Tactile sensing is essential for dexterous manipulation, yet large-scale human demonstration datasets lack tactile feedback, limiting their effectiveness in skill transfer to robots. To address this, we introduce TacCap, a wearable Fiber Bragg Grating (FBG)-based tactile sensor designed for seamless human-to-robot transfer. TacCap is lightweight, durable, and immune to electromagnetic interference, making it ideal for real-world data collection. We detail its design and fabrication, evaluate its sensitivity, repeatability, and cross-sensor consistency, and assess its effectiveness through grasp stability prediction and ablation studies. Our results demonstrate that TacCap enables transferable tactile data collection, bridging the gap between human demonstrations and robotic execution, with broad implications for fine-motor disciplines such as surgical training and musical performance. To support further research and development, we open-source our hardware design and software.

Vision-based tactile sensors have recently become popular due to their combination of low cost, very high spatial resolution, and ease of integration using widely available miniature cameras. The associated field of view and focal length, however, are difficult to package in a human-sized finger. In this article we employ optical fiber bundles to achieve a form factor that, at 15 mm diameter, is smaller than an average human fingertip. The electronics and camera are also located remotely, further reducing package size. The sensor achieves a spatial resolution of 0.22 mm and a minimum force resolution 5 mN for normal and shear contact forces. With these attributes, the DIGIT Pinki sensor is suitable for applications such as robotic and teleoperated digital palpation. We demonstrate its utility for palpation of the prostate gland and show that it can achieve clinically relevant discrimination of prostate stiffness for phantom andex vivotissue.

Skin deformation haptic devices worn on the finger pad provide realistic touch feedback during interactions with virtual objects. Two primary challenges in creating such devices are: first, making a multidegree-of-freedom device (DoF) that is small and lightweight so it does not encumber the wearer and second, providing accurate control of forces displayed to the finger pad. This work presents a 4-DoF finger pad haptic device, called Fourigami, that addresses these challenges. We address the first challenge using origami manufacturing methods and pneumatic actuation to fabricate a 25 g prototype that displays normal, shear, and twist and can be easily worn on the finger pad. We address the second challenge using a low-profile, 6-DoF, force/torque sensor to control forces displayed to the finger. Fourigami has a bandwidth ranging from 2 to 4 Hz depending on direction, and when acting on a human finger, it exerts forces ranging from$\pm$1.0 N in shear, 4.2 N in normal, and$\pm$4.2 N$\cdot$mm of twist. Finally, we demonstrate the device’s efficacy when rendering haptic feedback to a user tracking a sinusoidal trajectory and a trajectory representing interactions with a virtual object.

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.

It is difficult for robots to retrieve objects in densely cluttered lateral access scenes with movable objects as jamming against adjacent objects and walls can inhibit progress. We propose the use of two action primitives— burrowing and excavating—that can fluidize the scene to unjam obstacles and enable continued progress. Even when these primitives are implemented in an open loop manner at clockdriven intervals, we observe a decrease in the final distance to the target location. Furthermore, we combine the primitives into a closed loop hybrid control strategy using tactile and proprioceptive information to leverage the advantages of both primitives without being overly disruptive. In doing so, we achieve a 10-fold increase in success rate above the baseline control strategy and significantly improve completion times as compared to the primitives alone or a naive combination of them.

ReachBot, a proposed robotic platform, employs extendable booms as limbs for mobility in challenging environments, such as martian caves. When attached to the environment, ReachBot acts as a parallel robot, with reconfiguration driven by the ability to detach and re-place the booms. This ability enables manipulation-focused scientific objectives: for instance, through operating tools, or handling and transporting samples. To achieve these capabilities, we develop a two-part solution, optimizing for robustness against task uncertainty and stochastic failure modes. First, we present a mixed-integer stance planner to determine the positioning of ReachBot’s booms to maximize the task wrench space about the nominal point(s). Second, we present a convex tension planner to determine boom tensions for the desired task wrenches, accounting for the probabilistic nature of microspine grasping. We demonstrate improvements in key robustness metrics from the field of dexterous manipulation, and show a large increase in the volume of the manipulation workspace. Finally, we employ Monte-Carlo simulation to validate the robustness of these methods, demonstrating good performance across a range of randomized tasks and environments, and generalization to cable-driven morphologies. We make our code available at our project webpage, https://stanfordasl.github.io/reachbot_manipulation/

This paper explores a novel task "Dexterous Grasp as You Say'' (DexGYS), enabling robots to perform dexterous grasping based on human commands expressed in natural language. However, the development of this field is hindered by the lack of datasets with natural human guidance; thus, we propose a language-guided dexterous grasp dataset, named DexGYSNet, offering high-quality dexterous grasp annotations along with flexible and fine-grained human language guidance. Our dataset construction is cost-efficient, with the carefully-design hand-object interaction retargeting strategy, and the LLM-assisted language guidance annotation system. Equipped with this dataset, we introduce the DexGYSGrasp framework for generating dexterous grasps based on human language instructions, with the capability of producing grasps that are intent-aligned, high quality and diversity. To achieve this capability, our framework decomposes the complex learning process into two manageable progressive objectives and introduce two components to realize them. The first component learns the grasp distribution focusing on intention alignment and generation diversity. And the second component refines the grasp quality while maintaining intention consistency. Extensive experiments are conducted on DexGYSNet and real world environments for validation.

ReachBot is a robot that uses extendable and retractable booms as limbs to move around unpredictable environments such as martian caves. Each boom is capped by a microspine gripper designed for grasping rocky surfaces. Motion planning for ReachBot must be versatile to accommo-date variable terrain features and robust to mitigate risks from the stochastic nature of grasping with spines. In this paper, we introduce a graph traversal algorithm to select a discrete sequence of grasps based on available terrain features suitable for grasping. This discrete plan is complemented by a decoupled motion planner that considers the alternating phases of body movement and end-effector movement, using a combination of sampling-based planning and sequential convex programming to optimize individual phases. We use our motion planner to plan a trajectory across a simulated 2D cave environment with at least 90% probability of success and demonstrate improved robustness over a baseline trajectory. Finally, we use a simplified prototype to verify a body movement trajectory generated by our motion planning algorithm.

ReachBot is a new concept for planetary exploration, consisting of a small body and long, lightweight extending arms loaded primarily in tension. The arms are equipped with spined grippers for anchoring on rock surfaces. The design and testing of a planar prototype is presented here. Experiments with rock grasping and coordinated locomotion illustrate the advantages of low inertia passive grippers, triggered by impact and using stored mechanical energy for the internal force. Gripper design involves a trade-off among the range of possible grasp angles, maximum grasp force, required triggering force, and required reset force. The current prototype can pull with up to 8N when gripping volcanic rock, limited only by the strength of the 3D printed components. Calculations predict a maximum pull of 26N for the same spines and stronger materials.

When humans socially interact with another agent (e.g., human, pet, or robot) through touch, they do so by applying varying amounts of force with different directions, locations, contact areas, and durations. While previous work on touch gesture recognition has focused on the spatio-temporal distribution of normal forces, we hypothesize that the addition of shear forces will permit more reliable classification. We present a soft, flexible skin with an array of tri-axial tactile sensors for the arm of a person or robot. We use it to collect data on 13 touch gesture classes through user studies and train a Convolutional Neural Network (CNN) to learn spatio-temporal features from the recorded data. The network achieved a recognition accuracy of 74% with normal and shear data, compared to 66% using only normal force data. Adding distributed shear data improved classification accuracy for 11 out of 13 touch gesture classes.

Perceiving the environment through touch is important for robots to reach in cluttered environments, but devising a way to sense without disturbing objects is challenging. This work presents the design and modelling of whisker-inspired sensors that attach to the surface of a robot manipulator to sense its surrounding through light contacts. We obtain a sensor model using a calibration process that applies to straight and curved whiskers. We then propose a sensing algorithm using Bayesian filtering to localize contact points. The algorithm combines the accurate proprioceptive sensing of the robot and sensor readings from the deflections of the whiskers. Our results show that our algorithm is able to track contact points with sub-millimeter accuracy, outperforming a baseline method. Finally, we demonstrate our sensor and perception method in a real-world system where a robot moves in between free-standing objects and uses the whisker sensors to track contacts tracing object contours.

