This paper describes the development of a system for lifelike gaze in human-robot interactions using a humanoid Audio-Animatronics®bust. Previous work examining mutual gaze between robots and humans has focused on technical implementation. We present a general architecture that seeks not only to create gaze interactions from a technological standpoint, but also through the lens of character animation where the fidelity and believability of motion is paramount; that is, we seek to create an interaction which demonstrates the illusion of life. A complete system is described that perceives persons in the environment, identifies persons-of-interest based on salient actions, selects an appropriate gaze behavior, and executes high fidelity motions to respond to the stimuli. We use mechanisms that mimic motor and attention behaviors analogous to those observed in biological systems including attention habituation, saccades, and differences in motion bandwidth for actuators. Additionally, a subsumption architecture allows layering of simple motor movements to create increasingly complex behaviors which are able to interactively and realistically react to salient stimuli in the environment through subsuming lower levels of behavior. The result of this system is an interactive human-robot experience capable of human-like gaze behaviors.

We present a system for fast and robust handovers with a robot character, together with a user study investigating the effect of robot speed and reaction time on perceived interaction quality. The system can match and exceed human speeds and confirms that users prefer human-level timing. The system has the appearance of a robot character, with a bear-like head and a soft anthropomorphic hand and uses Bézier curves to achieve smooth minimum-jerk motions. Fast timing is enabled by low latency motion capture and real-time trajectory generation: the robot initially moves towards an expected handover location and the trajectory is updated on-the-fly to converge smoothly to the actual handover location. A hybrid automaton provides robustness to failure and unexpected human actions. In a 3x3 user study, we vary the speed of the robot and add variable sensorimotor delays. We evaluate the social perception of the robot using the Robot Social Attribute Scale (RoSAS). Inclusion of a small delay, mimicking the delay of the human sensorimotor system, leads to an improvement in perceived qualities over both no delay and long delay conditions. Specifically, with no delay the robot is perceived as more discomforting, and with a long delay it is perceived as less warm.

This work explores social perceptions of robots within the domain of human-to-robot handovers. Using the Robotic Social Attributes Scale (RoSAS), we explore how users socially judge robot receivers as three factors are varied: initial position of the robot arm prior to handover, grasp method employed by the robot when receiving a handover object trading off perceived object safety for time efficiency, and retraction speed of the arm following handover. Our results show that over multiple handover interactions with the robot, users gradually perceive the robot receiver as being less discomforting and having more emotional warmth. Additionally, we have found that by varying grasp method and retraction speed, users may hold significantly different judgments of robot competence and discomfort. With these results, we recognize empirically that users are able to develop social perceptions of robots which can change through modification of robot receiving behaviour and through repeated interaction with the robot. More widely, this work suggests that measurement of user social perceptions should play a larger role in the design and evaluation of human-robot interactions and that the RoSAS can serve as a standardized tool in this regard.

Human performers have developed impressive acrobatic techniques over thousands of years of practicing the gymnastic arts. At the same time, robots have started to become more mobile and autonomous, and can begin to imitate these stunts in dramatic and informative ways. We present a simple two degree of freedom robot that uses a gravity-driven pendulum launch and produces a variety of somersaulting stunts. The robot uses an IMU and a laser range-finder to estimate its state mid-flight and actuates to change its motion both on and and off the pendulum. We discuss the dynamics of this behavior in a framework of acrobatic capability and present experimental results.

Coiled actuators made from polymer fibers are fast becoming popular due to their low-cost and ease of fabrication. Unfortunately, reliable real-time temperature measurement has been frustrated by the small fiber diameter of typical actuators. By using coiled polymer fibers wrapped with a metal wire, we demonstrate the ability to concurrently drive a muscle by electrothermal heating, and monitor muscle temperature through the wire resistance. This simple method enables convenient overheat protection for these muscles, as well as the possibility for closed-loop temperature control. Using this platform, we demonstrate a nested controller using temperature and position feedback to improve contraction speed, and investigate the cooling rates of various configurations that increase total force output.

