Manipulation of objects within a robot's hand is one of the most important challenges in achieving robot dexterity. To address this challenge, Roller Graspers use steerable rolling fingertips. The fingertips impart motions and exert forces to achieve six degree of freedom mobility and closed-loop grasp force control. The design reported here uses image processing from cameras placed inside steerable compliant rollers to track contact conditions and locations. Integration of this data into a controller enables a variety of robust in-hand manipulation capabilities. We demonstrate that the same information can be used to reconstruct object shape. In addition, we show that by converting in-hand manipulation from a discontinuous process, with fingers frequently attaching and detaching from the object surface, to a continuous process, we can implement a convergent control loop that minimizes errors that otherwise accumulate during large object motions. The difference is apparent when comparing the results of an object rotation using a discontinuous finger-gaiting approach, as would be required without rolling fingertips, to the results obtained with continuous rolling. The results suggest that hybrid rolling fingertip and finger-gaiting approaches to manipulation may be a promising future research direction.

In this paper, we use impact-induced acceleration in conjunction with periodic stick-slip to successfully and quickly transport parts vertically against gravity. We show analytically that vertical vibratory transport is more difficult than its horizontal counterpart, and provide guidelines for achieving optimal vertical vibratory transport of a part. Namely, such a system must be capable of quickly realizing high accelerations, as well as supply normal forces at least several times that required for static equilibrium. We also show that for a given maximum acceleration, there is an optimal normal force for transport. To test our analytical guidelines, we built a vibrating surface using flexures and a voice coil actuator that can accelerate a magnetic ram into various materials to generate impacts. The surface was used to transport a part against gravity. Experimentally obtained motion tracking data confirmed the theoretical model. A series of grasping tests with a vibrating-surface equipped parallel jaw gripper confirmed the design guidelines.

Robot in-hand manipulation is an important skill for robots to carry out sophisticated tasks that require moving the grasped object within hand. In this work, we present the Roller Grasper V3, a nonanthropomorphic robot grasper with a steerable roller on each of its four fingertips, and a manipulation architecture that enables the Roller Grasper V3 to achieve full 6-DoF manipulation of the grasped object in$SE(3)$. The manipulation architecture consists of a high-level planner that searches for a feasible path with waypoints for the object to be manipulated, and a low-level control policy that is used to navigate the object in between the adjacent waypoints. The method was experimentally validated on the Roller Grasper V3 to manipulate multiple objects with different geometries and topologies.

In this paper we present a potential energy map based approach that provides a framework for the design and control of a robotic grasper. Unlike other potential energy map approaches, our framework considers friction for a more realistic perspective on grasper performance. Our analysis establishes the importance of considering dynamically variable geometry in grasper design, namely palm width, link lengths, and transmission ratios, which are assumed to be able to change in real-time. Our analysis assumes a two-phalanx tendon-pulley underactuated grasper, but it can be extended to other underactuated mechanisms. We demonstrate the utility of these novel potential energy maps and the method used to generate them in order by showing how various design parameters impact the grasping and in-hand manipulation performance of a particular design across a range of object sizes and friction coefficients. Optimal grasping designs have palms that scale with object size and transmission ratios that scale with the coefficient of friction. Using a custom in-hand manipulation metric, we compared the in-hand manipulation capabilities of a grasper that only dynamically varied its palm size, link lengths, and transmission ratios to a grasper with a variable palm and controllable actuation efforts. The analysis revealed the advantage of dynamically variable geometry; by varying only its palm size, link lengths, and transmission ratios in real-time, safe, caged in-hand manipulation of a wide range of objects could be performed.