Robotic manipulators navigating cluttered shelves or cabinets may find it challenging to avoid contact with obstacles. Indeed, rearranging obstacles may be necessary to access a target. Rather than planning explicit motions that place obstacles into a desired pose, we suggest allowing incidental contacts to rearrange obstacles while monitoring contacts for safety. Bypassing object identification, we present a method for categorizing object motions from tactile data collected from incidental contacts with a capacitive tactile skin on an Allegro Hand. We formalize tactile cues associated with categories of object motion, demonstrating that they can determine with > 90% accuracy whether an object is movable and whether a contact is causing the object to slide stably (safe contact) or tip (unsafe).

Tactile sensing can improve end-effector control and grasp quality, especially for free-flying robots where target approach and alignment present particular challenges. However, many current tactile sensing technologies are not suitable for the harsh environment of space. We present a tactile sensor that measures normal and biaxial shear strains in the pads of a gripper using a single optical fiber with Bragg grating (FBG) sensors. Compared to conventional wired solutions, the encapsulated optical fibers are immune to electromagnetic interference — critical in the harsh environment of space. Sampling is possible at over 1 kHz to detect dynamic events. We mount sensor pads on a custom two-fingered gripper with independent control of the distal and proximal phalanges, allowing for grip readjustment based on sensing data. Calibrated sensor data for forces match those from a commercial multiaxial load cell with an average 96.2% RMS for all taxels. We demonstrate the gripper on tasks motivated by the Astrobee free-flying robots in the International Space Station (ISS): gripping corners, detecting misaligned grasps, and improving load sharing over the contact areas in pinch grasps.

For small legged robots, ground contact interactions significantly affect the dynamics and locomotion performance. In this article, we designed thin, robust capacitive tactile sensors and applied them to the feet of a small hexapod with C-shaped rotating legs. The sensors measure contact forces as the robot traverses different types of terrain including hard surfaces with high or low friction, sand, and grass. Different gaits perform best on different types of terrain. Useful measured parameters include the magnitude and timing of the peak normal forces, in combination with the leg rotational velocity. The measured parameters were used in a support vector machine classifier to identify terrain types with 82.5% accuracy. Based on gait performance studies, we implemented a terrain-based gait control using real-time terrain classifications. A surface transitioning test shows 17.1% increase in body speed and 13.2% improvement in efficiency as the robot adjusts its gait.

Gentle suction flow at the fingertips of a compliant hand can enhance object acquisition and increase the robustness of pinch grasps under water. The approach adds a low-pressure pump and flexible tubes that terminate at the distal phalanges. The light flow rate does not create a powerful suction force, nor does it stir up significant sediment. The method works on porous and rough objects in addition to smooth objects as it does not require forming a seal. It changes contact conditions - normal force and coefficient of friction - and enlarges the acquisition region when grasping free objects under water. A simple hydrodynamic model matches empirical force measurements adequately for incorporation in a dynamic simulation to explore the effects of flow rate and object mass. Simulations and experiments show that effects of fingertip suction flow are most pronounced for acquiring objects on the order of 1 kg or less and when pinching large objects. Gentle suction flow is an effective, versatile, and convenient addition for robots that must grasp and manipulate objects under water.

This paper presents a method for efficiently testing the stability of an object under contact that accommodates empirical models of admissible forces at individual contact points. It handles a diverse range of possible geometries of the admissible force volume, including anisotropy, adhesion, and even nonconvexity. The method discretizes the contact region into patches, performs a convex decomposition of a polyhedral approximation to each admissible force volume, and then formulates the problem as a mixed integer linear program. The model can also accommodate articulated robot hands with torque limits and joint frictions. Predictions of our method are evaluated experimentally in object lifting tasks using a gripper that exploits microspines to exert strongly anisotropic forces. The method is applied to calculate gripper loading capabilities and equilibrium predictions for a quadruped climbing robot on steep and overhanging terrain.

Grasping objects that are too large to envelop is traditionally achieved using friction that is activated by squeezing. We present a family of shear-activated grippers that can grasp such objects without the need to squeeze. When a shear force is applied to the gecko-inspired material in our grippers, adhesion is turned on; this adhesion in turn results in adhesion-controlled friction, a friction force that depends on adhesion rather than a squeezing normal force. Removal of the shear force eliminates adhesion, allowing easy release of an object. A compliant shear-activated gripper without active sensing and control can use the same light touch to lift objects that are soft, brittle, fragile, light, or very heavy. We present three grippers, the first two designed for curved objects, and the third for nearly any shape. Simple models describe the grasping process, and empirical results verify the models. The grippers are demonstrated on objects with a variety of shapes, materials, sizes, and weights.

Magnetic resonance imaging (MRI) offers many benefits, including unsurpassed soft-tissue characterization and the ability to combine detection and biopsy into a single procedure. However, limited patient access in the narrow scanner bore requires tedious iterative positioning or use of robotic assistants that isolate the physician from the patient. As an alternative, we present a teleoperation technology for percutaneous procedures to meet the needs of interventional radiologists and overcome challenges imposed by the MR environment. The technology is demonstrated for a 1-DOF needle insertion procedure. The technology uses rolling diaphragms, a clutch, and a cable-capstan drive to propel the needle while relaying forces and motions to the operator. The system demonstrates excellent position tracking (< 0.7° error in the unloaded case) and reliably transmits changes in force. During needle teleoperation, users were able to detect light membrane punctures and differentiate spring stiffnesses nearly as accurately as by hand manipulation.

Free-flying robots have the potential to autonomously fulfill a wide range of tasks involving manipulation of objects in space. In this paper we study the design of a wrist mechanism for free-flying robots that are equipped with an adhesive gripper for attaching to objects and surfaces. The wrist and gripper allow the robots to apply moments in addition to forces, which increases their versatility for object manipulation. We apply grasp optimization to establish limitations on the forces/moments that the wrist can impart, subject to adhesion capabilities. Building on these results, we present considerations for tuning a passive wrist mechanism, or controlling an active wrist, to broaden the range of forces and moments that the robot can exert. Our theoretical insights and wrist designs are validated in simulations and on a planar micro-gravity test bed.

Grasping and manipulation of biological tissue are crucial processes during minimally invasive surgery (MIS). To enable atraumatic and reliable grasping, it would be useful to detect slip of the grasped object. Because tissue is moist, conformable, and delicate, and because the sensor must work in a surgical environment, this application requires a departure from conventional slip sensing methods. We present a technology and method based on hot-wire anemometry to detect slip while grasping wet, conformable materials and discuss how this approach may be extended to graspers used in robot-assisted surgery (RAS). We present our design and the results from characterization tests as well as experimental results that demonstrate its ability to detect planar direction of slip of wet, compliant objects.

Perching can extend the useful mission life of a micro air vehicle. Once perched, climbing allows it to reposition precisely, with low power draw and without regard for weather conditions. We present the Stanford Climbing and Aerial Maneuvering Platform, which is to our knowledge the first robot capable of flying, perching with passive technology on outdoor surfaces, climbing, and taking off again. We present the mechanical design and the new perching, climbing, and takeoff strategies that allow us to perform these tasks on surfaces such as concrete and stucco, without the aid of a motion capture system or off-board computation. We further discuss two new capabilities uniquely available to a hybrid aerial-scansorial robot: the ability to recover gracefully from climbing failures and the ability to increase usable foothold density through the application of aerodynamic forces. We also measure real power consumption for climbing, flying, and monitoring and discuss how future platforms could be improved for longer mission life.

We explore the use of grippers with gecko-inspired adhesives for spacecraft docking and acquisition of tumbling objects in microgravity. Towards the goal of autonomous object manipulation in space, adhesive grippers mounted on planar free-floating platforms are shown to be tolerant of a broad range of incoming linear and angular velocities. Through modeling, simulations, and experiments, we characterize the dynamic “grasping envelope” for successful acquisition and derive insights to inform future gripper designs and grasping strategies for motion planning.

Lateral skin stretch is a promising technology for haptic display of information between an autonomous or semi-autonomous car and a driver. We present the design of a steering wheel with an embedded lateral skin stretch display and report on the results of tests (N=10) conducted in a driving vehicle in suburban traffic. Results are generally consistent with previous results utilizing skin stretch in stationary applications, but a slightly higher, and particularly a faster rate of stretch application is preferred for accurate detection of direction and approximate magnitude.

We present a new palm design that features a dense array of micro-spines for the JPL Robosimian human-scale climbing robot. A linearly-constrained spine mechanism is introduced and analyzed using adhesion and stiffness models. This mechanism achieves a spine density of 19/cm2and a mean adhesion of 67N (207kPa) on coarse concrete surfaces. The models are validated on two different surfaces with two sets of experiments. A 120×100mm palm consisting of 12 spine tiles and a pulley differential system for load sharing are designed and tested on 9 different surfaces. The mean shear adhesion goes up to 710N (183kPa) on concrete blocks. Design considerations include scaling efficiency and maximal single-spine force. Desirable properties for load sharing in the palm design are discussed.

