embedded with digital technologies to support the most productive (physical) interaction between medical patients, clinical staff and the physical artifacts that surround and envelop them. This shortcoming is an opportunity for the architecture and robotics communities to interface with each other and the everyday users of healthcare environments. Our extended lab focused ten weeks on sketching in hardware a robotic, patient-room ecosystem we call home+ with the help of clinicians at the Roger C. Peace Rehabilitation Hospital of the Greenville Hospital System University Medical Center [GHS]. This early prototyping effort represents our vision for the larger robotic patient room, and identifies opportunities for more focused work on an Assistive Robotic Table (ART).

We propose an algorithm that uses energy minimization to estimate the current configuration of a non-rigid object. Our approach utilizes an RGBD image to calculate corresponding SURF features, depth, and boundary information. We do not use predetermined features, thus enabling our system to operate on unmodified objects. Our approach relies on a 3D nonlinear energy minimization framework to solve for the configuration using a semi-implicit scheme. Results show various scenarios of dynamic posters and shirts in different configurations to illustrate the performance of the method. In particular, we show that our method is able to estimate the configuration of a textureless nonrigid object with no correspondences available.

Our world is digital, physical, social and technological. Informal learning environments that are likewise digital, physical, social and technological have the potential to afford children with creative, informal learning explorations. Following from Antle's concept of "embodied child-computer interaction" and Vygotsky's "cycle of creative imagination," we demonstrate an intelligent, robotic informal learning environment at room-scale targeted for K-3 visitors to a regional children's museum. Our reconfigurable environment is, in essence, co-adaptive, allowing the physical learning environment and young students to mutually change and develop through iterative interactions.

We present a system for automatically extracting and classifying items in a pile of laundry. Using only visual sensors, the robot identifies and extracts items sequentially from the pile. When an item has been removed and isolated, a model is captured of the shape and appearance of the object, which is then compared against a database of known items. The classification procedure relies upon silhouettes, edges, and other low-level image measurements of the articles of clothing. The contributions of this paper are a novel method for extracting articles of clothing from a pile of laundry and a novel method of classifying clothing using interactive perception. Experiments demonstrate the ability of the system to efficiently classify and label into one of six categories (pants, shorts, short-sleeve shirt, long-sleeve shirt, socks, or underwear). These results show that, on average, classification rates using robot interaction are 59% higher than those that do not use interaction.

In this paper, a section of a continuum arm is modeled using lumped model elements (masses, springs and dampers). The model, although an approximation for a continuum structure, can be used to conveniently analyze the dynamics of the arm with selectable tradeoff in accuracy of modeling. Principles of lagrangian dynamics are used to derive the expressions for the generalized forces in the system. Simulation results using the model are compared with the physical measurements of a continuum arm prototype built using McKibben actuators. A brief discussion on how this relatively simple model can be more realizable when compared to other techniques of modeling continuum arms is also presented in the paper.

In this paper, we present a new approach towards the control of continuous backbone (continuum) “trunk and tentacle” robots. Development of model-based control algorithms for this new and emerging class of robots has been relatively slow due to the inherent complexity of their mathematical models. Based on the recently developed kinematics, velocity Jacobian and full dynamic model, a simple nonlinear task-space controller, established for rigid-link robots, is adapted and extended for continuum manipulators for the regulation of its tip or any location along its backbone in the task-space. This approach is applicable to all continuum robots with extension/contraction and bending capabilities. Simulation results are shown using a three-section, six degree-of-freedom planar continuum robot.

We present an algorithm for automatically unfolding a piece of clothing. A piece of laundry is pulled in different directions at various points of the cloth in order to flatten the laundry. The features of the cloth are extracted and calculated to determine a valid location and orientation in which to interact with it. The features include the peak region, corner locations, and continuity / discontinuity of the cloth. In this paper we present a two-stage algorithm, introducing a novel solution to the unfolding / flattening problem using interactive perception. Simulations using 3D simulation software, and experiments with robot hardware demonstrate the ability of the algorithm to flatten pieces of laundry using different starting configurations. These results show that, at most, the algorithm flattens out a piece of cloth from 11.1% to 95.6% of the canonical configuration.

We discuss disciplinary barriers which have traditionally prevented robotics from significantly impacting the built (architectural) environment we inhabit. Specifically, we describe the implementation of, and lessons learned from, a multidisciplinary graduate-level course in Architectural Robotics. The results from class interactions and projects provide insight into novel ways in which robotics expertise can be effectively leveraged in architecture. Conversely, our outcomes suggest ways in which the knowledge and perspective of architects could stimulate significant innovations in robotics.

Robotics research tends to focus upon either non-contact sensing or machine manipulation, but not both. This paper explores the benefits of combining the two by addressing the problem of classifying unknown objects, such as found in service robot applications. In the proposed approach, an object lies on a flat background, and the goal of the robot is to interact with and classify each object so that it can be studied further. The algorithm considers each object to be classified using color, shape, and flexibility. Experiments on a number of different objects demonstrate the ability of efficiently classifying and labeling each item through interaction.

Intelligent Systems can effectively bridge the wondrous world of childhood and the adult world of rules, goals and expectations. This paper explores the possibility of an embodied child-computer interaction that cultivates creativity - a core value of the successful adult in an increasingly digital society. We draw specifically on the Reggio Emilia method of education, not by adding to it PCs (as has been done, with mixed results), but instead, by respecting its focus on haptics - on the handling of physical things as a way of learning - embedding computation in the very fabric of the physical environment. We call this embodied system a Creativity Support Environment to emphasize the role of the physical environment as, itself, a "teacher" of creativity.