Physical human-robot interactions (pHRI) are less efficient and communicative than human-human interactions, and a key reason is a lack of informative sense of touch in robotic systems. Interpreting human touch gestures is a nuanced, challenging task with extreme gaps between human and robot capability. Among prior works that demonstrate human touch recognition capability, differences in sensors, gesture classes, feature sets, and classification algorithms yield a conglomerate of non-transferable results and a glaring lack of a standard. To address this gap, this work presents 1) four proposed touch gesture classes that cover an important subset of the gesture characteristics identified in the literature, 2) the collection of an extensive force dataset on a common pHRI robotic arm with only its internal wrist force-torque sensor, and 3) an exhaustive performance comparison of combinations of feature sets and classification algorithms on this dataset. We demonstrate high classification accuracies among our proposed gesture definitions on a test set, emphasizing that neural network classifiers on the raw data outperform other combinations of feature sets and algorithms. Accompanying video is here.1

This paper describes the development of a novel non-anthropomorphic robot hand with the ability to manipulate objects by means of articulated, actively driven rollers located at the fingertips. An analysis is conducted and systems of equations for two-finger and three-finger manipulation of a sphere are formulated to demonstrate full six degree of freedom nonholonomic spatial motion capability. A prototype version of the hand was constructed and used to grasp and manipulate a variety of objects. Tests conducted with the prototype confirmed the validity of the mathematical analysis. Unlike conventional approaches to within-hand manipulation using legacy robotic hands, the continuous rotation capability of our rolling fingertips allows for unbounded rotation of a grasped object without the need for finger gaiting.

The ability to perform in-hand manipulation still remains an unsolved problem; having this capability would allow robots to perform sophisticated tasks requiring repositioning and reorienting of grasped objects. In this work, we present a novel non-anthropomorphic robot grasper with the ability to manipulate objects by means of active surfaces at the fingertips. Active surfaces are achieved by spherical rolling fingertips with two degrees of freedom (DoF) - a pivoting motion for surface reorientation - and a continuous rolling motion for moving the object. A further DoF is in the base of each finger, allowing the fingers to grasp objects over a range of size and shapes. Instantaneous kinematics was derived and objects were successfully manipulated both with a custom handcrafted control scheme as well as one learned through imitation learning, in simulation and experimentally on the hardware.

The sense of touch, being the earliest sensory system to develop in a human body [1], plays a critical part of our daily interaction with the environment. In order to successfully complete a task, many manipulation interactions require incorporating haptic feedback. However, manually designing a feedback mechanism can be extremely challenging. In this work, we consider manipulation tasks that need to incorporate tactile sensor feedback in order to modify a provided nominal plan. To incorporate partial observation, we present a new framework that models the task as a partially observable Markov decision process (POMDP) and learns an appropriate representation of haptic feedback which can serve as the state for a POMDP model. The model, that is parametrized by deep recurrent neural networks, utilizes variational Bayes methods to optimize the approximate posterior. Finally, we build on deep Q-learning to be able to select the optimal action in each state without access to a simulator. We test our model on a PR2 robot for multiple tasks of turning a knob until it clicks.

Virtual-reality-based surgical simulation is one of the most notable and practical applications of kinesthetic haptic rendering. With recent advances in volume visualization technology, simulators can now incorporate pre-operative medical image data for surgical planning or rehearsal. For a truly immersive, patient-specific simulation experience, versatile haptic rendering of volume data is needed. This article presents a method for haptic rendering of deformable isosurfaces embedded within volumetric data. The proxy-based algorithm operates on the original data volume, rather than on an alternate or derived representation, to preserve geometric accuracy. Real-time deformation is driven by a coarser mesh generated from the volume. We show that this approach has very favorable properties for an application in surgical simulation.

We describe our development of an autonomous robotic system that safely navigates through an unmodified campus environment to purchase and deliver a cup of coffee. To accomplish this task, the robot navigates through indoor and outdoor environments, opens heavy spring-loaded doors, calls, enters, and exits an elevator, waits in line with other customers, interacts with coffee shop employees to purchase beverages, and returns to its original location to deliver the beverages. This paper makes four contributions: a robust infrastructure for unifying multiple 2D navigation maps; a process for detecting and opening transparent, heavy spring-loaded doors; algorithms for operating elevators; and software that enables the intuitive passing of objects to and from untrained humans.