The controllable adhesives used by insects to both carry large loads and move quickly despite their small scale inspires the μTug robot concept. These are small robots that can both move quickly and use controllable adhesion to apply interaction forces many times their body weight. The adhesives enable these autonomous robots to accomplish this feat on a variety of common surfaces without complex infrastructure. The benefits, requirements, and theoretical efficiency of the adhesive in this application are discussed as well as the practical choices of actuator and robot working surface material selection. A robot actuated by piezoelectric bimorphs demonstrates fast walking with a no-load rate of 50 Hz and a loaded rate of 10 Hz. A 12 g shape memory alloy (SMA) actuated robot demonstrates the ability to load more of the adhesive enabling it to tow 6.5 kg on glass (or 500 times its body weight). Continuous rotation actuators (electromagnetic in this case) are demonstrated on another 12 g robot give it nearly unlimited work cycles through gearing. This leads to advantages in towing capacity (up to 22 kg or over 1800 times its body weight), step size, and efficiency. This work shows that using such an adhesive system enables small robots to provide truly human scale interaction forces, despite their size and mass. This will enable future microrobots to not only sense the state of the human environment in which they operate, but apply large enough forces to modify it in response.

The ability to carry large payloads could greatly increase the applications of small, low cost climbing robots. We present a linear inchworm gait that uses a single powerful actuator to climb. To make this gait possible, we leveraged two new methods of achieving controllable, anisotropic adhesion (one method produces over 200 times stronger adhesion in the preferred direction). With controllable, anisotropic adhesion, the gait is robust to missed steps. In addition, the gait provides a stance in which the robot can rest without requiring power. An autonomous 9 gram robot is able to climb a smooth vertical surface at 3 mm/s, while hoisting more than a kilogram. We also present a scaled down version of the robot, which is considerably smaller than any previous dry adhesive climbing mechanism. It is actuated by externally powered Shape Memory Alloy, weighs 20 mg, and is capable of hoisting 500 mg. These climbers show that a large hoisting ability while climbing can be achieved using dry adhesives, and the presented concepts could aid in the development of autonomous, highly functional, small robots.

Nearly all robotic grippers have one trait in common: they grasp objects with normal forces, either directly, or indirectly through friction. This method of grasping is effective for objects small enough for a given gripper to partially encompass. However, to grasp larger objects, significant grip forces and a high coefficient of friction are required. We present a new grasping method for convex objects, using almost exclusively shear forces. We achieve shear grasping with a gripper that utilizes thin film gecko-inspired fibrillar adhesives that conform to the curvature of the object. We present a verified model for grasping a range of curvatures and results that demonstrate the thin film fibrillar adhesives' increased contact area on textured surfaces when loaded in shear. Finally, the gripper is implemented on a robotic arm and grasps a variety of convex objects (at rest and ballistic).

As the number of rocket bodies and other debris in Earth's orbit increases, the need to capture and remove this space junk becomes essential to protect new satellites. A low cost solution may include gecko-inspired directional adhesives, which require almost no compressive preload to generate adhesion and are therefore suitable for surface grasping in space where objects are free floating. Current individual adhesive units with a pair of opposed pads achieve a limit of 13N normal to the surface. Instead of using a single large unit to generate high levels of adhesion, using multiple small gripper units is desirable to prevent single-point failures and to conform to higher curvatures. For this strategy to succeed, it is essential to distribute the overall force evenly, to minimize the overall preload normal to the surface, and to prevent local failures from propagating over the array. We present two load sharing mechanisms. The first uses nearly-constant force springs in parallel. The second uses a tendon and pulleys in series. Both allow a 4-unit gripper to maintain the same adhesive stress as a single unit. A normal adhesive load to compressive preload ratio of 100:1 is demonstrated. Zero gravity experiments and air bearing floor experiments demonstrate the gripper's functionality in a simulated space environment. Design considerations are discussed for further scaling, with the trade-offs among load sharing, suitability for different surfaces, and failure sensitivity.

Perching on a vertical surface carries the risk of severe damage to the vehicle if the maneuver fails, especially if failure goes undetected. We present a detection method using an onboard 3-axis accelerometer to discriminate between perching success and failure. An analytical model was developed to calculate acceleration differences for success and failure and set decision times. Two distinct decision times were shown to be effective, corresponding to properly engaging the gripper and overloading the gripper's capabilities. According to a machine learning feature selection algorithm, the maximum Z axis acceleration of the quadrotor and the presence of near-zero readings are the most relevant features within these two time frames. Using these features, the detection algorithm discriminated between success and failure with a 91% accuracy at 40 ms, and 94% at 80 ms. Real-time detection and failure recovery experiments with a 20 g quadrotor verify the detection method. An improved approach that combines various decision times correctly identified success/failure for all 20 trials with an average total falling distance of 0.8m during recovery. We discuss the feasibility of extending our method to other quadrotor platforms.

Pinching is an important capability for mobile robots handling small items or tools. Successful pinching requires force-closure and, in underwater applications, gentle suction flow at the fingertips can dramatically improve the handling of light objects by counteracting the negative effects of water lubrication and enhancing friction. In addition, monitoring the flow gives a measure of suction-engagement and can act as a binary tactile sensor. Although a suction system adds complexity, elastic tubes can double as passive spring elements for desired finger kinematics.

We present a light, actuated smart staff with 5DOF tip force sensing which can be used by a humanoid robot operating in challenging terrain. The staff has an extension mechanism that employs mechanical multiplexing to achieve a high extension ratio in a stiff and compact package. The tip force sensor uses two metal diaphragms to achieve decoupling of axial and radial forces and the ability to tune the maximum range of forces in each direction independently. With the force sensor, the robot can characterize the coefficient of friction and orientation of a surface with simple motion primitives. Two sets of experiments were conducted with the smart staff manipulated by a 7 DOF robot arm. Using the sensor, the robot was able to determine the orientations of sloped surfaces within two degrees in two orthogonal directions.

Adhesion quality sensing is critical to the performance of any robot that utilizes gecko-inspired dry adhesives for climbing, perching, or grasping. We present a 3-axis tactile sensor designed for this application that demonstrates performance on par with a large commercial load cell while being compact enough to integrate into a robot foot. The sensor can measure spatially distributed force loads and demonstrates high sensitivity in both shear and normal components. Results showcase the sensor's ability to detect a variety of unreliable contact and loading conditions before the onset of adhesion failure.

An active needle is proposed for the development of magnetic resonance imaging (MRI)-guided percutaneous procedures. The needle uses a low-transition-temperature shape memory alloy (LT SMA) wire actuator to produce bending in the distal section of the needle. Actuation is achieved with internal optical heating using laser light transported via optical fibers and side coupled to the LT SMA. A prototype, with a size equivalent to a standard 16-gauge biopsy needle, exhibits significant bending, with a tip deflection of more than 14° in air and 5° in hard tissue. A single-ended optical sensor with a gold-coated tip is developed to measure the curvature independently of temperature. The experimental results in tissue phantoms show that human tissue causes fast heat dissipation from the wire actuator; however, the active needle can compensate for typical targeting errors during prostate biopsy.

We present a robot capable of both (1) dynamically perching onto smooth, flat surfaces from a ballistic trajectory and (2) successfully transitioning to a climbing gait. Merging these two modes of movement is achieved via a mechanism utilizing an opposed grip with directional adhesives. Critical design considerations include (a) climbing mechanism weight constraints, (b) suitable body geometry for climbing and (c) effects of impact dynamics. The robot uses a symmetric linkage and cam mechanism to load and detach the feet while climbing. The lengths of key parameters, including the distances between each the feet and the tail, are chosen based on the ratio of required preload force and detachment force for the adhesive mechanism.

Perching allows Micro Aerial Vehicles (MAVs) avoid the power costs and electrical and acoustic noise of sustained flight, for long-term surveillance and reconnaissance applications. This paper presents a dynamic model that clarifies the requirements for repeatable perching on walls and ceilings using an opposed-grip mechanism and dry adhesive technology. The model predicts success for perching over a range of initial conditions. The model also predicts the conditions under which other directional attachment technologies, such as microspines, will succeed. Experiments conducted using a launching mechanism for a range of different landing conditions confirm the predictions of the model and provide insight into future design improvements that are possible by modifying a few key damping and stiffness parameters.