In this paper we use KUKA's Fast Robot Interface (FRI) to design and implement a tracking controller on the Lightweight Robot (LBR) IIWA. We seek low latency, accurate and smooth tracking of the link positions to facilitate human interaction tasks. Focusing on a single joint and its low-level series elastic dynamics, we identify the internal torque control structure and its characteristics. Tracking controllers of varying complexity are tested in an optical motion capture system to provide an independent external reference measurement. Using full state feedback of both motor position and sensed joint torque, we achieve smooth and good tracking of the unsensed link positions.

In this paper we examine joint torque tracking as well as estimation of external torques for the KUKA Lightweight Robot (LBR) IIWA. To support physical human-robot interaction tasks, we need smooth estimation that allows detection of delicate external events and good control to hide inertial forces. Unfortunately a transmission nonlinearity in the motor to joint gearing injects vibrations and limits the performance of the built-in torque controller and observer. We confirm the nonlinearity to be a spatially periodic deflection between the motor and joint. Identification of this behavior allows us to generate more accurate joint position measurements. We also design a matching spatial filter to remove the vibrations from joint torque measurements. Experiments on an LBR IIWA show that compensating for the nonlinearity provides smoother external torque estimates and improves the torque tracking performance. Furthermore, we are able to increase the gain margin more than three fold over the built-in controller.

As agile robots learn to run and hop, we believe they will soon also perform large jumps and spins that require graceful landing. To land properly, they will need to be aware of their relative body orientation during free fall and make appropriate adjustments. In this paper, we examine the sensing and actuation necessary for a mechanism to alter its fall under a high rate of spin. We also present a simple new robot, the Binary Robotic Inertially Controlled bricK (BRICK). This device combines information from an accelerometer, a gyroscope, and a laser range-finder to track its orientation, and adjusts spin mid-flight by rapidly changing its moment of inertia between two states. An error analysis shows mechanical inaccuracies and uncertainty to be the largest source of variation. Nevertheless, our mechanism is able to fall from arbitrary heights, with arbitrary spin, and always land in a desired orientation.

We present a system enabling users to accurately catch a real ball while immersed in a virtual reality environment. We examine three visualizations: rendering a matching virtual ball, the predicted trajectory of the ball, and a target catching point lying on the predicted trajectory. In our demonstration system, we track the projectile motion of a ball as it is being tossed between users. Using Unscented Kalman Filtering, we generate predictive estimates of the ball's motion as it approaches the catcher. The predictive assistance visualizations effectively increases the user's senses but can also alter the user's strategy in catching.

Robotics have long sought an actuation technology comparable to or as capable as biological muscle tissue. Natural muscles exhibit a high power-to-weight ratio, inherent compliance and damping, fast action, and a high dynamic range. They also produce joint displacements and forces without the need for gearing or additional hardware. Recently, supercoiled commercially available polymer threads (sewing thread or nylon fishing lines) have been used to create significant mechanical power in a muscle-like form factor. Heating and cooling the polymer threads causes contraction and expansion, which can be utilized for actuation. In this paper, we describe the working principle of supercoiled polymer (SCP) actuation and explore the controllability and properties of these threads. We show that under appropriate environmental conditions, the threads are suitable as a building block for a controllable artificial muscle. We leverage off-the-shelf silver-coated threads to enable rapid electrical heating while the low thermal mass allows for rapid cooling. We utilize both thermal and thermomechanical models for feed-forward and feedback control. The resulting SCP actuator regulates to desired force levels in as little as 28 ms. Together with its inherent stiffness and damping, this is sufficient for a position controller to execute large step movements in under 100 ms. This controllability, high performance, the mechanical properties, and the extremely low material cost are indicative of a viable artificial muscle.