We present a constraint-based strategy for haptic rendering of arbitrary point cloud data. With the recent proliferation of low-cost range sensors, dense 3D point cloud data is readily available at high update rates. Taking a cue from the graphics literature, we propose that point data should be represented as an implicit surface, which can be formulated to be mathematically smooth and efficient for computing interaction forces, and for which haptic constraint algorithms are already well-known. This method is resistant to sensor noise, makes no assumptions about surface connectivity or orientation, and data pre-processing is fast enough for use with streaming data. We compare the performance of two different implicit representations and discuss our strategy for handling time-varying point clouds from a depth camera. Applications of haptic point cloud rendering to remote sensing, as in robot telemanipulation, are also discussed.

A method for 6-DOF haptic rendering of isosurface geometry embedded within sampled volume data is presented. The algorithm uses a quasi-static formulation of motion constrained by multiple contacts to simulate rigid-body interaction between a haptically controlled virtual tool (proxy), represented as a point-sampled surface, and volumetric isosurfaces. Unmodified volume data, such as computed tomography or magnetic resonance images, can be rendered directly with this approach, making it particularly suitable for applications in medical or surgical simulation. The algorithm was implemented and tested on a variety of volume data sets using several virtual tools with different geometry. As the constraint-based algorithm permits simulation of a massless proxy, no artificial mass or inertia were needed nor observed. The speed and transparency of the algorithm allowed motion to be responsive to extremely stiff contacts with complex virtualized geometry. Despite rendering stiffnesses that approach the physical limits of the interfaces used, the simulation remained stable through haptic interactions that typically present a challenge to other rendering methods, including wedging, prying, and hooking.

Inspired by human physiology, variable impedance actuation has been shown to benefit safety with its ability to modulate impact forces. But humans also continually adjust impedance during contact and throughout manipulation tasks. We examine the value and effect of continual impedance variation on quasi-static manipulation. We approach this challenge from the perspective of telerobotics where the operator can explicitly modulate the robotic impedance. Using a three degree of freedom planar teleoperation system we explore two quasi-static tasks: inserting a rigid peg into a tight hole and throwing a switch without overshoot. The work finds that no single impedance can optimally accomplish both tasks. Instead user-controlled impedance variations achieve the desired results, demonstrating the benefits of variable impedance to quasi-static applications in telerobotics.

We present a new mechanical design for a 3-DOF haptic device with spherical kinematics (pitch, yaw, and prismatic radial). All motors are grounded in the base to decrease inertia and increase compactness near the user's hand. An aluminum-aluminum friction differential allows for actuation of pitch and yaw with mechanical robustness while allowing a cable transmission to route through its center. This novel cabling system provides simple, compact, and high-performance actuation of the radial DOF independent of motions in pitch and yaw. We show that the device's capabilities are suitable for general haptic rendering, as well as specialized applications of spherical kinematics such as laparoscopic surgery simulation.

This paper presents a new algorithm for selecting the optimal needle insertion point in images of hand veins for robotic IV insertion. The 3D coordinates and orientation of the vein that the algorithm detects would eventually be fed to a robot for insertion of the IV needle. The goal of the algorithm is to identify venous bifurcations and determine an insertion point and approach angle for the needle in between their branches. The algorithm uses an annular tracking window that tracks along the veins and searches for bifurcations. We describe methods for centering the initial bifurcation estimates, error-checking, and positioning the needle exactly in between the bifurcation branches. We conclude with an experimental study of 50 subjects that shows a 32.4% success rate at detecting all bifurcations and a 82.6% success rate at finding at least one bifurcation in each image that contains bifurcations.

This paper proposes a new framework for fast and reliable traffic sign detection using images obtained from a single front-facing road vehicle camera. Our focus is on a methodology for reducing the computational requirements and increasing the performance of existing detection methods by refining the image space search using 3D scene geometry. Information concerning physical traffic sign dimensions and vehicle camera parameters is integrated into a model that predicts the image scales and locations at which traffic signs are likely to appear. We apply our framework to a Haar-feature-based detection method trained on a collection of stop signs. Experimental results show that the refined image search space results in much less computation time while retaining the same true positive detection performance as existing methods that search all image scales and locations. In addition, false positives at physically implausible traffic sign locations are eliminated.