Fingertip suction is investigated using a compliant, underactuated, tendon-driven hand designed for underwater mobile manipulation. Tendon routing and joint stiffnesses are designed to provide ease of closure while maintaining finger rigidity, allowing the hand to pinch small objects, as well as secure large objects, without diminishing strength. While the hand is designed to grasp a range of objects, the addition of light suction flow to the fingertips is especially effective for small, low-friction (slippery) objects. Numerical simulations confirm that changing suction parameters can increase the object acquisition region, providing guidelines for future versions of the hand.

Telerobotics has the potential to facilitate the repair of satellites in geosynchronous orbit by allowing human operators to interact naturally with remote objects. Time delays on the order of seconds make it difficult to provide immersive feedback to the operator, motivating the use of predictive visual and haptic displays of the robot and environment. A teleoperation framework developed for this scenario invokes a two-part environment model that predicts motion of objects in the environment, both in free space and during contact with the robot. When objects in the environment are in free space, a propagated model using delayed data provides predictive feedback to the operator. However, when the robot interacts with the environment, a local environment model that does not propagate delayed data is used. This reduces computational load and ensures stability during robot-environment interactions. Two experiments were carried out to test the teleoperation system. Results demonstrate the ability of the prediction algorithm to provide reliable feedback and improve operator performance before, during, and after robot-environment interactions.

To ensure safe and reliable operation in a robotic oil drilling system, it is essential to detect contact events such as impacts and slips between end-effectors and workpieces. In this challenging application, where high forces are used to manipulate heavy metal pipes in noisy environments, acoustic emissions (AE) sensors offer a promising contact sensing solution. Real-time AE signal features are used to create a multinomial contact event classifier. The sensitivity of signal features to a variety of contact events including two types of slip is presented. Results indicate that the classifier is able to robustly and dynamically classify contact events with >90% accuracy using a small set of AE signal features.

This paper presents calibration and user test results of a 3-D tip-force sensing needle with haptic feedback. The needle is a modified MRI-compatible biopsy needle with embedded fiber Bragg grating (FBG) sensors for strain detection. After calibration, the needle is interrogated at 2 kHz, and dynamic forces are displayed remotely with a voice coil actuator. The needle is tested in a single-axis master/slave system, with the voice coil haptic display at the master, and the needle at the slave end. Tissue phantoms with embedded membranes were used to determine the ability of the tip-force sensors to provide real-time haptic feedback as compared to external sensors at the needle base during needle insertion via the master/slave system. Subjects were able to determine the position of the embedded membranes with significantly better accuracy using FBG tip feedback than with base feedback using a commercial force/torque sensor (p = 0.045) or with no added haptic feedback (p = 0.0024).

This study demonstrates real-time scan plane control dependent on three-dimensional needle bending, as measured from magnetic resonance imaging (MRI)-compatible optical strain sensors. A biopsy needle with embedded fiber Bragg grating (FBG) sensors to measure surface strains is used to estimate its full 3-D shape and control the imaging plane of an MR scanner in real-time, based on the needle's estimated profile. The needle and scanner coordinate frames are registered to each other via miniature radio-frequency (RF) tracking coils, and the scan planes autonomously track the needle as it is deflected, keeping its tip in view. A 3-D needle annotation is superimposed over MR-images presented in a 3-D environment with the scanner's frame of reference. Scan planes calculated based on the FBG sensors successfully follow the tip of the needle. Experiments using the FBG sensors and RF coils to track the needle shape and location in real-time had an average root mean square error of 4.2 mm when comparing the estimated shape to the needle profile as seen in high resolution MR images. This positional variance is less than the image artifact caused by the needle in high resolution SPGR (spoiled gradient recalled) images. Optical fiber strain sensors can estimate a needle's profile in real-time and be used for MRI scan plane control to potentially enable faster and more accurate physician response.

We describe an instrumented biopsy needle that provides physicians the capability to sense interaction forces directly at the tip of the needle's inner stylet. The sensors consist of optical fiber Bragg gratings (FBGs), and are unaffected by electromagnetic fields; hence the needle is suitable for MR-guided procedures. In comparison to previous instrumented needles that measure bending strains, the new design has additional sensors and a series of micro-machined holes at the tip. The holes increase strain sensitivity, especially to axial forces, without significantly reducing the stiffness or strength. A comparison of the dynamic forces measured with the new needle and those obtained using a force/torque sensor at the needle base shows that the enhanced tip sensitivity is particularly noticeable when there is significant friction along the needle sleeve.

This paper presents a tool aimed at the design of compliant, under-actuated hands. The particular motivation is hands that will be used for an underwater robot to grasp a variety of objects, some of which may be delicate or slippery. The focus of the analysis is the problem of object acquisition. In comparison to many prior grasp analysis tools, the tool presented here models the dynamics of a hand, including actuation mechanisms, compliance and friction in an efficient formulation that permits one to evaluate variations in such quantities as phalange length, finger spacing, transmission ratios, and torsional joint stiffness when comparing hand designs. The analysis is demonstrated for a quasi-static object acquisition problem and leads to the computation of a vector space of three dimensional regions for which the hand will tend to center and stably grasp a compact object.

A dynamic model of a jump glider is presented and correlated with the results obtained with a prototype glider. The glider uses a carbon fiber spring and a main wing that pivots approximately parallel to the airflow during ascent and latches into place for a gliding descent. The robot demonstrates longer traveled distance than an equivalent drag-free ballistic mass. A detailed numerical and a simplified algebraic model are also introduced, which are useful for exploring design tradeoffs and performance. These models suggest ways to improve the traveled distance and indicate that with modest variations in the wing angle of attack during ascent, one can choose from a variety of launch angles to accommodate variations in ground friction without greatly compromising range.

Dynamic surface grasping is applicable to landing of micro air vehicles (MAVs) and to grappling objects in space. In both applications, the grasper must absorb the kinetic energy of a moving object and provide secure attachment to a surface using, for example, gecko-inspired directional adhesives. Functional principles of dynamic surface grasping are presented, and two prototype grasper designs are discussed. Computer simulation and physical testing confirms the expected relationships concerning (i) the alignment of the grasper at initial contact, (ii) the absorption of energy during collision and rebound, and (iii) the force limits of synthetic directional adhesives.

The manipulation of objects in a hand or gripper is typically accompanied by events such as slippage, between the fingers and a grasped object or between the object and external surfaces. Humans can identify such events using a combination of superficial and deep mechanoreceptors. In robotic hands, with more limited tactile sensing, such events can be hard to distinguish. This paper presents a signal processing method that can help to distinguish finger/object and object/world events based on multidimensional coherence, which measures whether a group of signals are sampling a single input or a group of incoherent inputs. A simple linear model of the fingertip/object interaction demonstrates how signal coherence can be used for slip classification. The method is evaluated through controlled experiments that produce similar results for two very different tactile sensing suites.

The demands of mobile manipulation are leading to a new class of multi-fingered hands with a premium on being lightweight and robust as well as being able to grasp and perform basic manipulations with a wide range of objects. A promising approach to addressing these goals is to use compliant, underactuated hands with selectively lockable degrees of freedom. This paper presents the design of one such hand that combines series-elastic actuation and electrostatic braking at the joints. A numerical analysis shows how the maximum pullout force varies as a function of kinematic parameters, spring forces at the joints and brake torques.

We present the design, analysis, and experimental validation of a variable stiffness device based on annular dielectric electroactive polymer (EAP) actuators. The device is based on a diaphragm geometry, which partially linearizes the viscoelastic response of acrylic dielectrics, providing voltage-controlled stiffness without high damping losses. Multiple diaphragms can be connected in a single device to increase stiffness or provide custom stiffness profiles. The geometry is analyzed to determine the relationship among force, displacement and voltage. A single-layer diaphragm was constructed and tested to validate the concept, demonstrating up to 10× change in stiffness.

Dynamic perching maneuvers for fixed-wing aircraft are becoming increasingly plausible due to recent progress in perching using `micro-spines' mounted on tuned suspensions and, separately, on feedback motion planning techniques for post-stall maneuvering. In this paper, we bring these complementary techniques together by efficiently estimating the mechanical stability of the plane when it makes contact with a vertical surface; the resulting landing funnel can then be used in a feedback motion planning algorithm for the flight controller. We consider a simplified model of the perching dynamics and report an extension of the region of attraction techniques, using sums-of-squares optimization, which combines polynomial approximations of barrier constraints with the traditional Lyapunov methods to achieve tight estimation of the true region of attraction for the model. We demonstrate the new method on a variety of design parameters for the perching system, suggesting a potential use as a mechanical system or controller design tool.