“AWE” is a programmable “Animated Work Environment” supporting everyday human activities, at home, work and school, in an increasingly digital society. AWE features a novel robotic “wall,” three horizontal, reconfigurable work surfaces, and embedded information technologies. The video shows AWE as a digital simulation moving through six standard wall-desk configurations, interspersed with still photos and video clips of people interacting with the physical, full-scale, working prototype. The video also shows AWE beginning to behave intelligently as well as users fine-tuning AWE's configurations by gesturing proximity sensors mounted at the hinges between wall panels. Usability testing suggests that AWE clearly adapts to variations in complex activities involving users working or playing in a single physical space with both physical and digital tools and artifacts.

We present a new geometrical approach to solving inverse kinematics for continuous backbone (continuum) robot manipulators. First, this paper presents a solution to the inverse kinematics problem for a single-section trunk. Assuming end-points for all sections of a multi-section trunk are known, this paper then details applying single-section inverse kinematics to each section of the multi-section trunk by compensating for resulting changes in orientation. Finally, an approach which computes per-section endpoints given only a final-section endpoint provides a complete solution to the multi-section inverse kinematics problem. The results of implementing these algorithms in simulation and on a physical continuum robot are presented and possible applications are discussed.

Continuum robotic manipulators, termed trunks, mimic the astounding capabilities of elephant trunks and octopus arms by bending in smooth arcs. Several approaches to kinematic analysis of continuum trunks complement a wide variety of available continuum robots. However, these kinematics exhibit singularity-like conditions when the trunk assumes a straight posture, which is essential to complete many tasks. The novel limiting-case analysis presented in this paper eliminates these problems, demonstrating that the unique causes of the problem are rooted in the continuum formulation and cannot be solved by traditional rigid-link singularity analysis. Three practical examples demonstrate the necessity of this analysis presented, enabling the trunk to successfully perform each task.

In this paper, a new dynamic model for continuum robot manipulators is derived. The dynamic model is developed based on the geometric model of extensible continuum robot manipulators with no torsional effects. The development presented in this paper is an extension of the dynamic model proposed by Mochiyama and Suzuki (2002) to include a class of extensible continuum robot manipulators. Numerical simulation results are presented for a planar 3-link extensible continuum robot manipulator.

Summary form only given. Continuum robots are biologically-inspired by the invertebrate organisms such as octopus arms and elephant trunks. These robots with a backbone-less structure offer a superior performance in unstructured and cluttered environments such as collapsed buildings, unknown geographical terrain, holes and tunnels. This video features OctArm, a continuum robot that demonstrates its capabilities in whole arm manipulation, biologically-inspired maneuvering, and grasping. The video also depicts a 3D graphical model of OctArm in that can be rendered in real-time in Matlab's real-time workshop.

In this paper, the dynamic model for planar continuum manipulators that was presented in our previous work is extended to include new terms reflecting the effects of potential energy. First the gravitational potential energy of the manipulator is derived. Then, the elastic potential energy of the manipulator is derived for both bending and extension. Finally, the effects of the total potential energy are included in the dynamic model. Numerical simulation results are presented for a planar 3-section extensible continuum robot manipulator. The results show a much stronger match to physical continuum robots than with previously available models.

Continuum or hyper-redundant robot manipulators can exhibit behavior similar to biological trunks, tentacles, or snakes. Unlike traditional rigid-link robot manipulators, continuum robot manipulators do not have rigid joints, hence these manipulators are extremely dexterous, compliant, and are capable of dynamic adaptive manipulation in unstructured environments. However, the development of high-performance control algorithms for these manipulators is quite a challenge, due to their unique design and the high degree of uncertainty in their dynamic models. In this paper, a controller for continuum robots, which utilizes a neural network feedforward component to compensate for dynamic uncertainties is presented. Experimental results using the OCTARM, which is a soft extensible continuum manipulator, are provided to illustrate that the addition of the neural network feedforward component to the controller provides improved performance.

This paper introduces new analyses and algorithms which are essential for the practical implementation of continuous backbone continuum robots. Actuator length limits strongly shape the configuration or joint space of continuum manipulators, introducing couplings which are not reflected in previously published kinematic models. These unmodeled effects significantly restrict the practical application of previously established kinematic models on continuum robot hardware. This paper presents a new analysis of the effects of actuator limits on continuum robots. Based on the new understanding of the configuration space uncovered, we derive for the first time the configuration space of continuum robots when constrained by actuator length limits. These contributions are essential for effective use of a wide range of continuum robots and have been implemented and tested on two different types of continuum robots. Results and insight gained from this implementation are presented

This paper describes the results of field trials and associated testing of the OctArm series of multi-section continuous backbone "continuum" robots. This novel series of manipulators has recently (Spring 2005) undergone a series of trials including open-air and in-water field tests. Outcomes of the trials, in which the manipulators demonstrated the ability for adaptive and novel manipulation in challenging environments, are described. Implications for the deployment of continuum robots in a variety of applications are discussed

In contrast to traditional robotic manipulators composed of rigid links, a continuum manipulator is a long, continuously flexible extremity that grasps objects usingthe entire length of the trunk. OctArm, a three-section continuum manipulator composed of 9 McKibben actuators, was mounted on tracked mobile platform and teleoperated in a series of field and laboratory experiments. Results from these experiments show its ability to grasp objects of many shapes and sizes, retain a solid hold despite vibration or changes in acceleration, cradle fragile objects reliably, and operate in extreme environments. This robust featureset shows the usefulness and strong potential of these manipulators.