Robots are ever more present in human environments and effective physical human-robot interactions are essential to many applications. But to a person, these interactions rarely feel biological or equivalent to a human-human interactions. It is our goal to make robots feel more human-like, in the hopes of allowing more natural human-robot interactions. In this paper, we examine a novel biologically-inspired control method, emulating antagonistic muscle pairs based on a nonlinear Hill model. The controller captures the muscle properties and dynamics and is driven solely by muscle activation levels. A human-robot experiment compares this approach to PD and PID controllers with equivalent impedances as well as to direct human-human interactions. The results show the promise of driving motors like muscles and allowing users to experience robots much like humans.

Natural muscles exhibit high power-to-weight ratios, inherent compliance and damping, fast actuation and high dynamic ranges. Unfortunately, traditional robotic actuators have been unable to attain similar properties, especially in a slender muscle-like form factor. Recently, super-coiled polymer (SCP) actuators have rejuvenated the promise of an artificial muscle. Constructed from commercial nylon fishing line or sewing thread and twisted until coils form, these lightweight actuators have been shown to produce significant mechanical power when thermally cycled. In this paper, we develop a thermomechanical and thermoelectric model of SCP actuators, and examine their controllability. With off-the-shelf conductive sewing thread, we show the ability to produce controlled forces in under 30 ms, exceeding human muscle performance. Finally, we use SCP actuators in a robotic hand to demonstrate their applicability as a low-cost, high performance robotic muscle.

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 novel robotic grasp controller that allows a sensorized parallel jaw gripper to gently pick up and set down unknown objects once a grasp location has been selected. Our approach is inspired by the control scheme that humans employ for such actions, which is known to centrally depend on tactile sensation rather than vision or proprioception. Our controller processes measurements from the gripper's fingertip pressure arrays and hand-mounted accelerometer in real time to generate robotic tactile signals that are designed to mimic human SA-I, FA-I, and FA-II channels. These signals are combined into tactile event cues that drive the transitions between six discrete states in the grasp controller: Close, Load, Lift and Hold, Replace, Unload, and Open. The controller selects an appropriate initial grasping force, detects when an object is slipping from the grasp, increases the grasp force as needed, and judges when to release an object to set it down. We demonstrate the promise of our approach through implementation on the PR2 robotic platform, including grasp testing on a large number of real-world objects.

Telerobotics fundamentally aims to project human skills into a remote, unstructured environment. A key component of human skills is anticipatory modulation of limb impedances in accordance with task requirements and in expectation of events or disturbances. These adjustments occur continually in human interaction strategies, yet are mostly masked in telerobotics by limited bandwidth controllers and fixed impedance hardware. We propose a telerobotic architecture with user-controlled variable impedance and show a single degree of freedom experimental implementation. The master incorporates a grip force sensor as an additional impedance command channel. Since grip force correlates with the user's own impedance, this input provides an intuitive and natural extension to the regular interface. On the slave, a physically variable clutch actuator is used to adjust both low and high frequency impedance. The additional command channel allows the operator to utilize impedance variation strategies to control impact forces and accomplish varying tasks. These natural interaction strategies are simpler and more robust, leading to superior performance and a telerobot which more effectively represents the operator.

For a wide range of telerobotic applications, the slave device needs to be a large, powerful, industrial type robot in order to achieve the desired tasks. Due to the large frictional forces within the gearing of such robots, a force-feedback controller is necessary to precisely control the forces the robot applies when manipulating its environment. This paper proves passivity, and therefore guarantees stability, of a model-based force controller in one degree of freedom (DOF) when subject to viscous and Coulomb friction. The controller is then expanded to muli-DOF systems. In addition to maintaining the robustness of the 1-DOF controller, the multi-DOF controller provides additional freedom to design the closed loop dynamics of the robot. This freedom allows the control designer the ability to shape and optimize how the system feels from a users perspective. The robustness of the controller is experimentally validated and the freedom to modify the closed loop dynamics is explored using a 2-DOF device.