A side optical actuation method is presented for a slender MR-compatible active needle. The needle includes an active region with a shape memory alloy (SMA) wire actuator, where the wire generates a contraction force when optically heated by a laser delivered though optical fibers, producing needle tip bending. A prototype, with multiple side heating spots, demonstrates twice as fast an initial response compared to fiber tip heating when 0.8 W of optical power is applied. A single-ended optical sensor with a gold reflector is also presented to measure the curvature as a function of optical transmission loss. Preliminary tests with the sensor prototype demonstrate approximately linear response and a repeatable signal, independent of the bending history.

Gait retraining, a promising treatment for knee osteoarthritis, requires the modification of three separate joint motions. In this paper we present the results of three studies to inform the design of a wearable haptic feedback system for this application. The first study motivates our choice of feedback modality for each of the motions. The latter two studies explore how to present haptic feedback to train three different motions concurrently. When feedback is presented simultaneously, subjects have poor perception of three or more haptic cues, tend to focus on only one motion at a time, and require several steps to modify all three motions. These findings suggest that vibrational feedback should be presented one joint at a time for haptic gait retraining.

This paper introduces a multi-actuator tactile device designed for remote touch communication. While closely-spaced high-frequency vibrotactile actuators can be difficult to distinguish, our system utilized four linear DC motors for presenting spatial tactile messages through low-frequency actuation. An experiment was conducted to determine accuracy for recognizing stimuli presented on the palm of the hand. Participants were asked to identify 10 predefined stimulus patterns created from the four linear actuators positioned in either a diamond or square configuration. Results showed that positional, linear, and circular stimuli were recognized with mean response accuracies of 98.8, 96.5, and 90.2%, respectively. No statistically significant differences were found between the actuator configurations. These findings can be utilized in developing a remote communication channel that supports the transfer of spatial aspects of touch such as mapping the location of finger touch of one user to tactile sensation on the palm of another user.

We describe an underactuated hand mechanism that is able to adopt a wide range of grasp types by varying the internal forces in its fingers. The adjustment is accomplished by varying the preloads of springs, which affect the grasp stability and stiffness for large and small objects. Preload adjustment can be accomplished with low power, non-backdrivable actuators in the fingers. The analysis is presented first for a planar, two-fingered hand to illustrate the trends and tradeoffs associated with variations in preload. The results are then applied numerically to a three fingered hand with three phalanges per finger. This design is a prototype for a hand to be used in an underwater oil drilling platform under conditions of low friction and uncertain object locations.

This paper presents a variable impedance suspension system based on electroactive polymer (EAP) actuators, leveraging their inherent compliance and damping, light weight, and low power requirements. We describe the manufacturing process used to create a small, lightweight EAP suspension and a novel control circuit used to vary its properties. Next, we model the electromechanical coupling by which impedance values are changed, and experimentally verify its behavior. Of particular interest is the transient response, for example, as encountered when a robot touches down after jumping or gliding. We conclude with a discussion of the changes in performance that are possible when applying a variable impedance EAP suspension to a small flying and perching robot.

We present two foot mechanisms that allow relatively large patches of synthetic fibrillar dry adhesives applied inexactly by a climbing robot to perform at levels previously obtained only for small samples in precisely aligned and controlled bench-top tests. The mechanisms are inspired by the structures found in the toes of the gecko. The first mechanism uses ankles with roll and yaw flexures and a compliant structure behind the adhesive material to achieve approximately uniform pressures under nominal loading conditions on flat and curved surfaces. The second design uses a tendon-supported structure to achieve uniform loading and prevent premature peeling failures despite significant misalignment with a flat wall surface. The two designs are demonstrated on Stickybot III, an approximately 1 kg climbing robot, and can be scaled to larger areas and loads by tiling the basic structure.

A new generation of robots is being designed for human occupied workspaces where safety is of great concern. This research demonstrates the use of a capacitive skin sensor for collision detection. Tests demonstrate that the sensor reduces impact forces and can detect and characterize collision events, providing information that may be used in the future for force reduction behaviors. Various parameters that affect collision severity, including interface friction, interface stiffness, end tip velocity and joint stiffness irrespective of controller bandwidth are also explored using the sensor to provide information about the contact force at the site of impact. Joint stiffness is made independent of controller bandwidth limitations using passive torsional springs of various stiffnesses. Results indicate a positive correlation between peak impact force and joint stiffness, skin friction and interface stiffness, with implications for future skin and robot link designs and post-collision behaviors.

An active needle is proposed for the development of MRI guided percutaneous procedures. The needle uses internal laser heating, conducted via optical fibers, of a shape memory alloy (SMA) actuator to produce bending in the distal section of the needle. Active bending of the needle as it is inserted allows it to reach small targets while overcoming the effects of interactions with surrounding tissue, which can otherwise deflect the needle away from its ideal path. The active section is designed to bend preferentially in one direction under actuation, and is also made from SMA for its combination of MR and bio-compatibility and its superelastic bending properties. A prototype, with a size equivalent to standard 16G biopsy needle, exhibits significant bending with a tip rotation of more than 10°. A numerical analysis and experiments provide information concerning the required amount of heating and guidance for design of efficient optical heating systems.

Joint stiffness plays an important role in both safety and control performance, particularly in human-friendly robots using artificial pneumatic muscles. Due to the limited control bandwidth of pneumatic muscles, stiffness characteristics and their effects on safety in the frequency domain should be taken into account. This paper introduces the concept of instantaneous stiffness and validates its model with the Stanford Safety Robot (S2ρ. The potential effects of instantaneous stiffness on safety is explored through experimental comparison of peak impact accelerations under various impact conditions. Instantaneous stiffness demonstrates different effects on the impact acceleration depending on impact velocity and controller gain. Finally, the paper discusses the stiffness characteristics as a guideline for design and control to improve the robot safety while maintaining the control performance.

We present a wearable haptic feedback device for the foot, which gives the sensation of a small pebble in a shoe when actuated and no sensation otherwise. Because it stimulates slowly-adapting as well as fast-adapting mechanoreceptors it is useful for displaying a condition that may persist over time, as well as the occurrence of an event. The feedback, which we call the “virtual pebble” due to its ability to appear on command, is intended as a complement to vibration feedback. We performed a user study to quantify perception accuracy during standing, walking, and jogging for haptic feedback combinations on the foot and knee from vibrotactors and the virtual pebble. We also quantified absolute perception thresholds for single vibration and virtual pebble actuations. Results show that subjects are able to correctly perceive a combination of the pebble and vibration much more accurately than a combination of two vibrations. In addition, subjects are most sensitive to vibration feedback while stationary but most sensitive to virtual pebble feedback while jogging. These findings suggest that the virtual pebble is useful as an additional channel of haptic feedback during ambulatory locomotion.

We present an approach that builds upon previous developments in unmanned air vehicles and climbing robots and seeks to emulate the capabilities of bats, insects and certain birds that combine powered flight with the ability to land and perch on sloped and vertical surfaces. As it approaches a wall, the plane executes an intentional pitch-up maneuver to shed speed and present its feet for landing. On contact, a nonlinear suspension dissipates the remaining kinetic energy and directs interaction forces toward the feet to engage small asperities on surfaces such as brick or concrete. The focus of the work in this paper is on the controller used for sensing a wall and executing vertical landing and take-off procedures and on the mechanisms developed for spine engagement and disengagement.

We present an approach that builds upon previous developments in unmanned air vehicles and climbing robots and seeks to emulate the capabilities of bats, insects and certain birds that combine powered flight with the ability to land and perch on sloped and vertical surfaces. As it approaches a wall, the plane executes an intentional pitch-up maneuver to shed speed and present its feet for landing. On contact, a nonlinear suspension dissipates the remaining kinetic energy and directs interaction forces toward the feet, where microspines can engage small asperities on surfaces such as brick or concrete. The plane can then take off by disengaging the spines and lifting off, pointing its nose up and away from the wall to slowly build forward speed until it can resume normal flight.

A formidable challenge in the development of human-friendly robots is to simultaneously achieve desired levels of performance and safety. To address this issue, a hybrid actuation concept has been proposed, combining large, low impedance actuators and small, high-frequency actuators. However, the determination of design parameters remains a challenge, as stiffness and electrical motor torque capacity simultaneously affect both the control performance and the safety of the manipulator. Using analytical models of the hybrid actuation system, we propose a methodology to achieve a combination of low impedance and high control bandwidth. The optimized parameters are verified and compared with previous ones through simulation and experimentation.