Previous work has shown that high frequency content is important for realistic haptic feedback, while stability considerations limit the ability of closed-loop control to effectively generate high frequencies. Open-loop playback of high frequencies offers a promising way to generate rich contact transients and textures, but complex high frequency dynamics cause distortion. This paper explores the equalization and dynamic decoupling of multi-DOF haptic devices for accurate open-loop playback. Toward this end, a user study is performed to determine the frequency limit of human force direction sensitivity at 35Hz. This information together with experimental system identification techniques is used to develop a strategy for equalization in different frequency bands. Finally, MIMO equalization is accomplished through online simulation of the system model under the control of an LQR tracking controller.

Robotic control of flexible devices can enhance and simplify many medical procedures. We present a method for controlling a tendon-driven continuum manipulator by means of specifying the shape configuration. The basis for control is a linear beam configuration model that transforms beam configuration to tendon displacement by modeling internal loads of the compliant system. An essential aspect of this model is the inclusion of both the mechanical and geometrical coupling among serial articulating sections. Important capabilities of this model are the general forward kinematics and the decoupled inverse kinematics that allow for independent control of multiple sections. Tracking results are presented for a cardiac catheter with two articulating sections.

Rigid robotic manipulators employ traditional sensors such as encoders or potentiometers to measure joint angles and determine end-effector position. Manipulators that are flexible, however, introduce motions that are much more difficult to measure. This is especially true for continuum manipulators that articulate by means of material compliance. In this paper, we present a vision based system for quantifying the 3-D shape of a flexible manipulator in real-time. The sensor system is validated for accuracy with known point measurements and for precision by estimating a known 3-D shape. We present two applications of the validated system relating to the open-loop control of a tendon driven continuum manipulator. In the first application, we present a new continuum manipulator model and use the sensor to quantify 3-D performance. In the second application, we use the shape sensor system for model parameter estimation in the absence of tendon tension information.

Robot haptics ultimately consists of a set of models which interpret and predict a robot’s physical interaction with the world. In this paper, we describe one approach to modeling support friction within a two-dimensional environment consisting of a single robot finger pushing objects on a table. Instead of explicitly modeling the friction distribution between the object and the table, we learn the mapping between pushes and the motion of the object using an online, memory-based model using local regression. The resulting manipulation map implicitly describes the support friction without a complex model. We also describe methods of acquiring object shape and localizing the object using a proximity sensor. Results are presented for objects with different friction distributions.

The most critical challenge for Personal Robotics is to manage the issue of human safety and yet provide the physical capability to perform useful work. This paper describes a novel concept for a mobile, 2-armed, 25-degree-of- freedom system with backdrivable joints, low mechanical impedance, and a 5 kg payload per arm. System identification, design safety calculations and performance evaluation studies of the first prototype are included, as well as plans for a future development.

Human perception is based on differences. After all, nobody will ask you to hold an object and measure its weight to three significant figures and expect you to succeed. But comparing the weight of the object to another object (say, an apple) would be an easy task and an everyday occurrence. In this paper we explore support friction estimation for pushing operations. We present two difference-based techniques for measuring friction (a transition-based method and a work-based method) and test each using two different force sensors (a commercial sensor and an estimation method based on motor torque). Our results show that low-cost, noisy force sensors perform just as well as highly accurate sensors when used with our difference-based friction estimation techniques. Finally, we present an algorithm which determines if two objects have statistically similar support friction coefficients using a modified version of Student’s t-test.

Continuum robotic manipulators articulate due to their inherent compliance. Tendon actuation leads to compression of the manipulator, extension of the actuators, and is limited by the practical constraint that tendons cannot support compression. In light of these observations, we present a new linear model for transforming desired beam configuration to tendon displacements andviceversa. We begin from first principles in solid mechanics by analyzing the effects of geometrically nonlinear tendon loads. These loads act both distally at the termination point and proximally along the conduit contact interface. The resulting model simplifies to a linear system including only the bending and axial modes of the manipulator as well as the actuator compliance. The model is then manipulated to form a concise mapping from beam configuration-space parameters tonredundant tendon displacements via the internal loads and strains experienced by the system. We demonstrate the utility of this model by implementing an optimal feasible controller. The controller regulates axial strain to a constant value while guaranteeing positive tendon forces and minimizing their magnitudes over a range of articulations. The mechanics-based model from this study provides insight as well as performance gains for this increasingly ubiquitous class of manipulators.

