This paper reports a numerical method for modeling underwater vehicle (UV) interactions with the free surface using a finite-dimensional dynamical plant model. Although finite-dimensional plant models of fully submerged UV behavior are well-established, they are unable to model the ubiquitous condition of a UV operating at or near the free surface. We report a Monte Carlo-based hybrid model approach for calculating the buoyancy and righting moment of a partially or fully submerged UV in order to model interactions with the free surface. We also report a preliminary evaluation of the hybrid model in numerical simulations, comparing the hybrid model’s performance to that of a model for fully submerged UVs and to the experimentally observed behavior of an actual vehicle while fully submerged and while interacting with the free surface. The results of this preliminary study suggest that the proposed hybrid approach may offer a simple and practical method for modeling UV behavior when submerged or interacting with the free surface.

We report a novel model-based nullspace adaptive trajectory-tracking control (NS-ATTC) algorithm for fully-actuated 6-degree-of-freedom (DOF) underwater vehicles which estimates unknown plant and actuator model parameters simultaneously. We provide a stability and convergence analysis with proof of asymptotically stable tracking error convergence, as well as a preliminary simulation study demonstrating 6-DOF trajectory tracking. The NS-ATTC algorithm does not require acceleration instrumentation and provides a stable online parameter estimate, enabling robust model-based autonomy.

Teleoperation of robots in space is challenging due to high latency and limited workspace visibility. Previously, the Interactive Planning and Supervised Execution (IPSE) and Augmented Virtuality systems were developed to reduce failure risk. These tools were visualized on a 3D da Vinci surgical console and operated using the da Vinci manipulators or visualized on conventional monitors and operated with a keyboard and mouse. Experimental studies indicated operator preference for the latter. In this work, we develop a 3D virtual reality (VR) interface for IPSE, implemented on a Meta Quest 2 head-mounted display (HMD), and evaluate it against the prior 2D, keyboard-and-mouse-based interface. The results demonstrate improved operator load with the 3D VR interface, with no decrease in task performance, while also providing cost and portability benefits compared to the conventional 2D interface.

This paper addresses the long-standing open problem of observability of mass and inertia plant parameters in the adaptive identification (AID) of second-order nonlinear models of 6 degree-of-freedom rigid-body dynamical systems subject to externally applied forces and moments. Although stable methods for AID of plant parameters for this class of systems, as well numerous approaches to stable model-based direct adaptive trajectory-tracking control of such systems, have been reported, these studies have been unable to prove analytically that the adaptive parameter estimates converge to the true plant parameter values. This paper reports necessary and sufficient conditions for the uniform complete observability (UCO) of 6-DOF plant inertial parameters for a stable adaptive identifier for this class of systems. When the UCO condition is satisfied, the adaptive parameter estimates are shown to converge to the true plant parameter values. To the best of our knowledge this is the first reported proof for this class of systems of UCO of plant parameters and for convergence of adaptive parameter estimates to true parameter values.We also report a numerical simulation study of this AID approach which shows that (a) the UCO condition can be met for fully-actuated plants as well as underactuated plants with the proper choice of control input and (b) convergence of adaptive parameter estimates to the true parameter values. We conjecture that this approach can be extended to include other parameters that appear rigid body plant models including parameters for drag, buoyancy, added mass, bias, and actuators.

We report the development of novel fault detection and isolation (FDI) methods for model-based fault detection (MB-FD) and quotient-space fault isolation (QS-FI). This FDI approach performs MB-FD and QS-FI of single or multiple con-current faults in plants and actuators simultaneously, without a priori knowledge of fault form, type, or dynamics. To detect faults, MB-FD characterizes deviation from nominal behavior using the plant velocity and plant and actuator parameters estimated by nullspace-based adaptive identification. To isolate (i.e. identify) faults, the QS-FI algorithm compares the estimated parameters to a nominal parameter class in progressively decreasing-dimensional quotient spaces of the parameter space. A preliminary simulation study of these proposed FDI methods applied to a three degree-of-freedom uninhabited underwater vehicle plant model shows their ability to detect as well as isolate faults for the cases of both single and multiple simultaneous faults and suggests the generalizability of the MB-FD and QS-FI approaches to any well-defined second-order plant and actuator model whose parameters enter linearly: a broad class of systems which includes aerial vehicles, marine vehicles, spacecraft, and robot arms.