The priorities of a climbing legged robot are to maintain a grasp on its climbing surface and to climb efficiently against the force of gravity. These priorities profoundly constrain the choice of gait regulation methods. We propose a gait regulation and analysis method that varies foot detachment timing, effectively modifying stride length and frequency in order to maintain gait phasing, subject to kinematic and stability constraints. The method results in linear equations, leading to straightforward tests for local and global convergence when, for example, disturbances such as foot slippage cause departures from the nominal phasing. We illustrate the procedure with an example involving a bounding gait and compare it with empirical results obtained on the RiSE climbing robot.

As robots and humans move towards sharing the same environment, the need for safety in robotic systems is of growing importance. Towards this goal of human-friendly robotics, a robust, low-cost, low-noise capacitive force sensing array is presented with application as a whole body artificial skin covering. This highly scalable design provides excellent noise immunity, low-hysteresis, and has the potential to be made flexible and formable. Noise immunity is accomplished through the use of shielding and local sensor processing. A small and low-cost multivibrator circuit is replicated locally at each taxel, minimizing stray capacitance and noise coupling. Each circuit has a digital pulse train output, which allows robust signal transmission in noisy electrical environments. Wire count is minimized through serial or row-column addressing schemes, and the use of an open-drain output on each taxel allows hundreds of sensors to require only a single output wire. With a small set of interface wires, large arrays can be scanned hundreds of times per second and dynamic response remains flat over a broad frequency range. Sensor performance is evaluated on a bench-top version of a 4 × 4 taxel array in quasi-static and dynamic cases.

Prior research in biology and mechanics has shown the importance of hierarchy to the performance of dry adhesive systems on rough surfaces. The gecko utilizes several levels of hierarchy that operate on length scales from millimeters to 100s of nanometers in order to maneuver on smooth and rough vertical surfaces ranging from glass to rock. The gecko's hierarchical system serves two main purposes: it permits conformation to the surface for a large effective area of contact, and it distributes the load evenly among contacting elements. We present a new two-tiered directional adhesive system that provides these capabilities for a gecko-inspired climbing robot. The distal features consist of wedge-shaped structures with a base width of 50 mum and a height of approximately 180 mum. The wedges are mounted atop angled cylindrical features, 380 mum in diameter by approximately 1 mm long. Together, the proximal and distal features bend preferentially in the direction of inclination when loaded with a tangential force, achieving a combination of directional adhesion and conformation to rough surfaces. Using this system, a four legged robot that was previously restricted to climbing smooth surfaces is able to climb vertical surfaces such as a wood panels, painted metals, and plastics. On rougher surfaces, the two-tiered system improves adhesion by a factor of five compared to the wedge features alone. The hierarchical system also improved alignment and performance for large patch sizes.

Determining design parameters is often a challenging procedure, especially in human-friendly robot design due to competition between robot safety and performance. Presenting an analytical model of hybrid actuation for human-friendly robot development, this paper proposes design methodologies to improve performance factors such as range of motion, payload, and acceleration while maintaining the safety factor of effective inertia. The optimized parameters for various design requirements have been provided for 1DOF and 2DOF applications. Comparison between current design parameters and the optimized parameters for a current platform shows the performance improvement. In future work this research will be extended to systems with higher degrees of freedom.

Climbing robots are especially susceptible to thermal overload during normal operation, due to the need to oppose gravity and to frequently apply internal forces for clinging. As an alternative to setting conservative limits on the motor peak and average current, we investigate methods for measuring motor temperatures, predicting motor thermal conditions and generating thermally constrained behavior. A thermal model, verified using empirical data, predicts the motor's winding temperature based on measured case temperature and input current. We also present a control strategy that maximizes robot velocity while satisfying a constraint on the maximum permissible motor winding temperature.

We describe a simple and low-cost system that can help multiple sclerosis (MS) patients with asymmetric impairment to exert better grasp force control in manipulation tasks. The approach consists of measuring force vectors at the fingertips of the impaired hand, computing the force imbalance among the fingers, and providing corresponding haptic signals to the fingers of the opposite hand. Tests conducted on 24 MS patients indicated that for those with mild impairment, slightly better results were obtained with an ldquoevent-cuerdquo feedback (ECF) that alerted them when the grasp forces were straying outside of a desirable range. For patients with more severe impairment, better results were obtained by providing a proportional signal, in which the frequency and duty cycle of vibration pulses were correlated directly with the magnitudes of the fingertip forces. Post-test surveys of the patients also indicated that mildly impaired subjects preferred an event-cue feedback, and more severely impaired subjects preferred the proportional feedback.

Force sensing is an essential requirement for dexterous robot manipulation. We describe composite robot end-effectors that incorporate optical fibers for accurate force sensing and estimation of contact locations. The design is inspired by the sensors in arthropod exoskeletons that allow them to detect contacts and loads on their limbs. In this paper, we present a fabrication process that allows us to create hollow multimaterial structures with embedded fibers and the results of experiments to characterize the sensors and controlling contact forces in a system involving an industrial robot and a two-fingered dexterous hand. We also briefly describe the optical-interrogation method used to measure multiple sensors along a single fiber at kilohertz rates for closed-loop force control.

We describe the dynamic testing and control results obtained with an exoskeletal robot finger with embedded fiber optical sensors. The finger is inspired by the designs of arthropod limbs, with integral strain sensilla concentrated near the joints. The use of fiber Bragg gratings (FBGs) allows for embedded sensors with high strain sensitivity and immunity to electromagnetic interference. The embedded sensors are useful for contact detection and for control of forces during fine manipulation. The application to force control requires precise and high-bandwidth measurement of contact forces. We present a nonlinear force control approach that combines signals from an optical interrogator and conventional joint angle sensors to achieve accurate tracking of desired contact forces.

The adhesive and frictional properties of dry adhesive materials can be described by a three-dimensional limit surface in the space of normal and tangential contact forces at the feet. We present the empirically derived limit surface for directional adhesive pads and illustrate its application to controlling the forces at the feet of a robot climbing on arbitrary slopes, including overhanging surfaces. For the directional adhesive patches that we have developed, the limit surface is convex, which permits efficient computation of the desired internal and external forces among the feet to maximize a safety margin with respect to disturbance forces on the robot. The limit surface also intersects the origin in force space, which enables efficient climbing without wasting energy in attaching and detaching the feet. These insights are applied to an experimental climbing platform demonstrating the proper use of directional adhesion and mimicking the climbing behavior seen in geckos.

This DOI is not currently attached to any metadata records. DOIs can’t actually ever be deleted (they’re persistent), but sometimes our members create DOIs in error. We do have a process to approximate deletion which we follow only in rare cases where the DOI has been genuinely created in error, and most crucially, if the DOI has never been published anywhere online or in print and never otherwise distributed to or communicated with anyone (authors, readers, reviewers, etc.

We describe the design and control of a new bio-inspired climbing robot designed to scale smooth vertical surfaces using directional adhesive materials. The robot, called Stickybot, draws its inspiration from geckos and other climbing lizards and employs similar compliance and force control strategies to climb smooth vertical surfaces including glass, tile and plastic panels. Foremost among the design features are multiple levels of compliance, at length scales ranging from centimeters to micrometers, to allow the robot to conform to surfaces and maintain large real areas of contact so that adhesive forces can support it. Structures within the feet ensure even stress distributions over each toe and facilitate engagement and disengagement of the adhesive materials. A force control strategy works in conjunction with the directional adhesive materials to obtain sufficient levels of friction and adhesion for climbing with low attachment and detachment forces.

Force sensing is an essential requirement for dexterous robot manipulation. Although strain gages have been widely used, a new sensing approach is desirable for applications that require greater robustness, design flexibility and immunity to electromagnetic noise. An exoskeletal force sensing robot finger was developed by embedding fiber Bragg grating (FBG) sensors into a polymer-based structure. Multiple FBG sensors were embedded into the structure to allow the manipulator to sense and measure both contact forces and grasping forces. In order to fabricate a three-dimensional structure, a new shape deposition manufacturing (SDM) process was explored. The sensorized SDM-fabricated finger was then characterized using an FBG interrogator. A force localization scheme is also described

Recent biological research suggests that reliable, agile climbing on smooth vertical surfaces requires controllable adhesion. In nature, geckos control adhesion by properly loading the compliant adhesive structures on their toes. These strongly anisotropic dry adhesive structures produce large frictional and adhesive forces when subjected to certain force/motion trajectories. Smooth detachment is obtained by simply reversing these trajectories. Each toe's hierarchical structure facilitates intimate conformation to the climbing surface resulting in a balanced stress distribution across the entire adhesive area. By controlling the internal forces among feet, the gecko can achieve the loading conditions necessary to generate the desired amount of adhesion. The same principles have been applied to the design and manufacture of feet for a climbing robot. The manufacturing process of these Directional Polymer Stalks is detailed along with test results comparing them to conventional adhesives.