Traditional image mosaicing usually relies on rigid image transformations. In many medical applications, however, tissue deformation during image acquisition or 3D parallax effects may require nonrigid transformations in the mosaicing process. This paper presents a new method that integrates deformable surface models into the image mosaicing algorithms. Our approach has two main contributions. First, we present a global alignment algorithm to efficiently deal with accumulated image registration errors. Second, we introduce a local alignment algorithm to accommodate local scene deformations. These two problems are integrated into a single optimization problem that simultaneously recovers the motion of the camera as well as the structure of the scene. Our approach is demonstrated on simulations, images from a hand-held digital camera, and microscopic images acquired with a micro-endoscope.

This paper presents the design of an optical fiber proximity sensor for haptic exploration with a robotic finger. The sensor uses emitter and receiver optical fiber pairs to measure the intensity of light reflected off surrounding objects in a 2-D workspace. We present the design and construction a 32-point sensor array mounted within a 36 mm diameter finger and describe software techniques to process data acquired by an inexpensive web-cam. We experimentally characterize the sensor performance and demonstrate applications for haptic exploration such as pre-contact velocity reduction and non-contact contour following based on object curvature.

Despite a wealth of literature on discrimination thresholds for displacement, force magnitude, stiffness, and viscosity, there is currently a lack of data on our ability to discriminate force directions. Such data are needed in designing haptic rendering algorithms where force direction, as well as force magnitude, are used to encode information such as surface topography. Given that haptic information is typically presented in addition to visual information in a data perceptualization system, it is also important to investigate the extent to which the congruency of visual information affects force-direction discrimination. In this article, the authors report an experiment on the discrimination threshold of force directions under the three display conditions of haptics alone (H), haptics plus congruent vision (HVcong), and haptics plus incongruent vision (HVincong). Average force-direction discrimination thresholds were found to be 18.4°, 25.6°, and 31.9° for the HVcong, H and HVincong conditions, respectively. The results show that the congruency of visual information significantly affected haptic discrimination of force directions, and that the force-direction discrimination thresholds did not seem to depend on the reference force direction. The implications of the results for designing haptic virtual environments, especially when the numbers of sensors and actuators in a haptic display do not match, are discussed.

Rendering stiff virtual objects remains a core challenge in the field of haptics. A study of this problem is presented, which relates the maximum achievable object stiffness to the elements of the control loop. In particular, we examine how the sampling rate, quantization, computational delay, and amplifier dynamics interact with the inertia, natural viscous, and Coulomb damping of the haptic device. Nonlinear effects create distinct stability regions, and many common devices operate stably, yet in violation of passivity criteria. An energy-based approach provides theoretical insights, supported by simulations, experimental data, and a describing function analysis. The presented results subsume previously known stability conditions

Rendering a stiff virtual wall remains a core challenge in the field of haptics. A passivity study of this problem is presented, which relates the maximum achievable wall stiffness to the system discretization and sampling delays, to the quantization of the encoder, to the inertia of the haptic device, as well as to both the natural viscous and Coulomb damping present in the haptic device. The resulting stability criterion generalizes previously known results. Its analytic derivation is verified in both simulation and experiments on a one degree of freedom testbed.

This paper presents a series of kinematic and haptic analysis, which lead to the design of a particularly simple, yet useful multi-hand multi-finger haptic interface. We also discuss rendering issues, which must be addressed in utilizing it, including and extension of the proxy to more general contact.