We propose a system for visually monitoring and servoing the cutting of a multi-layer insulation (MLI) blanket that covers the envelope of satellites and spacecraft. The main contributions of this paper are: 1) to propose a model for relating visual features describing the engagement depth of the blade to the force exerted on the MLI blanket by the cutting tool, 2) a blade design and algorithm to reliably detect the engagement depth of the blade inside the MLI, and 3) a servoing mechanism to achieve the desired applied force by monitoring the engagement depth. We present results that validate these contributions by comparing forces estimated from visual feedback to measured forces at the blade. We also demonstrate the robustness of the blade design and vision processing under challenging conditions.

Ground-based teleoperation of robot manipulators for on-orbit servicing of spacecraft represents an example of high-payoff, high-risk operations that are challenging to perform due to high latency communications, with telemetry time delays of several seconds. In these scenarios, confidence of operating without failure is paramount. We report the development of an Interactive Planning and Supervised Execution (IPSE) system that takes advantage of accurate 3D reconstruction of the remote environment to enable operators to plan motions in the virtual world, evaluate and adjust the plan, and then supervise execution with the ability to pause and return to the planning environment at any time. We report the results of an experimental evaluation of a representative on-orbit telerobotic servicing task from NASA's upcoming OSAM-1 mission to refuel a satellite in low earth orbit; specifically, to change the robot tool to acquire the fuel supply line and then to insert it into the satellite fill/drain valve. Results of a pilot study show that the operators preferred, and were more successful with, the IPSE system when compared to a conventional teleoperation implementation.

On-orbit servicing of satellites is complicated by the fact that almost all existing satellites were not designed to be serviced. This creates a number of challenges, one of which is to cut and partially remove the protective thermal blanketing that encases a satellite prior to performing the servicing operation. A human operator on Earth can perform this task telerobotically, but must overcome difficulties presented by the multi-second round-trip telemetry delay between the satellite and the operator and the limited, or even obstructed, views from the available cameras.This paper reports the results of ground-based experiments with trained NASA robot teleoperators to compare our recently-reported augmented virtuality visualization to the conventional camera-based visualization. We also compare the master console of a da Vinci surgical robot to the conventional teleoperation interface. The results show that, for the cutting task, the augmented virtuality visualization can improve operator performance compared to the conventional visualization, but that operators are more proficient with the conventional control interface than with the da Vinci master console.

This paper addresses the problem of underwater robotic vehicle navigation relative to moving or stationary sea ice. A brief review of previously-reported under-ice navigation methods is given, as well as a brief motivation for the use of under-ice robotic vehicles with precision navigation capabilities. We then describe our proposed approach, which employs two or more satellite navigation beacons atop the sea ice along with other precision vehicle and ship mounted navigation sensors to estimate vehicle, ice, and ship states by means of an Extended Kalman Filter. Navigation results for a simulated 7.6 km under ice survey are presented for varying satellite beacon separation. Preliminary analysis suggests that for the simulated sensors, vehicle trajectory, and ice velocities, the proposed method can accurately estimate vehicle position up to 1.2 km from the deployment ship given sufficient satellite beacon separation. Decreased beacon separation results in divergence of the vehicle's position estimate at large standoff distances from the ship. We conclude with suggestions for future improvements.

This paper reports a preliminary study for use of a fully dynamic vehicle process model in combined underwater communication and navigation (cooperative navigation) of underwater vehicles equipped with an acoustic modem, attitude, and depth sensors, but lacking a Doppler velocity log (DVL), and a surface vehicle equipped with an acoustic modem and GPS. We report both simulation and at-sea experimental trials with the JHU Iver3 autonomous underwater vehicle (AUV). The case of underwater vehicle navigation without a DVL is of interest in several use-cases including (a) small and low-cost underwater vehicles for which DVLs may be impractical or infeasible due to their size and cost and (b) for missions in which the vehicle's altitude above the sea floor (or depth beneath overhead ice) exceeds the DVL acoustic bottom-lock range. To the best of our knowledge, all previous studies on cooperative navigation have reported use of a kinematic process model, which works well in the presence of frequent, high-accuracy velocity measurements, as is the case when the vehicle is equipped with a DVL. This preliminary study suggests that the dynamical process model may offer a significant advantage over the purely kinematic model in the absence of frequent, high-accuracy velocity measurements, as is the case when the submerged vehicle is not equipped with a DVL.