This paper presents a new miniature gripper design, suitable for endoscopic surgery and similar applications. The gripper is based on a mechanism fabricated in-situ via a rapid prototyping process that permits multiple materials and the addition of embedded components. The gripper is actuated using a tuned vibrating mass and impact mechanism. The mechanism relies on close tolerances and clearances, obtained by depositing and subsequently removing thin films of sacrificial material. The gripper design and fabrication process are scalable, and future versions of the gripper can be made at a fraction of the size of the first 15 mm prototype without incurring manufacturing difficulty. Tests on the first prototype reveal the importance of controlling friction and preload at the sliding interface.

Shared control represents a middle ground between supervisory control and traditional bilateral control in which the remote system can exert control over some aspects of the task while the human operator maintains access to low-level forces and motions. Our telemanipulation system includes tactile, force and motion sensors that allow the slave to regulate grasp forces and impart rolling motions to a grasped object. We describe a set of experiments designed to determine whether shared control can improve the ability of an operator to handle objects delicately and to determine what combinations of force, visual and audio feedback provide the best level of performance and operator sense of presence. The results demonstrate the benefits of shared control and the need to choose carefully the types and methods of direct and indirect feedback.

We review the state of the art in friction estimation and rendering for haptic interfaces and present a method based on a modified Karnopp friction model. We illustrate some of the advantages of this approach and show how it can be used to create accurate and convincing displays of sliding friction, including pre-sliding displacement and stick-slip behavior. We also present the results of human performance experiments in targeting tasks and show that real and simulated friction produce essentially the same results. In both cases, moderate low-stiction friction can improve performance and high stiction degrades it.

Haptic exploration with robotic fingers is accomplished by feature-guided exploration, where information about surface features such as cracks and ridges is used to guide the finger in an exploratory procedure. A local exploration strategy uses contact trajectory information from a tactile sensor to identify features while moving over and around them. Using an algorithm based on the Voronoi diagram, an approximation of the medial axis of the feature is found, then pruned using an edge length threshold. Multiple feature skeletons are then used to create a global skeleton that partitions the surface into regions. The models resulting from these local and global explorations can be used to characterize objects for information storage and manipulation planning.

Presents an overview of research in dexterous manipulation. We first define robotic dexterous manipulation in comparison to traditional robotics and human manipulation. Next, kinematics, contact types and forces are used to formulate the dexterous manipulation problem. Dexterous motion planning is described, which includes grasp planning and quality measures. We look at mid- and low-level control frameworks, and then compare manipulation versus exploration. Finally, we list accomplishments in the different areas of dexterous manipulation research, and highlight important areas for future work.

We consider the detection of small surface features, such as ridges and bumps, on the surface of an object during dextrous manipulation. First, we review the representation of object surface geometry and present definitions of surface features based on local curvature. These definitions depend on the geometries of both the robot fingertips and the object being explored. We also show that the trajectory traced by a round fingertip rolling or sliding over the object surface has some intrinsic properties that facilitate feature detection. Next, several algorithms based on the feature definitions are presented and compared. Finally, we present simulated and experimental results for feature detection using a hemispherical fingertip equipped with an optical tactile sensor.

Multifingered robotic hands have not yet made significant inroads into practical applications, partly due to the complexity of dextrous manipulation tasks, and also due to control software shortcomings. High level task controllers exist, as do low level grasp controllers, but neither of these fully address the problems of changing kinematic and dynamic constraints that arise during a grasping and manipulation task. This paper develops a framework, utilizing phases, events, and transitions, that bridges the gap between highand low-level control. Results from constraint handling and transition experiments conducted with a two-fingered hand are included.

We present an approach for haptic exploration of unknown objects with dextrous robotic hands. The emphasis is on developing a robust manipulation process that allows fingers to traverse the surface of an object. The process consists of a sequence of phases in which some fingers are responsible for grasping and manipulating the object while others roll and slide over the object surface. The rolling/sliding fingers can utilize sensors to determine surface properties such as texture, friction or small features such as grooves and ridges. Simulations and experiments with a two-fingered hand were conducted to investigate the robustness of the approach for exploring various object shapes.

In this paper, we study stiffness analysis as applied to human grasping. Grasp stiffness has been demonstrated to be useful for modeling and controlling robotic manipulators. The computation of general linear R/sup 3/spl times/3/ stiffness matrices for grasping, which can be decomposed into symmetric (conservative) and asymmetric (nonconservative) components, offers physical insights for stiffness control in robotics as well as human grasping. Methods of stiffness calibration, using least-squares best fits with and without symmetry constraints, are presented and applied to the force and displacement data obtained from grasping tasks to study human grasping behaviors. The results of this study show that a linear relationship between force and displacement is capable of capturing the characteristics of the experimental data of human grasps for which displacements are small (on the order of one to seven mm). Different measures, proposed and developed in the robotics literature, are employed to predict the behavior of human grasps in reacting to externally applied loads.

The superiority of deformable human fingertips as compared to hard robot gripper fingers for grasping and manipulation has lead to a number of investigations with robot hands employing elastomers or materials such as fluids or powders beneath a membrane at the fingertips. When using such materials, it is important to account for their properties during manipulation. The rigid-body rolling kinematic equations developed and applied in previous investigations do not consider load- and object-dependent fingertip deformations. This paper is concerned with determining the kinematic effects of soft fingertips during manipulation with rolling. The long-term goal of this work is to produce a model of rolling with soft fingertips that can be incorporated into a real-time control system to produce current best estimates of contact locations and velocities when planning and executing rolling maneuvers.

This paper presents an experimental comparison of tactile array versus force-torque sensing for localizing contact during manipulation. The manipulation tasks involved rotating and translating objects using a planar two fingered manipulator. A pin and a box were selected as limiting cases of point and line contact against a cylindrical robot finger tip. Force-torque contact sensing results suffered from difficulties in calibration, transient forces, and low grasp force. Tactile array sensing was immune to these problems, and the effect of shear loading was only noticeable for a simple centroid algorithm. The results show that with care, both of these sensing schemes can determine the contact location within a millimeter during real manipulation tasks.

We present an approach to event detection during a dexterous manipulation task. The approach utilizes a combination of tactile sensors as well as contextual information. The manipulation task is decomposed into distinct phases, each of which is associated with a limited number of feasible events such as making or breaking contact, slipping, etc. A set of context-based and sensor-based features is associated with each possible event for each type of manipulation phase. The goal is to detect events as reliably and as rapidly as possible. At any time during a task, each possible event is assigned a confidence value between 0 and 1. This indicates how confident the detection scheme is that a given event could be occurring at that instant. A high-level controller can then make use of this information to determine when to switch to a different manipulation phase.

We address the problem of controlling contact forces generated when the fingers of a robot close on an object or make contact with surfaces in the robot's environment. The use of controllable fingertip materials is proposed to enhance system performance and avoid contact instability problems that can arise with noncollocated sensors and actuators. We describe a novel fingertip employing an electrorheological fluid and present the results of experiments to evaluate its capabilities when used with a robot contacting a stationary object at various speeds. Having characterized the fingertip behavior as a function of applied voltage, we turn to the question of optimal control, Using a simplified dynamic model of a robot equipped with a controllable electrorheological fingertip, we obtain a piece-wise optimal solution for the fingertip damping as a function of time, to minimize settling time while satisfying constraints on the contact forces.

This paper concerns a new tactile sensor with both 3-axis force sensing and slip sensing functions. The first three axis force sensing is achieved with tactile heads, each of which is supported by three pressure sensing elements. The pressure sensing function is achieved with arrays of pressure transducers that measure a change in the contact resistance between a specially treated polyimide film and a resistive substrate. The slip sensing function is achieved through the use of a stress-rate sensor that responds to small-scale variations in a surface profile with roughness. Static and dynamic analyses of the new tactile sensor were made and compared with experimental results. Further experiments were conducted with an algorithm to detect rotational slip.>

The SHARE project seeks to apply information technologies in helping design teams gather, organize, re-access, and communicate both informal and formal design information to establish a "shared understanding" of the design and design process. This paper presents the visions of SHARE, along with the research and strategies undertaken to build an infrastructure toward its realization. A preliminary prototype environment is being used by designers working on a variety of industry sponsored design projects. This testbed continues to inform and guide the development of NoteMail, MovieMail, and Xshare, as well as other components of the next generation SHARE environment that will help distributed design teams work together more effectively on the Internet.