Though a large number continuum robots exist, little work has been done to accurately and effectively visualize these devices in three dimensions. Like octopus arms and elephant trunks, these robots lack discrete joints, instead bending in smooth, continuous curves. Three-dimensional visualization of traditional rigid-link robots is both well established and extensively used in modeling, simulation, design, and operation of these robots. Providing three-dimensional visualization techniques extends these benefits, considered essential for rigid-link robots, to continuum robots. This paper presents a highly flexible three-dimensional visualization technique which executes in realtime for a large class of continuum robots. The results of this technique are then applied to two different continuum manipulators which are representative of most continuum robot designs, demonstrating the wide applicability of this method

Allowing dynamic motions for payloads within a workcell is a fundamentally novel idea for practical industrial robots. The ability to handle payloads moving in semi-structured ways would significantly increase the potential markets for industrial robotics. However, due to the inherent time delay between complex sensing and manipulation, the manipulation fails in some circumstances. Therefore, in this paper, we propose a generic method to model the dynamic intercept and manipulation capability of vision based industrial robot systems. In order to verify the method, we present experiments using our industrial workcell prototype to dynamically intercept and manipulate semi-randomly moving objects. We conduct experiments over 1000 runs with two different kinds of dynamic tasks, "scoop" and "trap." The experimental results validate our theory

This paper introduces three algorithms which are essential for the practical, real-time implementation of continuum robots. Continuum robots lack the joints and links which compose traditional and high-degree-of-freedom robots, instead relying on finite actuation mechanisms to shape the robot into a smooth curve. Actuator length limits shape the configuration or joint space of continuum manipulators, introducing couplings analyzed in this paper which must be understood to make effective use of continuum robot hardware. Based on the new understanding of the configuration space uncovered, this paper then derives the workspace of continuum robots when constrained by actuator length limits. Finally, a tangle/untangle algorithm correctly computes the shape of the distal segments of multisection tendon-actuated continuum robots. These contributions are essential for effective use of a wide range of continuum robots, and have been implemented and tested on two different types of continuum robots. Results and insight gained from this implementation are presented

We introduce a new method for synthesizing kinematic relationships for a general class of continuous backbone, or continuum , robots. The resulting kinematics enable real-time task and shape control by relating workspace (Cartesian) coordinates to actuator inputs, such as tendon lengths or pneumatic pressures, via robot shape coordinates. This novel approach, which carefully considers physical manipulator constraints, avoids artifacts of simplifying assumptions associated with previous approaches, such as the need to fit the resulting solutions to the physical robot. It is applicable to a wide class of existing continuum robots and models extension, as well as bending, of individual sections. In addition, this approach produces correct results for orientation, in contrast to some previously published approaches. Results of real-time implementations on two types of spatial multisection continuum manipulators are reported.

We introduce a new method for synthesizing kinematics and Jacobian relationships for an important class of continuous backbone “continuum” robots. The resulting Jacobians enable task and shape control by relating work space (Cartesian) coordinates to actuator inputs (tendon lengths, pneumatic pressures, etc.), via robot shape coordinates. The approach, which is applicable to a wide class of existing continuum robots, also features the capability of including extension, as well as bending, of individual sections. The approach is also shown to produce correct results for orientation, in contrast to previously published approaches. Results of a real-time implementation of the method on a multisection continuum manipulator are reported.

This paper presents new results for intuitive teleoperation of continuous backbone "continuum" robot manipulators. Continuum robots present unique challenges due to the nonintuitive (to humans) nature of their basic movements. We present a series of mappings, at both position and velocity levels, which provide human operators with a versatile and intuitive suite of options for joystick control of continuum robots. Results from implementations on two types of continuum manipulator hardware are summarized.

In this paper, we describe the design and implementation of a novel multi-section, continuous-backbone ("continuum") robot. The design is based on an innovative "hose-in-hose" concept. Its implementation is novel with respect to previous continuum robot designs in that stiffness and extension, in addition to bending, are actively controlled in each section of the robot. This requires a non-trivial extension of previously proposed kinematic models, and poses challenges for real-time control of the robot. We introduce a tangling/untangling algorithm to map between overall cable lengths and per-section cable lengths. Details of the design and its implementation are presented, along with a summary of real-time control issues and experimental results.

Several factors must be considered for robotic task execution in the presence of a fault, including: detection, identification, and accommodation for the fault. In this paper, a nonlinear observer is used to identify a class of actuator faults once the fault has been detected by some other method. Advantages of the proposed fault-identification method are that it is based on the nonlinear dynamic model of a robot manipulator (and hence, can be extended to a number of general Euler Lagrange systems), it does not require acceleration measurements, and it is independent from the controller. A Lyapunov-based analysis is provided to prove that the developed fault observer converges to the actual fault. Experimental results are provided to illustrate the performance of the identification method.

Several factors must be considered for robotic task execution in the presence of a fault, including: detection, identification, and accommodation for the fault. In this paper, a prediction error based dead-zone residual function and nonlinear observers are used to detect and identify a class of actuator faults. Advantages of the proposed fault detection and identification methods are that they are based on the nonlinear dynamic model of a robot manipulator (and hence, can be extended to a number of general Euler Lagrange systems), they do not require acceleration measurements, and they are independent from the controller. A Lyapunov-based analysis is provided to prove that the developed fault observer converges to the actual fault.

Visual sensing for robotics has been around for decades, but our understanding of a timing model remains crude. By timing model, we refer to the delays (processing lag and motion lag) between "reality" (when a part is sensed), through data processing (the processing of image data to determine part position and orientation), through control (the computation and initiation of robot motion), through "arrival" (when the robot reaches the commanded goal). In this study, we introduce a timing model where sensing and control operate asynchronously. We apply this model to a robotic workcell consisting of a Sta/spl uml/ubli RX-130 industrial robot manipulator, a network of six cameras for sensing, and an off-the-shelf Adept MV-19 controller. We present experiments to demonstrate how the model can be applied.