This paper reports a method and preliminary evaluation of a novel null-space least-squares parameter identification method for a fully nonlinear second -order 6-degree-of-freedom (DOF) dynamic process model of an underactuated underwater vehicle (UV) for which both the model parameters and the control-input parameters are unknown. This paper further reports the application of the identified plant models in combined underwater communication and navigation (cooperative navigation) of UVs. We report an approach to model identification that simultaneously identifies 6-DOF UV nonlinear plant-model parameters, control-surface parameters, and thruster-model parameters. We believe this approach is suitable for identifying plant model parameters from data obtained in full-scale experimental trials of UVs in controlled motion. The reported approach to nonlinear model identification of UVs is evaluated in simulation studies. The resulting identified UV plant models are further evaluated in simulated cooperative navigation missions of the UV that are representative of high-precision survey missions. To the best of our knowledge, this paper reports the first method to identify 6-DOF UV model parameters, control-surface parameters, and thruster-model parameters simultaneously.

Nine degrees of freedom (DOF) inertial measurement units (IMUs) comprised of three-axis magnetometers, three-axis accelerometers, and three-axis angular rate sensors are commonly used in attitude and heading reference systems (AHRSs). Two classes of AHRSs exist: systems that estimate true-North heading and systems that estimate magnetic-North heading. True-North heading AHRSs require high-end angular rate sensors which are sensitive enough to dynamically estimate Earth-rate (typically fiber-optic and ring-laser gyros), while magnetic-North AHRSs employ gyros that are not sensitive enough to dynamically estimate Earth-rate (i.e. all MEMS gyros). Thus, magnetic-North AHRSs employ magnetometers for estimating heading. This paper will focus on this class of magnetic-North AHRSs. These systems fuse IMU measurements to generate estimates of the instrument's roll, pitch, and magnetic heading. However, their accuracy is limited by sensor measurement bias that is unknown a priori. Hence, accurate sensor bias estimation and compensation is essential for true attitude estimation. This paper reports a novel adaptive sensor bias observer for sensor measurement biases in 9-DOF IMUs. The algorithm requires smaller angular movements of the instrument than other reported sensor bias calibration methods, does not require a priori knowledge of local fields like the local magnetic field or the local gravity vector, and does not require knowledge of the attitude of the instrument. Stability proofs, preliminary simulations, and a full-scale vehicle experimental evaluation are reported.

This paper reports a novel stable adaptive attitude estimator and preliminary simulation results of a true-North gyrocompass system employing the attitude adaptive identifier and a commercially available low-cost inertial measurement unit (IMU) comprising a 3-axis fiber optic gyroscope (FOG) with a 3-axis micro-electro-mechanical systems (MEMS) accelerometer. Optical North-seeking gyrocompass systems typically employ a microprocessor system to sample the low-level raw sensor values for angular-rate and linear-acceleration at a high sampling rate and estimate true-North heading, pitch, and roll. This paper reports the first adaptive attitude estimator on SO (3) which utilizes 3-axis angular-rate sensor data and 3-axis linear acceleration sensor data to estimate the instrument's 3-degrees of freedom (DOF) attitude (roll, pitch, and heading) without using magnetometry of the Earth's magnetic field. A stability proof and preliminary numerical simulation results are reported. The simulation results for a rotating IMU configuration are promising, and further experimental evaluation and extension of the algorithm for the case of a translating IMU configuration typically found on moving robotic vehicles are needed.