Variable impedance actuators provide the ability to robustly alter interaction impedances mechanically, without bandwidth, power, and stability limitations. They can achieve the physical benefits of an elastic transmission and also recover characteristics of traditionally controlled, inelastic motors. We review previously explored benefits of variable impedance actuators for energetic tasks and impact safety. We then focus on benefits in low frequency force interactions. We examine impedance and force dynamic ranges and illustrate how they are significantly increased by physical impedance variation. Theoretical analysis is confirmed by experiments on a 1-DOF testbed with three impedance settings.

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.

Internal friction, backlash and structural compliance within a robot makes force control a tricky non-colocated control problem. Traditional force controllers are typically tuned for a specific environment and invariably have instability problems when contacting stiffer environments. This paper presents a new force controller designed to use control effort to compensate for energy losses due to friction without modifying the robots underlying passive dynamics. The controller uses a lossless model of the robot's inertia to predict the robot's motion in real time based on the wave-variables flowing between robot and environment. The model motion is used as a desired input for a wave-variable based controller. To calculate the wave variables the controller uses measurements of both the contact force and the acceleration at the end-effector. The resulting controller is compared analytically and experimentally to more traditional controllers.

Impedance type devices are frequently used in haptics due to their excellent rendition of free-space, low cost, and convenience. The spring drive, a recently proposed alternative to the traditional current motor driver for such devices, has been shown to improve their stiffness in rigid contact by moving the haptic coupling from the digital domain to analog circuitry. Unlike the current drive, which operates the motor as a force source, the spring drive converts the motor to a motion source. In this paper we construct a motion-based virtual environment to fully leverage the benefits of operating an impedance device with motion control. This quasi-static environment is connected to a mid-level controller which interfaces with the analog motor drive. A full system analysis and experimental demonstration verify the anticipated performance.

Traditional bilateral teleoperation communicates both motion and force information explicitly between master and slave devices. Any such closed loop architecture trades off performance with potential instability, especially when using force measurements of high inertia slaves contacting stiff environments. More conservatively, open-loop architectures avoid stability issues, transmitting motion commands while allowing any force feedback only via sensory substitution. We propose open-loop bilateral teleoperation as an alternative communicating force information explicitly and restricting motion information to visual feedback. This naturally matches a user's needs, seeing motion and feeling forces. A user study was conducted to compare the novel user interface to three common open loop and bilateral control methods: position control, position control with force feedback, and rate control. The results of this study show that users are able to achieve superior force tracking with little tremor. Position tracking and trial completion time suffered from the lack of direct position connection, but training provides a promising method to restore this performance.

Variable impedance actuation is characterized by the ability to independently set output force and output impedance for a robotic device. Adjusting the output impedance in real-time allows a device to better adapt to a variety of tasks, operate in human-like fashion, and support human safety. This paper focuses on a series clutch actuator based on magnetorheological fluid which allows a fast, electrical change of the impedance while maintaining good force tracking. In particular the mechanical clutch can alter the high-frequency impedance, decoupling the motor inertia and thus reducing impact forces. We present the mechanical clutch design and a control system architecture to automatically adjust the fluid magnetization level and leverage the clutch benefits. Experiments verify torque tracking and impact force reduction both in autonomous and telerobotic operation. The actuator was designed and manufactured in collaboration with the Materials Design Institute at Los Alamos National Laboratory, and is tested in a single degree of freedom demonstration.

Spring drive amplifiers utilize the natural inductive properties of a DC motor to produce stronger position feedback than is achievable with traditional current amplifiers. Impedance-type haptics devices can leverage these amplifiers to render superior contacts with higher contact stiffness. Use of these amplifiers, however, requires the virtual environment to specify motion commands for each motor. This work extends the recently developed 1-DOF integrated approach to multi-DOF applications. It presents a motion controller working with spring drive amplifiers, together producing the maximum achievable isotropic Cartesian stiffness. Isotropy is necessary to guarantee that haptic contact forces are rendered in the correct direction. The system is implemented on a PHANTOM 1.0 haptic device and analytic performance is verified by experiment.