In this paper we develop an interactive 3D browser for large topographic maps using a visual display augmented by a haptic, or force feedback, display. The extreme size of our data files (over 100 million triangles) requires us to develop the "proxy graph algorithm", a new haptic contact model. The proxy graph algorithm approximates proven virtual proxy methods but enhances the performance significantly by restricting the proxy location to the edges and vertices of the object. The resulting algorithm requires less computation and reduces the average number of collision detection operations per triangle that the proxy crosses during each haptic update cycle. We also develop a collision detection algorithm optimized for our heightfield dataset.Our "MarsView" software enables hands-on interactive display of visual and geologic data with polygon counts in excess of 100 million triangles using a standard PC computer and a commercial haptic interface. MarsView's haptic user interface allows the user to physically interact with the surface as they pan it around and zoom in on details. The hybrid system renders complex scenes at full visual and haptic rates resulting in a more immersive user experience than a visual display alone.

The paper briefly describes daVinci/sup TM/, a surgical telerobot designed to provide enhanced dexterity to doctors performing minimally invasive surgical procedures. The rationale for a full 7-degree-of-freedom master-slave system is presented along with a discussion of the resulting computational architecture and recent clinical applications.

This paper presents the Black Falcon, an eight degree-of-freedom teleoperator slave with a dextrous wrist for minimally invasive surgery (MIS). We show how teleoperation can address several key problems in MIS by increasing dexterity and degrees of freedom, by giving the surgeon some force feedback to feel instrument-tissue interactions and by eliminating geometric discrepancies between actual and observed tool motions. We discuss relevant design constraints, summarize the mechanism design and give data showing the quality of force reflection achieved. We demonstrate suturing along arbitrarily oriented suture lines in animal tissue, a task essentially impossible using current instruments.

In this paper, a closed-form formulation for inverse kinematics for redundant manipulators with inequality constraints has been proposed. This formulation has been derived by using the Kuhn-Tucker condition, the Lagrange multiplier method, and the active/working set method, so that its solution may satisfy the necessary and sufficient condition for optimization subject to equality and inequality constraints. From the formulation, computationally efficient kinematic control methods have been derived using differential kinematics and gradient projection method. The effectiveness of the proposed methods has been demonstrated with a 4-DOF planar manipulator, and then a 7-DOF spatial manipulator as a practical application to a nozzle dam task of a nuclear power plant.

Current force control capabilities are limited by actuator performance. Brush friction and actuator saturation lead to limit cycles and instability in many force control systems. The authors propose that actuators with the proper passive characteristics provide the best potential for fast, accurate force control. The authors report on a new actuator concept which combines two actuators to create a micro-macro actuator which has improved force resolution and bandwidth. Unlike previous micro-macro robots which used actuators coupled in series, the actuators in this system are coupled in parallel using a compliant transmission. Three specifications for force control performance are defined and a model is presented. A control law for the combined actuator is presented and a general analysis of the design is formulated. Finally, measurements of performance in a prototype device are presented. This system has achieved force resolution of 0.25% and force control bandwidth of 60 Hz.

Haptic display is the process of applying forces to a human "observer" giving the sensation of touching and interacting with real physical objects. Touch is unique among the senses because it allows simultaneous exploration and manipulation of an environment. A haptic display system has three main components. The first is the haptic interface, or display device, generally some type of electro-mechanical system able to exert controllable forces on the user with one or more degrees of freedom. The second is the object model-a mathematical representation of the object containing its shape and other properties related to the way it feels. The third component, the haptic rendering algorithm, joins the first two components to compute, in real time, the model-based forces to give the user the sensation of touching the simulated objects. This paper focuses on a new haptic rendering algorithm for generating convincing interaction forces for objects modeled as rigid polyhedra. We create a virtual model of the haptic interface, called the god-object, which conforms to the virtual environment. The haptic interface can then be servo-ed to this virtual model. This algorithm is extensible to other functional descriptions and lays the groundwork for displaying not only shape information, but surface properties such as friction and compliance.