Despite the availability of increasingly more robust machine perception and control algorithms, human operators are still needed to directly control robotic systems in extreme environments where there is a high cost of failure. This paper reports a novel architecture for semi-autonomous teleoperation over high-latency telemetry and the results of a 15-subject user study used to evaluate that architecture. The intent-recognition-based traded control (IRTC) architecture recognizes operator intent based on remote scene and task modeling, and automatically trades control to an autonomous reactive subsystem. Each subject participated in one two-hour session during which they controlled a single simulated redundant robotic manipulator with 4000ms of closed-loop latency. Subjects continuously assemble and disassemble a 3D lattice structure with or without IRTC-based assistance. The user study showed that the IRTC system improved operator performance in the simulated multi-object assembly task. All source code for conducting the experiment including the simulation and data processing is available online under a permissive open-source license.

Six-degree of freedom (DOF) inertial measurement units (IMUs) are widely used for attitude estimation. However, such systems' accuracy is limited by the accuracy of calibration of bias, scale factors, and non-orthogonality of sensor measurements. This paper reports a stable adaptive estimator of measurement bias in six-DOF IMUs and preliminary simulation results employing a commercially available IMU comprising a 3-axis fiber optic gyroscope (FOG) with a 3-axis micro-electro-mechanical systems (MEMS) accelerometer. A stability proof of the adaptive estimator and preliminary numerical simulation results are reported. The simulation results for a rotating IMU configuration are promising, and further experimental evaluation and extension of the algorithm for the case of a translating IMU configuration typically found on moving robotic vehicles are needed.

We report the development and a preliminary multi-user evaluation of an assisted teleoperation architecture for assembly tasks over high-latency networks. While such tasks still require human insight, there are often elements of these tasks which can be executed autonomously. Our architecture contextualizes a user's intended actions in a remote scene. It assists the user by performing the intended action more precisely based on the latest local scene model. We report the results of a multi-user study of nine participants to evaluate performance of this approach using a full-3D dynamic robotic simulation in a laboratory environment. The study required users to assemble part of a structure with 200 or 4000 milliseconds of time delay, with or without assistance from the reported system. For each condition, we evaluated performance based both on partial and final task completion times, and we estimated each user's workload with the NASA Task Load Index. The study showed that our architecture has the potential to increase feasibility of the task both with and without large telemetry delay and to enable users to complete elements of the task more rapidly. We also found that the assistance dramatically reduced the users' workload. We provide open-source implementations for all components of our system, which can be adapted to other robotic platforms.

This paper reports a preliminary study of a method for combined underwater communication and navigation of underwater vehicles (cooperative navigation) equipped with an acoustic modem, attitude, and depth sensors, but lacking a Doppler velocity log (DVL), and a surface vehicle equipped with an acoustic modem and GPS. Few previously reported studies have utilized acoustic range rate in addition to acoustic range for the general navigation of underwater vehicles. This paper reports an observation model for range-rate measurements and preliminary anecdotal simulation studies for cooperative navigation of one underwater vehicle client with one surface vehicle server employing both range and range-rate observations to estimate the vehicle states with a delayed-state extended Kalman filter in the absence of DVL velocity observations. The preliminary studies suggest that the addition of range-rate measurements may offer advantages over the case of range-only observations in a limited set of circumstances, such as poor range-observation accuracy. The present study is preliminary, however, and directions for future study are suggested.

This paper reviews the motivation, development, and use of underwater robotic vehicles designed for use in ice-covered waters, with special attention paid to the navigation systems employed for under-ice deployments. The scientific need for routine access under fixed and moving ice by underwater robotic vehicles is briefly reviewed. The challenges of under-ice vehicle navigation are summarized. The paper then reviews all known under-ice robotic vehicles and their associated navigation systems, categorizing them by vehicle type (tethered, untethered, hybrid, and glider) and by the type of ice they were designed for (fixed land-fast sea ice and moving sea ice).

This paper addresses the problem of ice-relative navigation of underwater robotic vehicles for oceanographic missions under moving sea ice. We define the ice-relative navigation problem and report a novel underwater robot vehicle, Nereid-UI, and its navigation system designed for under-ice oceanographic operations in ice-covered seas. The goal of Nereid-UI is to enable deployments in polar ocean regions traditionally considered difficult or impossible to access such as the ice-ocean interface in marginal ice zones, the water column of ice-covered seas, and the water column underlying ice shelves. This paper also reports the navigation results of Nereid-UI's first under-ice sea trials and science operations conducted under moving multi-year sea ice off the ice breaker Polarstern in the Arctic Ocean at 83° N 6° W - about 200 km NE of Greenland.