In this paper, we consider the problem of task-space tracking control of robot manipulators. Based on a quaternion representation of the end-effector orientation, we design a class of task-space controllers that ensure asymptotic end-effector position and orientation tracking. To facilitate the control design, we first develop model-based and adaptive full-state feedback controllers. We then present a model-based output feedback controller that eliminates link velocity measurements via a model-based observer. The application of the proposed control strategy to redundant robots is also discussed. Simulation results based on a six-link manipulator system are presented for the output feedback controller.

The investigation of continuum robots has become an area of considerable interest in the last several years. Unlike conventional robotic manipulators which bend in discrete locations, continuum robots bend over continuous sections. One of the main issues that is hampering research in this area is the determination of the robot's shape. In this paper we present a shape-determining scheme that is based on machine vision. The approach uses a high speed camera, an engineered environment, and image processing to determine the shape of our continuum robot called the Elephant's Trunk Manipulator. We present experimental results showing the effectiveness of the technique.

Visual sensing for robotics has been around for decades, but our understanding of a timing model remains crude. By timing model, we refer to the delays (processing lag and motion lag) between "reality" (when a part is sensed), through data processing (the processing of image data to determine part position and orientation), through control (the computation and initiation of robot motion), through "arrival" (when the robot reaches "reality"). In this work we introduce a timing model where sensing and control operate asynchronously. We apply this model to a robotic workcell consisting of a Staubli RX-130 industrial robot manipulator, a network of six cameras for sensing, and an off-the-shelf Adept MV-19 controller. We demonstrate some experiments to show how the model is applied.

Continuum manipulators are robotic manipulators built using one continuous, elastic and highly deformable "backbone", instead of multiple rigid links and joints. In previous work (2000), we illuminated various kinematic and dynamic properties of continuum robots, but the question of controller design remained open. This paper presents a basic result for continuum robots that has long been known for rigid-link robots: a simple PD-plus-feedforward controller can exponentially regulate the position of a manipulator.

In this paper we discuss the application of our recently developed nonlinear analytical redundancy (NLAR) fault detection technique to a two-degree of freedom robot manipulator. NLAR extends the traditional linear AR technique to derive the maximum possible number of fault detection tests into the continuous nonlinear domain. The ability to handle nonlinear systems vastly expands the accuracy and viable applications of the AR technique. The effectiveness of the approach is demonstrated through an example.

As manipulators, robot arms are woefully under-utilized in modern industrial workcells. The norm involves little or no sensing, the grasp of a single known object, and the execution of a single geometric motion. In contrast, the popular ideal of a visually guided arm (as for a human) should be able to track and grab relatively arbitrary objects, under relatively arbitrary motions, across a comfortable range of velocities. Our ongoing research aims at extending these capabilities in a modern industrial workcell. We outline a framework in which these capabilities might be measured, and demonstrate experimentally the capabilities of our current prototype.

Continuum manipulators, inspired by the natural capabilities of elephant trunks and octopus tentacles, may find niche applications in areas like human-robot interaction, multiarm manipulation, and unknown environment exploration. However, their true capabilities will remain largely inaccessible without proper analytical tools to evaluate their unique properties. Ellipsoids have long served as one of the foremost analytical tools available to the robotics researcher, and the purpose of this paper is to first formulate, and then to examine, three types of ellipsoids for continuum robots: manipulability, force, and compliance.

We focus on a class of robotic manipulators that utilize continuous backbone structures. Such manipulators, known as "continuum" robots, exhibit behavior similar to tentacles, trunks, and snakes. Specifically, we have previously discussed some of the mechanical and kinematic details of the Clemson -Tentacle Manipulator." This work examines the dynamic characteristics of this manipulator, proposing a vibration damping control strategy for configurations with the worst vibration characteristics. We begin by formulating the dynamics for one section of the Tentacle Manipulator. We then proceed to develop a vibration control strategy which incorporates a setpoint regulator. We supplement the theoretical developments with experimental results.

A Simulink robotic toolkit (SRTK) for the Puma 560 robot manipulator is developed on the MATLAB/Simulink-based platform. Through the use of the real-time Linux target and the real-time Windows target, the SRTK can be executed on the Linux or Win32-based operating systems in real-time. Moreover, the graphical user-friendly nature of Simulink allows the SRTK to be a flexible tool that can easily be customized to fit the specific needs of the user, that is, based on the layered approach of the SRTK, the user can perform operations such as calibration, joint control, Cartesian control, Cartesian PD control, impedance control, some trajectory generation tasks, and real-time simulation of the Puma 560 through a user-friendly MATLAB-based graphical user interface without writing any code. The SRTK allows a researcher to use the Puma 560 without the burden of the external issues related to the control, interface, and software issues, while providing for the flexibility for easily modifying components for increased functionality.

Manipulability and force ellipsoids have long been a useful tool for analyzing the relative capabilities of robotic, manipulators to move in, or to exert forces in, certain directions. The purpose of this paper is to first formulate, and then to examine, the manipulability and force ellipsoids for continuum robots. Continuum robots have continuously flexible backbones; consequently, their infinite-dimensional kinematics present special challenges in the formulation and interpretation of ellipsoids.

We present a novel approach to the workcell design for enhanced performance of industrial robot manipulators, in which the workcell features a specially integrated sensor network. In contrast to traditional robot workcells, in which the role of environmental sensors (if present at all) is relatively inflexible and tightly focused on a specific task, the sensor network performs real-time dynamic sensing of the entire workcell. The system makes use of "off the shelf" components, and integrates them with the existing industrial robot controller, to allow the manipulator to perform more dynamic operations in a less structured workcell. Details of the novel sensor networked workcell and experiments with an industrial robot are presented.