Haptic rendering is the process of computing and generating forces in response to user interactions with virtual objects. Recent efforts by our team at MIT's AI laboratory have resulted in the development of haptic interface devices and algorithms for generating the forces of interaction with virtual objects. This paper focuses on the software techniques needed to generate sensations of contact interaction and material properties. In particular, the techniques we describe are appropriate for use with the Phantom haptic interface, a force generating display device developed in our laboratory. We also briefly describe a technique for representing and rendering the feel of arbitrary polyhedral shapes and address issues related to rendering the feel of non-homogeneous materials. A number of demonstrations of simple haptic tasks which combine our rendering techniques are also described.

The authors discuss the application of intrinsic tactile sensing (ITS) to grasp and manipulation control. A brief description of ITS, i.e., contact sensing based on force/torque measurements at fingertips, is provided. A method for using sensory feedback in the control of grasp forces to augment grasp robustness against slippage is discussed with respect to a simple grasp type; simulation and experimental data are provided. The possible generalization of this sensor-driven approach to the control of optimal grasp force in complex grasp configurations is addressed.>

The mechanical bandwidth of a manipulator ultimately limits its closed-loop bandwidth and so its response in both trajectory and force control. Here, mechanical design strategies are introduced to improve performance, including placing a distinct speed reducer at the joint rather than at the motor shaft, limiting the transmission ratio and properly selecting the contact compliance. The authors define simple models of the transmission for position-in-position-out and force-out and examine the corresponding transfer functions. The bandwidth of each of the simple models (which neglect damping) is approximately equal to the frequency of the first break point in the magnitude of the frequency response which, in turn, is equal to its lowest resonant frequency. The aim is for the open-loop bandwidth to be as high as possible to increase the quickness of the manipulator's response to commands.>

An approach to manipulation that uses all the available manipulation surfaces of the robot to act on and sense the environment is outlined. The kinematic, mechanism, actuation, and control implications of such a design are discussed and initial experimentation with a prototype mechanism are described. A three-degree-of-freedom underwater manipulator using a number of the resulting design concepts is described.>

We have studied the effect of Coulomb friction and stiction on force control with integral feedback. The force is applied through a compliant transmission by a velocity-controlled motor. Our results show that stiction can cause the applied force to enter a limit cycle. Coulomb friction can extend the system stability bounds but may lead to an input-dependent stability. Under certain conditions Coulomb friction causes an actuator limit cycle even though the applied force approaches the desired steady state force. Based on the analysis, we give design guidelines for increasing the performance.

In this paper we will discuss some of the mechanical attributes of teleoperator systems and the ways in which their dexterity may be increased by the addition of articulated end effectors. We present a number of the design issues from a mechanism and control point of view, including kinematic properties, friction and transfer functions.

Redundant manipulators are expected to increase robot performance by reducing the problem of workspace singularities, allowing for obstacle avoidance and providing the opportunity for gross motion optimization. We show that the addition of redundant joints can also increase the dynamic response for small motions of the manipulator at its endpoint. We begin by considering a two link mechanism, which is the simplest redundant system for effecting motion in a single direction. It is shown that the addition of a second link reduces the power required for sinusoidal motion at the mechanism endpoint. A method of choosing the relative link dimensions is then presented. Given a particular choice of link lengths, we show how to allocate motion between the joints to minimize the power required for a specified amplitude of motion. Finally, a strategy is proposed for local control of this redundant system which uses a quick acting mode to respond to disturbances and high bandwidth commands, and a slow acting mode to return the mechanism to a nominal configuration. The implications for control of redundant manipulator systems (i.e. hand and arm systems) are discussed.

As manipulation practice moves toward greater dexterity through the use of more complex end effectors it becomes necessary to sense more details of the interactions between the manipulator and grasped object. Accurate modeling of grasp kinematics is necessary for high quality control of the force and motion states of the grasped object. To do this one must ascertain the location, orientation and type of contact that occurs between fingers and objects. We present an approach for determining geometric features of certain basic types of contact. The characteristics of forces and moments transmitted through point, line and surface contacts are considered and used to determine the number and placement of sensing elements. Several sensor designs are given that use a minimal number of strain gauge measurements to locate the position and orientation of point and line contacts.