The ability to refuel satellites on-orbit using teleoperated robots could extend the life of satellite missions, potentially saving time and resources for both industry and space agencies. One critical step in the refueling process is to gain access to the satellite's fueling port by cutting through a seam of tape that adheres two sections of multi-layer insulation (MLI) covering the satellite body. The deformable, delicate, specular nature of the metalized tape used to adhere sections of MLI to one another makes cutting the tape seams a difficult task to perform remotely, a difficulty that is compounded by unavoidable multi-second communications delays. Virtual-fixture-assisted teleoperation can help mitigate some of these issues by constraining the motion of the cutting blade based on a priori knowledge of the task. Adding force control may further assist teleoperators by automatically setting a desired normal cutting force. This paper presents the results of a 20-participant user study for a representative satellite tape-cutting task, showing that force control based on a virtual fixture mapped to the MLI blanket plane can decrease both tape bunching and operator workload.

Direct teleoperation with multisecond time-delayed telemetry between master and slave is challenging for humans to perform. When controlling a holonomic robot with many degrees of freedom, operators may incidentally provide commands in an intended direction without realizing their mistake until receiving feedback several seconds later. For some applications, imposing a virtual nonholonomic constraint (VNHC) on the motion of the end effector can help prevent operators from moving in an unintended direction by reducing the number of controllable degrees of freedom. This paper presents the development of a VNHC for a planar time-delayed telerobotic task, motivated by an on-orbit telerobotic satellite servicing operation. We also describe a nonholonomic virtual fixture (NHVF) that adheres to the VNHC to further reduce the potential for operators to input mistaken commands. We report the results of a pilot study in which teleoperation with a VNHC was found to have comparable task performance to holonomic planar teleoperation, while decreasing operator workload. The NHVF was found to decrease performance slightly, though user feedback indicated that a differently implemented virtual fixture and controller may improve performance.

This paper reports a comparative experimental evaluation of proportional derivative and adaptive model-based control for underwater vehicles. To the best of the authors' knowledge, this is the first such evaluation of model-based adaptive tracking control for underwater vehicles during simultaneous dynamic motion in all 6 degrees-of-freedom. This experimental evaluation revealed the presence of unmodeled thruster dynamics arising during reversals of the vehicle's thrusters, and that the unmodeled thruster dynamics can destabilize parameter adaptation. The three major contributions of this paper are: an experimental analysis of how unmodeled thruster dynamics can destabilize parameter adaptation, a two-step adaptive model-based control algorithm which is robust to the thruster modeling errors present, and a comparative experimental evaluation of adaptive model-based control and proportional derivative control for fully-actuated underwater vehicles preforming simultaneous 6 degree-of-freedom trajectory tracking.

In this paper we present an approach to extending the capabilities of telemanipulation systems by intelligently augmenting a human operator's motion commands based on quantitative three-dimensional scene perception at the remote telemanipulation site. This framework is the first prototype of the Augmented Shared-Control for Efficient, Natural Telemanipulation (ASCENT) System. ASCENT aims to enable new robotic applications in environments where task complexity precludes autonomous execution or where low-bandwidth and/or high-latency communication channels exist between the nearest human operator and the application site. These constraints can constrain the domain of telemanipulation to simple or static environments, reduce the effectiveness of telemanipulation, and even preclude remote intervention entirely. ASCENT is a semi-autonomous framework that increases the speed and accuracy of a human operator's actions via seamless transitions between one-to-one teleoperation and autonomous interventions. We report the promising results of a pilot study validating ASCENT in a transatlantic telemanipulation experiment between The Johns Hopkins University in Baltimore, MD, USA and the German Aerospace Center (DLR) in Oberpfaffenhofen, Germany. In these experiments, we observed average telemetry delays of 200ms, and average video delays of 2s with peaks of up to 6s for all data. We also observed 75% frame loss for video streams due to bandwidth limits, giving 4fps video.