This paper describes a novel technique, based on interval methods, for estimating reliability using fault trees. The approach encodes inherent uncertainty in the input data by modeling these data in terms of intervals. Appropriate interval arithmetic is then used to propagate the data through standard fault trees to generate output distributions which reflect the uncertainty in the input data. Through a canonical example of reliability estimation for a robot manipulator system, we show how the use of this novel interval method appreciably improves the accuracy of reliability estimates over existing approaches to the problem of uncertain input data. This method avoids the key problem of loss of uncertainty inherent in some approaches when applied to noncoherent systems. It is further shown that the method has advantages over approaches based on partial simulation of the input-data space because it can provide guaranteed bounds for the estimates in reasonable times.

We introduce a new approach to fault detection for robot manipulators. The technique, which is based on the isolation of fault signatures via filtered torque prediction error estimates, does not require measurements or estimates of manipulator acceleration as is the case with some of the previously suggested methods. The method is formally demonstrated to be robust under uncertainty in the robot parameters. Furthermore, an adaptive version of the algorithm is introduced, and shown to both improve coverage and significantly reduce detection times. The effectiveness of the approach is demonstrated by experiments with a two-joint manipulator system.

We consider a class of robotic manipulators generally termed "hyper-redundant". Specifically, we seek to examine some of the kinematic properties of "continuum" hyper-redundant robots. Unlike the case with rigid-link robots, there is no commonly accepted formula for describing continuum robot kinematics. Although these manipulators are continuously flexible, they are actuated with a finite number of actuators. We discuss two possible options for mapping desired infinite-dimensional robot shapes to the finite-dimensional actuator space, using "natural" and "wavelet" decompositions. We compare and contrast these kinematic descriptions, illustrating how the wavelet decomposition can simplify the inverse kinematics for redundant planar continuum robots.

The interactions between a robot and its environment involving sudden contact and impact comprise the key elements of impulsive manipulation. Of the collision models in use in robotics to date no one model is able to capture the richness of impulsive manipulation in impact and grasping analysis. Thus, we introduce an algebraic collision law specifically tailored to robotic interactions such as grasping. Synthesizing an algebraic collision law given in other arenas with the operational contact inertia matrix, we obtain an impulsive manipulation model which is consistent with the laws of physics and also computationally efficient. This law has potential uses in many aspects of dynamic simulation and manipulation.

Over the past several years, there has been a rapidly expanding interest in the study and construction of a new class of robot manipulators which utilize high degree of freedom, or continuous, backbone structures. In this paper, we consider and illustrate some basic properties of a class of "hyper-redundant" robots, known as "continuum" robots. We base our analysis around remotely-driven, tendon-actuated manipulators, such as the Rice/Clemson "Elephant's Trunk". We discuss such issues as the kinematic model, the relationship between tendon lengths and bending, and desirable design constraints for continuum robot mechanisms.

The idea of studying tentacle and trunk type biological manipulation is not new, but there has been little progress in the development and application of physical devices to simulate these types of manipulation. Our research in this area is centered on a novel elephant trunk robot. We review the construction of the robot and how it compares to biological manipulators. We then apply our previously designed kinematic model to describe the kinematics of the robot. We finish by providing some examples of intelligent manipulation using the robot.

In this paper, we introduce a new approach to fault detection for robot manipulators. The technique, which is based on the isolation of fault signatures via filtered torque prediction error estimates, does not require measurements or estimates of manipulator acceleration as is the case with some previously suggested methods. The method is formally demonstrated to be robust under uncertainty in the robot parameters. Furthermore, an adaptive version of the algorithm is introduced, and shown to both improve coverage and significantly reduce detection times. The effectiveness of the approach is demonstrated by experiments with a two-joint manipulator system.

There exist in robotics, as in many other disciplines, problems described by an underdetermined set of constraints, possessing an infinite number of solutions. The problem of robot manipulator redundancy resolution is just such a situation, requiring that a particular solution be chosen according to some type of optimization criterion. One possibility employs a type of optimization which minimizes the maximum magnitude of the solution vector. This is the minimum infinity norm solution, also known as the "minimum effort solution." The paper explores the details of least infinity norm optimization, using kinematic redundancy resolution as a test case to explore the details of infinity-norm optimization. We introduce for the first time a closed-form expression for minimum effort solutions, illustrating the heretofore unknown properties of nonuniqueness and discontinuity in time-varying situations, and postulating a possible remedy for the discontinuity problem. Additionally, to reinforce the mathematics, simulations of four-link robots are included, as well as an extended discussion of minimum-effort solutions from a geometric point of view.

In this paper, we describe the hardware and control architecture of a novel four-fingered dextrous robot hand. The benefits of the unusual arrangement of the fingers (which resembles that in raptors and other birds) in the hand are discussed. Kinematic models for the fingers and transmission system are presented. A simulation and real-time control environment has been developed for the hand, and is discussed in the paper. Experiments in dextrous and dynamic manipulation using the hand are also detailed.

We consider the case for adopting a truly 'digital' type of robot, which would evolve between a discrete and finite set of states. One distinct advantage of this philosophy is that a formal logical analysis can be applied to digital robots, since discrete-time models can now correctly and completely model the robot behavior. We argue that there are significant benefits to this strategy in numerous cases, especially with respect to fault detection and fault tolerance. However, there are also disadvantages-in order to guarantee digital behavior, constraints on the robot's operations are imposed. Essentially, we gain formality of digital analysis at the expense of precision of continuous movement. Using an analogy to digital electronics, we discuss ways in which the development of digital robots could revolutionize certain aspects of robotics.

Techniques for determining and correcting threaded part alignment using force and angular position data are developed to augment currently limited techniques for aligning threaded parts. These new techniques are based on backspinning a nut with respect to a bolt and measuring the force change that occurs when the bolt "falls" into the nut. Kinematic models that describe the relationship between threaded parts during backspinning are introduced and are used to show how angular alignment may be determined. The models indicate how to distinguish between the aligned and misaligned cases of a bolt and a nut connection by using axial force data only. In addition, by tracking the in-plane relative attitude of the bolt during spinning, data can be obtained on the direction of the angular misalignment which, in turn, is used to correct the misalignment. Results from experiments using a bolt held in a specialized fixture and a three fingered Stanford/JPL hand are presented.