Dynamic tactile sensing, which is defined as sensing during motion for perception of high spatial and temporal frequencies, is presented. Applications include sensing fine surface features and textures and monitoring contact conditions for dextrous manipulation. One type of dynamic tactile sensor, the stress rate sensor, is described in detail. It uses piezoelectric polymer transducers to measure the changes in stress induced in the sensor's rubber skin as it traverses small surface features and textures. The signals are interpreted with the aid of a solid mechanics model of the contact interaction and a linear deconvolution filter. Experimental verification of the sensor's performance, including the detection of surface features only 6.5 mu m high, are presented.>

The ability to sense and respond to frictional variations is important for dexterous manipulation. It is demonstrated that it is possible to elicit rapid, nonhabituating and sustained grasp responses by means of a tactile display. Experiments in which subjects grasped and lifted an instrumented test object using the thumb and index finger are reported. While the object was held in air, rapid but small sliding movements were invoked between the object and either contact plate and caused a load force redistribution. This reliably triggered a grasp force increase similar to the ones elicited by natural slips occurring during normal manipulation. An important application of this finding is in relaying frictional information from a slave hand to a human operator. Furthermore, it may make it possible to reduce disparity between master and slave hands in force reflective telemanipulation systems.>

Many real-world planning problems involve substantial amounts of domain-specific reasoning that is either awkward or inefficient to encode in a general purpose planner. A hybrid planning architecture for such domains is proposed. It utilizes a set of specialists to complement both the overall expressiveness and the efficiency of a traditional hierarchical planner. Such an architecture promises to retain the flexibility and generality of a classical planning framework while allowing deeper and more efficient domain-specific reasoning through specialists. The architecture has several ramifications on the internal operations of the planner as well as its interactions with the specialists. Continual interactions between the planner and the specialists necessitate an incremental, interactive, and least-commitment oriented approach to planning. As the planner and the specialists in such a model may use heterogeneous reasoning mechanisms and representations, a complete understanding of the operations of one by the other is not possible.>

The issue of controlling contact forces generated when the fingers of a dextrous device first close on an object is addressed. The use of active fingertips is proposed to enhance the system performance and avoid contact instability problems resulting from noncollocated sensors and actuators. A first step towards exploring this issue is the study of an idealized controllable fingertip making contact with an object. The authors provide analytical and simulation studies to identify ideal fingertip characteristics to achieve a desired performance for a simple contact problem. An investigation of the performance of more realistic fingers with limited controllability follows. Preliminary experimental results for a prototype semi-active fingertip that uses an electrorheological fluid to achieve active damping control are provided. A brief summary of future experimental plans to implement such active fingertips in simple manipulation tasks is presented.>

Preliminary experiments are presented concerning the use of tactile sensing to enhance the flexibility and robustness of robotic manipulation. A simple two-fingered manipulator with very clean dynamics has been constructed to focus on tactile and force sensing in manipulation. Manipulation is characterized by constantly changing mechanical systems, as fingers make or break contact or start to roll or slide on the surface of a grasped object. It is important to detect these changes since control schemes must change to match the varying task requirements. Following the human model, it is shown that dynamic tactile sensors can reliably detect the changing contact conditions. In a simple grasp-lift-replace task, use of these sensors enables the manipulator to cope with uncertainty in object location and task forces.>

The authors present an attempt to model soft robot fingertips filled with powders or plastic fluids. They propose two rolling models, adapted from hot metal rolling and extrusion, and discuss the factors that affect the choice of appropriate models. The integration of energy losses in the dynamic equations of motion is then considered. Initial simulation studies have shown that soft fingertips can help stabilize the grasp and reduce the demands on the control system. The viscoplastic nature of the finger tips affects the dynamics of manipulation by dissipating energy. The coin snap problem is given as an example to demonstrate this effect.>

The authors present a scheme for sensing small accelerations of the outer skin covering the fingers of a manipulator. The sensor is constructed with a thin rubber skin covering a soft inner layer of foam rubber. This decouples the skin from the manipulator structure, isolating it from structural vibrations and facilitating the tracking of object surfaces. An accelerometer attached to the inner surface of the skin measures the large local accelerations produced when areas of the skin catch and snap back as the sensor moves against a surface. The authors present experimental confirmation of the ability to detect the onset of slip, and discuss the sensor response to various surface texture parameters.>

Prototype fingertips using electrorheological (ER) fluids with elementary tactile sensing were fabricated and tested. The fingertips consist of a layer of ER fluid sandwiched between a grounded elastomer skin and a positively charged electrode. This arrangement forms a capacitor whose value increases as the elastomer is deflected toward the positive electrode. The ER fingertips can be put on a robot gripper or the fingers of a dextrous robot hand. The fluid layer acts as a soft conformal pad when the voltage is turned off. When energized, the fluid changes from a Newtonian fluid to a Bingham plastic with a yield stress of a few kPa. The result is a finger with simple tactile sensing and the ability to generate large lifting forces with small grasp forces, due to interlocking between the deformed skin/solidified fluid and the gripped object. A gripper with ER fingertips was able to grip a raw egg gently using capacitance sensing. The authors examine the improved lifting force available with ER fingertips over passive designs. The design of a multielement fingertip for shape sensing is investigated and recommendations are offered for designing practical ER robotic hands.>

Current analytical models of grasping and manipulation with robotic hands contain simplifications and assumptions that limit their application to manufacturing environments. To evaluate these models, a study was undertaken of the grasps used by machinists in a small batch manufacturing operation. Based on the study, a taxonomy of grasps was constructed. An expert system was also developed to clarify the issues involved in human grasp choice. Comparisons of the grasp taxonomy, the expert system, and grasp-quality measures derived from the analytic models reveal that the analytic measures are useful for describing grasps in manufacturing tasks despite the limitations in the models. In addition, the grasp taxonomy provides insights for the design of versatile robotic hands for manufacturing.>

The authors express the compliance of the grasp of a robotic hand as a function of grasp geometry, contact conditions between the fingers and the grasped object, and mechanical properties of the fingers. It is argued that the effects of structural compliance and small changes in the grasp geometry should be included in the computation. Factors are then examined that can lead a grasp to become unstable, independently of whether it satisfies force closure. Finally, the authors examine the reverse problem of how to specify servo gains at the joints of a robotic hand so as to achieve, as nearly as possible, a desired overall grasp compliance. It is shown that coupling between the joints of different fingers is useful in this context.>

The authors are concerned with finding the magnitudes of applied moment and force which will cause a robot finger to slip on the surface of a grasped object. Friction and contact models used in previous grasp analyses are reviewed, and an improved model which includes torsion-shear interaction is described. Experimental measurements of the initiation of sliding as a function of loading are reported. These measurements suggest that a simple linear function of torsion and shear magnitudes will adequately predict the onset of the slip in many tasks. The use of this function is illustrated in two measures of slip susceptibility for grasp planning.>

Compliant materials were tested both under clean, dry conditions and with environmental contamination to determine which materials were most suitable for the contact areas of a robotic hand and to establish accurate models of the materials' frictional behavior. Some of the most promising materials under clean, dry conditions performed unreliably in the presence of oil and water. Contact shape, surface texture and surface porosity each had a strong effect on the ultimate coefficient of friction. Combining the results of these tests with what we know about the skin on human and primate hands leads to several design conclusions about the ideal skin for the fingers of a robotic hand.

This paper represents the first part of an effort to codify the knowledge required for manipulation tasks in a small-batch manufacturing cell. The motivation for this work is to pave the way for robots that can independently determine how to grasp and manipulate parts in a limited environment and to facilitate the design of advanced, but cost-effective manufacturing hands. We begin with an examination of grasps used by humans working with tools and metal parts. The grips are compared in terms of power, contact area, friction, damping and tactile sensitivity. The comparison leads to a grip taxonomy in which grasps are mapped against task-related quantities (such as power) and object-related quantities (such as slenderness). The examinations of the task requirements and grasps suggest a number of general principles for the design and control of manufacturing hands.