This paper addresses the modeling and experimental identification of six degree-of-freedom (6-DOF) coupled nonlinear second order plant models for low-speed, fully-actuated, and neutrally buoyant open-frame underwater vehicles. We report a comparative experimental evaluation of six different candidate plant models whose unknown plant parameters are estimated from data obtained in free-motion vehicle trials. We report an experimental evaluation of the performance of each of the six different 6-DOF coupled non-linear finite-dimensional plant models for underwater vehicles estimated by total least squares (TLS) by comparing the mean absolute error between the experimentally observed vehicle velocities and the velocities obtained by a numerical simulation of the experimentally identified plant models. We also report a cross-validation which evaluates the ability of a plant model to accurately reproduce observed plant velocities for experimental trials differing from the trial from which the plant model parameters were estimated. We conclude that plant models including fully parametrized coupled quadratic drag terms perform best overall in cross-validation. This study has the following contributions: It is the first reported experimental 6-DOF fully-coupled plant model identification and cross-validation of low-speed, fully-actuated, and neutrally buoyant underwater vehicles; it is the first experimental 6-DOF plant model identification for this class of underwater vehicles during free-flight experiments; and it is the first reported use of TLS to perform 6-DOF experimental plant model identification of an underwater vehicle.

This paper reports a comparative experimental evaluation of one non-model-based proportional derivative (PD) 6 degree-of-freedom (6-DOF) controller and one model-based 6-DOF controller designed to enable fully actuated underwater vehicles to perform 6-DOF set-point regulation and trajectory tracking. We show analytically the non-model-based PD controller is capable of performing locally asymptotically stable set-point regulation. We show analytically the model-based controller is capable of locally asymptotically stable 6-DOF trajectory tracking. Experimental results with the Johns Hopkins University remotely operated vehicle (JHU ROV) show the model-based controller's mean absolute position and velocity tracking error is significantly smaller than the non-model-based PD controller for coupled maneuvers.

This paper reports a novel adaptive identifier for underwater vehicles as well as its local stability proof and comparative experimental evaluation. The adaptive identification algorithm estimates the hydrodynamic mass, quadratic drag, gravitational force, and buoyancy parameters of a second-order rigid-body plant under the influence of actuator forces and torques. Adaptive model identification methods do not require instrumentation of vehicle acceleration as required of other standard methods, such as conventional least squares. Previous adaptive model identification methods have focused on model-based adaptive tracking controllers however these approaches are not applicable when the plant is either uncontrolled, under open-loop control, or using any control law other than a specific adaptive tracking controller; the adaptive identifier reported herein does not require reference trajectory-tracking, and thus is applicable in these commonly occurring cases. An experimental comparison of adaptive identification and conventional least squares parameter identification is reported. The adaptively identified model is shown to be similar to the least squares identified model.

Doppler navigation is one of the most widely practiced navigation methods for underwater robotic vehicles, yet its accuracy is limited both by sensor calibration and by the accuracy of the vehicle's attitude measurement. This paper reports a method to improve the dynamic attitude estimation for underwater vehicles employing Doppler sonar and low-cost micro-electro-mechanical systems (MEMS) attitude and heading reference systems (AHRSs). Our approach employs three-axis velocity measurements from a Doppler velocity log (DVL) to estimate acceleration to provide corrections to the AHRS accelerometer signals that improve the dynamic estimates of vehicle roll and pitch. We report an implementation of this approach with a nonlinear complementary filter to estimate the vehicle attitude dynamically. We report the results of an in-water comparative experimental evaluation of the proposed and previously reported attitude estimation methods using low-cost MEMS AHRSs. We also report an experimental evaluation of the effect of the attitude estimation accuracy on the spatial accuracy of three-dimensional Doppler navigation of underwater vehicles.

Our goal is to develop new methods for telerobotic on-orbit servicing of spacecraft under ground-based supervisory control of human operators to perform tasks in the presence of uncertainty and telemetry time delay of several seconds. We propose a new delay tolerant control methodology, using virtual fixtures, hybrid position/force control, task frame formalism, and environment modeling, that is robust to modeling and registration errors. The task model is represented by graphical primitives and virtual fixtures on the teleoperation master and by a hybrid position/force controller on the slave robot. The virtual fixtures guide the operator through a model-based simulation of the task, and the goal of the slave controller is to reproduce this action (after a few seconds of delay) or, if measurements are not consistent with the models, to stop motion and alert the operator. This approach is suitable for tasks in unstructured environments, such as servicing of existing on-orbit spacecraft that were not designed for servicing. We introduce the overall control concept, its main components, and an example application in which the remote slave robot cuts the tape that secures a flap of multi-layer insulation over the access panel of a satellite mockup.