Techniques for determining and correcting threaded part alignment using minimal force and angular position data are developed to augment currently limited techniques for aligning threaded parts. These new techniques ore based on backspinning a nut with respect to a bolt and measuring the force change that occurs when the bolt "drops" into the nut. Kinematic models that describe the relationship between threaded parts during backspinning are introduced and are used to show how angular alignment may be determined. The models indicate how to distinguish between the aligned and misaligned cases of a bolt and a nut connection by using axial force data only. In addition, by tracking the in-plane relative attitude of the bolt during spinning, data can be obtained on the direction of the angular misalignment which, in turn, is used to correct the misalignment. Results from experiments using a bolt held in a specialized fixture and a Stanford/JPL hand are presented.

This paper describes the innovative use of a genetic algorithm to solve the grasp synthesis problem for multifingered robot hands. The goal of our algorithm is to select a 'best' grasp of an object, given some information about the object geometry and some user-defined 'fitness functions' which intuitively delineate 'good' from 'bad' grasp qualities. The fitness functions are used by the specially designed genetic algorithm, which iteratively selects the grasp. The approach is biologically inspired both in the use of the genetic algorithm to 'evolve' populations of candidate grasps, and in the choice of fitness functions, which adapt intuition from nature to guide the evolution process.

There are numerous situations in robotics where it becomes desirable to minimize the maximum magnitude of a solution to an underdetermined set of linear equations. For example, there have been several approaches to finding the joint velocities of kinematically redundant robots using this philosophy. Unfortunately, the solution of this optimization problem, known as the "minimum infinity-norm solution", cannot be expressed in a closed form in general thus requiring the use of an algorithm to iteratively refine an initial guess before reaching the desired solution. In order to increase our understanding and reduce the complexity of infinity-norm algorithms, we first formulate a new "infinity inverse", and then use the new inverse to explore critical issues such as uniqueness and continuity of least infinity-norm solutions. The new inverse is compared with the well-known pseudoinverse, or minimum two-norm solution. We discuss when and why one particular norm might produce a better solution than the other, reinforcing the discussion with an interesting example of a kinematically redundant manipulator.

We consider the grasping and manipulation strategies of raptors, focusing on the particularly successful case of the osprey. The osprey makes superb use of its two four-digit feet, each of which has five degrees of freedom. As manipulation strategies exploit not only quasistatic but also dynamic grasping, particularly in fishing, for which the bird is highly renowned. We investigate the unusual kinematic design of the osprey foot, and consider the capabilities of the foot for achieving stable grasps. We also perform a dynamic analysis of the osprey in fishing, where the talons dynamically impact the fish. Implications for robot hand design and dynamic grasping are discussed.

The adoption of efficient online fault detection and isolation (FDI) tools is becoming of the utmost importance for robots, especially for those operating in remote or hazardous environments, where a high degree of safety and self-diagnostics capabilities is required. In this paper a new observer-based approach to fault detection and isolation for robot manipulators is proposed. A nonlinear observer of the system's outputs, joint position and velocities, is designed directly in the discrete-time domain; in order to improve the robustness of the observer to unknown dynamics and discretization errors, a linear feedback of the observation error and a delayed nonlinear compensation action are added. The residuals for the detection of both sensor and actuator failures are then generated from the observation errors. Simulation results show the effectiveness of the proposed approach, even if a relatively low sampling rate is adopted and in the presence of large modeling errors.

A technique for determining threaded part alignment using minimal force and angular position data is developed. This technique is based on backspinning a nut with respect to a bolt and measuring the force spike that occurs when the bolt "drops" into the nut. Kinematic models that describe the relationship between threaded parts during backspinning are presented and are used to show how angular alignment may be determined. The models indicate that it may be possible to distinguish between the aligned and misaligned cases between a bolt and a nut by using axial force data only. In addition, by tracking the in-plane relative attitude of the bolt during spinning, data can be obtained on the direction of the angular misalignment. Results from experiments using a bolt held in a Salisbury hand are presented.

This paper investigates the use of an infinity norm in formulating the optimization measures for computing the inverse kinematics of redundant arms. The infinity norm of a vector is its maximum absolute value component and hence its minimization implies the determination of a minimum effort solution as opposed to the minimum-energy criterion associated with the Euclidean norm. In applications where individual magnitudes of the vector components are of concern, this norm represents the physical requirements more closely than does the Euclidean norm. We first study the minimization of the infinity-norm of the joint velocity vector itself, and discuss its physical interpretation. Next, a new method of optimizing a subtask criterion, defined using the infinity-norm, to perform additional tasks such as obstacle avoidance or joint limit avoidance is introduced. Simulations illustrating these methods and comparing the results with the Euclidean norm solutions are presented.

The incorporation of fault tolerance techniques into robot systems improves the reliability, but also increases the hardware and computational requirements in the overall system. It is not always clear how to evaluate the merit, or 'effectiveness' of different fault tolerance approaches for a given application. We present a new set of performance criteria designed to measure and compare the effectiveness of robot fault tolerance strategies. The measures, which are designed to evaluate fault tolerance/performance/cost tradeoffs, can also be used to evaluate pure performance or pure fault tolerance strategies. We show their usefulness using a variety of proposed fault tolerance approaches in the literature focusing on multiprocessor control architectures.