Traditional haptic rendering creates virtual springs using DC motors with current amplifiers and encoder-based position feedback. It is well known that the stiffness of virtual environments is limited by quantization, discretization, and amplifier bandwidth effects. In this paper we propose a novel control architecture that, rather than canceling motor electrical dynamics, uses them to achieve better performances. First we recognize that the inductance L provides a natural sensor-less stiff behavior at high frequencies. Second, electrical resistance R serves as the basis of a wave transform that, performed through an analog circuit, allows to build a more stable interface with virtual environments, achieving robustness to servo delays and discretization. Encoder feedback and digital control loop are required only to provide parametric robustness at low frequencies. A prototype 1-DOF system has been implemented and confirms the promise of this novel paradigm

Humans rely on information-laden high-frequency accelerations in addition to quasi-static forces when interacting with objects via a handheld tool. Telerobotic systems have traditionally struggled to portray such contact transients due to closed-loop bandwidth and stability limitations, leaving remote objects feeling soft and undefined. This work seeks to maximize the user's feel for the environment through the approach of acceleration matching; high-frequency fingertip accelerations are combined with standard low-frequency position feedback without requiring a secondary actuator on the master device. In this method, the natural dynamics of the master are identified offline using frequency-domain techniques, estimating the relationship between commanded motor current and handle acceleration while a user holds the device. During subsequent telerobotic interactions, a high-bandwidth sensor measures accelerations at the slave's end effector, and the real-time controller re-creates these important signals at the master handle by inverting the identified model. The details of this approach are explored herein, and its ability to render hard and rough surfaces is demonstrated on a standard master-slave system. Combining high-frequency acceleration matching with position-error-based feedback of quasi-static forces creates a hybrid signal that closely corresponds to human sensing capabilities, instilling telerobotics with a more realistic sense of remote touch

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

Tapping on surfaces in a typical virtual environment feels like contact with soft foam rather than a hard object. The realism of such interactions can be dramatically improved by superimposing event-based, high-frequency transient forces over traditional position-based feedback. When scaled by impact velocity, hand-tuned pulses and decaying sinusoids produce haptic cues that resemble those experienced during real impacts. Our new method for generating appropriate transients inverts a dynamic model of the haptic device to determine the motor forces required to create prerecorded acceleration profiles at the user's fingertips. After development, the event-based haptic paradigm and the method of acceleration matching were evaluated in a carefully controlled user study. Sixteen individuals blindly tapped on nine virtual and three real samples, rating the degree to which each felt like real wood. Event-based feedback achieved significantly higher realism ratings than the traditional rendering method. The display of transient signals made virtual objects feel similar to a real sample of wood on a foam substrate, while position feedback alone received ratings similar to those of foam. This work provides an important new avenue for increasing the realism of contact in haptic interactions.

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.

Traditionally focused on applications where humans have been kept safely out of reach, the field of robotics is undergoing a major shift as recent developments have brought humans much closer to robots. While device hardware has progressed to fill this new field, the underlying controller and amplifier architecture has remained nearly the same as that developed for industrial robots decades ago. Herein we develop a new, integrated control architecture designed to address the unique requirements of human-interactive robotic devices. This new architecture takes advantage of recent technological advances to produce a single-loop, third order controller integrating both switching control and a fullstate observer. In this paper, we explore the performance on a simplified, first-order system, specifically focusing on the interaction between the controller and the DC motors found in many devices. Experimental testing demonstrates improvements compared to existing PWM and linear amplifiers, with the promise of future improvements for the field of human-interactive robotics.