Due to the coupling in the dynamics equations, coarse-grain parallelism of robot control algorithms is particularly difficult. We have developed a new algorithm based on the Newton-Euler dynamics formulation that overcomes the serial nature of these equations, allowing a high level of parallelism. Our controller uses data from a previous control step in current calculations to allow many more tasks to be executed in parallel, thus providing higher control update rates. The use of 'stale' data is an effective solution to the speedup problem, but presents some special difficulties. One stability issue when using 'stale' data that is encountered in previous approaches is discussed here, along with a partial solution to the problem.

Teleoperation continues to be a primary control mode in robotics applications, particularly for robots with complex hands. This paper details a novel method of teleoperation of complex anthropomorphic robotic hands: converting the myoelectric signal (generated by the operator's muscles during movement) into robot commands replicating the motion. Myoelectric prosthetic hands have used this user interface for over two decades; however, the feasibility of using this approach for commanding more than one degree-of-freedom, as in the pincher type grip in current myoelectric hands, has been in question. The research described in this paper addresses myoelectric control of NASA/Johnson Space Center's sixteen degree-of-freedom Utah/MIT Dextrous Hand for two grasping (key and chuck) options and three thumb motions (abduction, extension, and flexion). We discuss myoelectric signal processing approaches, data collection apparatus, and a realtime teleoperation implementation. We also present results in realtime discrimination of key and chuck grasps and offline discrimination of thumb motions. Our results include a 90% correct grasp selection rate and an 87% correct thumb motion selection, both using the myoelectric spectrum.

In this paper, the authors present a new control algorithm for multiple cooperating mechanisms manipulating a common object, with rolling contact between the end-effectors and the object. The algorithm is based on a new dynamic formulation, in which the rolling degrees of freedom between the end-effector and the object are modeled as one or more unactuated joints of the manipulator. Such an augmentation of the rolling contacts imparts each manipulator with additional degrees of freedom and could also make it kinematically redundant. This can be exploited for the satisfaction of a secondary subtask criterion such as collision avoidance. In addition, a control law can be specified that enables simultaneous control of the object trajectory, the internal forces in the object and the trajectories of the contact points on the object or the end-effecters.

In this paper, we consider the case of the raccoon, which has a dextrous five fingered hand and is renowned for its skills in dextrous manipulation. The kinematics of the raccoon hand are examined, and some critical differences and deficiencies with respect to the human hand design noted. We show how the raccoon successfully employs novel manipulation strategies in cases where the kinematics of its hands appear limited. Implications for the design and application of dextrous robotic hands are discussed.

This paper presents a layered fault tolerance framework containing new fault detection and tolerance schemes. The framework is divided into servo, interface, and supervisor layers. The servo layer is the continuous robot system and its normal controller. The interface layer monitors the servo layer for sensor or motor failures using analytical redundancy based fault detection tests. A newly developed algorithm generates the dynamic thresholds necessary to adapt the detection tests to the modeling inaccuracies present in robotic control. Depending on the initial conditions, the interface layer can provide some sensor fault tolerance automatically without direction from the supervisor. If the interface runs out of alternatives, the discrete event supervisor searches for remaining tolerance options and initiates the appropriate action based on the current robot structure indicated by the fault tree database. The layers form a hierarchy of fault tolerance which provide different levels of detection and tolerance capabilities for structurally diverse robots.>

Kinematic redundancy of robotic manipulators has been known to be useful in accomplishing additional performance on top of the main task of tracking desired end effector trajectories. Robustness has been a major concern in manipulator control where exact physical properties of manipulators are unobtainable. In this paper, we review a method of analyzing robustness of joint space controllers for manipulators, and extend the analysis to end effector space control for the first time. We then generalize the approach to the case of kinematically redundant manipulators by introducing the redundancy as part of the manipulator states, and show that kinematic redundancy is useful in making manipulator controllers more robust. The final result of this paper is an optimization problem whose solution determines the self-motion which optimizes the system robustness.>

This paper introduces new methods to evaluate the effects of impact and contact forces on robot manipulators. New measures of the vulnerability of any arm to impacts in varying directions are given. Impact ellipsoids corresponding to these measures are defined and analyzed. Examples showing 'good' and 'bad' configurations for contacts and tasks of different types are presented.>

A unified method for the instantaneous kinematics of redundant, nonredundant and in-parallel manipulators is developed. For redundant arms, we investigate the relationship between kinematic and algorithmic singularities when the method of extended Jacobian is used for task optimization. Under the same model, it is found that, for serial manipulators to move in a point-to-point fashion and for general motion of in-parallel manipulators, their instantaneous kinematics take a similar format as the method of extended Jacobian for redundant arms. Thus, our method of solution can be applied to these manipulators. Several features for the manipulators are demonstrated based on the concept of task separation in the row space of the Jacobian of these manipulators.>

Autonomous robotic fault detection is becoming increasingly important as robots are used in more inaccessible and hazardous environments. Detection algorithms, however, are adversely effected by the model simplification, parameter uncertainty, and computational inaccuracy inherent in robotic control, leading to an unacceptable number of false alarms and overzealous fault tolerance. The algorithms must use thresholds to mask out these errors. Typically, the thresholds are empirically determined from a specific robot trajectory. The effect of modeling inaccuracy, however, fluctuates dynamically as the robot moves and failures occur. The thresholds need to be dynamic and respond to the changes in the robot system so as to differentiate between real failures and misalignment due to modeling errors. This paper first summarizes the reachable measurement intervals (RMI) method of computing dynamic thresholds and then, learning from the robot-oriented analysis of RMI, presents a more efficient threshold generation method using the manipulator dynamics property of linearity in parameters.>

This paper introduces new methods to evaluate the effects of impact and contact forces on single and multiple robot manipulators. New measures of the vulnerability of any arm to impacts in varying directions are given. Impact ellipsoids corresponding to these measures are defined and analyzed. The effect of different configurations of kinematically redundant arms on (potentially damaging) impact forces at their end effectors during contact with the environment are investigated. New methods for examining the optimal configurations of redundant manipulators under impact task constraints are discussed. Examples showing "good" and "bad" configurations for contacts and tasks of different types are presented. Application of the methods to multiple cooperating arms is considered. Contact due to additional manipulators grasping, or regrasping, a common object held by one or more manipulators is analyzed. Applications to planning and simulation of manipulation of commonly held objects by multiple arms are discussed.>

Presents an analysis of the mechanics for multi-fingered grasps of planar objects. The main feature in the approach followed is a novel decomposition of the contact finger forces. At each grasp point, a contact force is resolved into components along the normal and tangential directions. This concept of decomposition gives deeper physical insights into the roles of the normal and tangential finger force components for multi-fingered manipulation.

The authors introduce a novel formulation of subtask performance for redundant manipulators. This formulation uses the singularity robust inverse (SRI), which is effective in yielding feasible joint motions in single regions, in conjunction with a homogeneous-like joint velocity component to perform an additional subtask such as obstacle avoidance. This novel inverse kinematic scheme enables the manipulator to overcome singularities (or, more accurately, avoid infeasible joint motions at or near singular configurations) and avoid obstacles in addition to the main motion task. The attractive aspect of this scheme is that it results in the satisfaction of two subtasks without requiring two explicit subtask criteria. This is because one of the subtasks, i.e., feasible joint motion, is implicitly incorporated in the particular solution in the form of the SRI. As depicted in simulations, the proposed formulation proves to be an effective inverse kinematic solution in singular regions of the manipulator workspace.>

Remote manipulation of objects can provide for safer construction and operations in extreme environments such as space, underwater, and disaster areas. For manipulation of objects designed for human use such as levers, handles, knobs, and so forth, a dexterous hand is desirable. Robots can be operated in remote locations as telerobots with supervision by the human operator but with a certain degree of local autonomy. This requires some intelligence at the remote site. We describe recent work related to intelligent grasping by a dexterous mechanical hand. In order to provide robot hands with intelligence required for effective multifingered grasping, a strategy of grasp reasoning is being developed to plan the grasp so that the fingers will be guaranteed to firmly grasp the object during handling and generate fine motion to perform tasks using the same planned grasp points. Grasp planning strategies based upon heuristic experiences from the motions of human hands and fingers may experience difficulties when applied to the grasp of mechanical hands and fingers due to lack of precise sensing devices. This paper proposes a planned strategy for grasping based on mechanics principles and codes the grasp mechanics into an expert system which has been applied in graphic simulation. This system can be used to reason and make decisions of grasp points on any polygonal object. This strategy has the advantages of being intelligence based and computationally efficient without sacrificing the physics of the grasp. The method will be useful in real-time applications of sophisticated robot hands by reducing the complexity both in planning and control. This system cm have applications to the grasping of objects for construction and operation by mechanical hands with semi-autonomous operations in extreme environments.

It is shown how choosing the self-motion inherent in redundant arms is crucially important when flexibility is present. The self-motion, by exciting or damping the flexural modes, alters the dynamic response of the arms. Kinematic redundancy can also be used in many cases to help damp out vibrations. This issue is examined, and control algorithms designed to regulate the flexibility while maintaining precise tracking of the end-effector trajectory are introduced. The controllers are of the computed torque type in end-effector space, and use self-motion of the links to reduce the flexible effects.>

Previous implementations of robot force control seldom produced satisfactory results, and researchers in the past have experienced significant instability problems associated with their force controllers. When a manipulator is constrained to an environment (force-controlled), geometric stability due to the manipulator configuration and the force-controlled direction is shown to be a significant factor in overall system stability. This exploratory study points out a rather intuitive, geometrically based stability and analyzes the phenomenon both analytically and graphically. Sequential joint self-motion algorithms for kinematically redundant manipulators are suggested for reduced transitional impact and greater stability in the ensuing force-controlled operation.>

The problem of reducing the potentially damaging effects caused by interaction of robotic manipulators with their environment is considered. The emphasis is on reducing the magnitude of impulsive forces created at the instant of contact, the effects of which are transmitted throughout the system. A model for impact dynamics for manipulator systems is introduced and used to analyze the effects of these impulsive forces. In particular, for the case of redundant manipulators, it is shown how the redundancy can be used to configure the mechanisms so as to reduce the resulting impulsive contact forces, thus utilizing redundancy to aid in environmental interaction.>

For an object being rigidly grasped and manipulated by multiple robotic mechanisms, the internal loading characteristics at a common coordinate set within the object are considered. It is demonstrated that representation of internal forces and moments in these common coordinates give insight into force and load distribution schemes developed previously. In particular, it is shown how internal loads may be created in some end-effector force distribution schemes even when no component in the null-space of the grasp matrix is included. It is further shown that a particular pseudoinverse of the grasp matrix, which can be shown to be consistent with the kinematic constraints, may be used to eliminate this situation. The case of a two-arm system is used to illustrate the concepts introduced.>

The issue of distributing the task among the multiple robot arms while considering the manipulator dynamics is considered. The forces and moments required to move an object are distributed in such a way that extra degrees of freedom within the system may be used to satisfy or optimize criteria related to the manipulator dynamics. A method to perform such subtasks is introduced, and examples of possible criteria noted. It is expected that such techniques will produce trajectories which will be more desirable for the individual arms, dynamically, since the dynamics are considered in the task distribution.>

The problem of selecting joint space trajectories for redundant manipulators is considered. Solutions which allow secondary tasks to be performed by the arm simultaneously with end-effector motions may be selected in a number of ways. An algorithm to accomplish this, by means of conditions on a scalar function of the joint variables, is introduced and analyzed. Problems inherent in schemes involving constraints in configuration space are considered.>