Providing the user with high-fidelity force feedback has persistently challenged the field of telerobotics. Interaction forces measured at the remote site and displayed to the user cause unintended master device motion. This movement is interpreted as a command for the slave robot and can drive the closed-loop system unstable. This paper builds on a recently proposed approach for achieving stable, high-gain force reflection via cancellation of the master mech anism’s induced motion. Such a strategy hinges on obtaining a good model of the master’s response to force feedback. Herein, we present a thorough modeling approach based on successive isolation of system components, demonstrated on a one-degree-of-freedom testbed. A sixth-order mechanical model, including viscous and Coulomb friction as well as a new method for modeling hysteretic stiffness, describes the testbed’s high-frequency resonant modes. This modeling method’s ability to predict induced master motion should lead to significant improvements in force-reflecting teleoperation via the cancellation approach.

Telerobotics has long struggled to provide realistic force feedback to the user, especially across substantial time delays. Wave variable based controllers provide stable force reflection at frequencies up to a few Hertz for typical communication delays; however, the bandwidth of human perception extends to a thousand Hertz. We address this problem by incorporating a force sensor at the slave end effector and creating an additional feedback path to provide high frequency force information to the user. We build this augmented feedback system on top of a normal wave variable controller, leveraging the separation of power flows provided by the wave variable formalism and building a fundamentally asymmetric controller that better matches the sensory capabilities of the human operator. To further improve the user’s perception of the slave site, we investigate the use of wave filters to compensate for wave reflections without introducing the excessive damping inherent to impedance matching. Both of these improvements are validated experimentally in a simple three degree of freedom teleoperator.

In this paper we propose an integrated motion control architecture based on a full third order motor model. We investigate the advantages and feasibility of controlling a motor using very fast (MHz) switching using digital components in place of traditional amplifiers. A switching controller combines the current and encoder (position) feedback paths into a single loop, and a model based observer estimates the unsensed motor velocity. When compared to second order controllers built with traditional amplifiers, the proposed design promises increased performance, better efficiency, and unproved velocity estimation. Advances in semiconductor technology facilitate the implementation of these fast switches and the required logic using relatively standard components. Preliminary experiments verify good behavior of a DC motor driven up to 5 MHz.

This paper extends earlier results on stable force reflecting teleoperation in the presence of significant time-delays to the case, frequent in practice, where the transmission delays are themselves varying with time in an unpredictable fashion. It shows that stability can be preserved through the systematic use of specially designed wave-variable filters. The resulting performance of the teleoperation system is illustrated in simulations, and is consistent with reasonable expectations on "ideal" behavior. The results may provide a practical tool for implementing force-reflecting teleoperation over the Internet.

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.

Many robotic applications involve interactions with a simple mechanism, such as opening a door or turning a crank. Implementing such tasks using standard controllers may require precise knowledge of the kinematics or result in prohibitively large internal forces. We propose a simple method that learns the shape of the mechanism while in motion and generates little internal forces, in essence following the path of least resistance. The discussion is illustrated experimentally.

Wave variables were originally introduced in the context of time delayed force reflecting teleoperation. Their use provides significant benefits for control, including robustness to arbitrary delays and an inherent hybrid construction, well suited for handling unknown passive environments. They also suggest a new perspective for analysis, presenting information from an alternative viewpoint. In this paper we explore the concept of wave variables in a more general robotic and mechanical setting, leading to alternate control approaches.

We examine the behavior of force reflecting teleoperators which are subjected to large time delays up to several seconds. While stability is guaranteed by the use of passive transmission procedures, such systems can demonstrate particular dynamics which interfere with normal operation. Using the notion of wave variables for the analysis and implementation, and making appropriate design choices, we can construct a telerobot system with consistent and predictable behavior. This follows the design goal of a virtual tool accounting for the implicit limitations imposed by the delay.

The authors explore performance issues linked to the effective implementation of adaptive manipulator controllers. In particular, they discuss computational implementations of the algorithm directly in Cartesian space, the utilization of kinematic redundancies, and applications to adaptive compliant motion control. The development is illustrated experimentally on a four-degree-of-freedom whole-arm articulated manipulator. It is suggested that the range of application of adaptive tracking controllers may extend well beyond adaptation to grasped loads.>