We report a decentralized extended information filter (DEIF) algorithm designed for single-beacon cooperative acoustic navigation of one or more client underwater vehicles. In single-beacon cooperative acoustic navigation, ranges and state information from a single reference source (the server) are used to improve localization and navigation of an underwater vehicle (the client). The ranges and state information are obtained using underwater acoustic modems and a synchronous-clock time-of-flight paradigm. Apart from the server's acoustic data broadcasts, the client has no access to the server's position or sensor measurements. We show that at the instance of each range measurement update, the DEIF algorithm yields identical results for the current vehicle state estimate as the corresponding centralized extended information filter (CEIF), which fully tracks the joint probability distribution between the server and client. We compare the state estimation results of the DEIF algorithm with that of a CEIF and three other filters reported in the literature. The evaluation is performed using both simulated data and an experimental dataset comprised of one surface craft and two autonomous underwater vehicles.

This paper reports the design requirements, practical challenges, and a preliminary design for a magnetic resonance imaging (MRI) guided, three degree-of-freedom (DOF) transrectal prostate intervention robot. We show the operational space constraints imposed by patient anatomy when performing transrectal prostate procedures in a magnetic resonance (MR) scanner bore, as determined by analyzing data from 12 patient procedures with a device. We also describe practical challenges arising in designing a compact actuated MR compatible needle placement robot for MRI-guided transrectal needle intervention in the prostate. We present a preliminary design which aims to improve upon previous un-actuated and partially-actuated devices with the addition of an actuated needle insertion module. Such an enhancement enables needle driving to take place inside the MR scanner bore and thereby may reduce the overall procedure time - thus improving patient comfort and reducing likelyhood of needle targeting errors resulting from patient motion. We show that it is feasible to add such actuation while reducing the footprint of the device in accordance with the anatomical and MR scanner constraints and practical design requirements.

We report a comparative performance evaluation, using at-sea field data, of recently reported methods for the problem of in-situ calibration of the alignment rotation matrix between Doppler sonar velocity sensors and inertial navigation sensors arising in the navigation of underwater vehicles. Most previously reported solutions to this alignment calibration problem require the use of absolute navigation fixes of the underwater vehicle, thus requiring additional navigation sensors and/or beacons to be located externally and apart from the underwater vehicle. We briefly review four recently reported alignment calibration methods employing only internal vehicle navigation sensors for velocity, acceleration, attitude, and depth. We report the results of comparative analysis of the performance of these recently reported methods and a previously reported method with navigation data from deep-water survey missions of the Sentry autonomous underwater vehicle conducted in March, 2011 in the Kermadec Arc in the Southern Pacific Ocean. The results reveal consistent differences in performance of the various methods when analyzed on navigation data from several different vehicle dives.

This paper presents an augmented reality framework, implemented on the master console of a modified da Vinci® surgical robot, that enables the operator to design and implement assistive virtual fixtures during teleoperation. Our specific goal is to facilitate teleoperation with large time delays, such as the delay of several seconds that occurs with ground-based control of robotic systems in earth orbit. The virtual fixtures give immediate visual feedback and motion guidance to the operator, while the remote slave performs motions consistent with those constraints. This approach is suitable for tasks in unstructured environments, such as servicing of existing on-orbit spacecraft that were not designed for servicing. We conducted a pilot study by teleoperating a remote slave robot for a thermal barrier blanket cutting task using virtual fixtures with and without time delay. The results show that virtual fixtures reduce the time required to complete the task while also eliminating significant manipulation errors, such as tearing the blanket. The improvement in performance is especially dramatic when a simulated time delay (4 seconds) is introduced.

Recent studies of neuromotor control have shown that humans modulate the impedance of their arms for different tasks, motivating the development of a prosthetic arm with user-selectable impedance characteristics. While impedance control has been extensively studied in robotics, prosthetic arms present a unique combination of human and robotic control, in which human capabilities and preferences play an important role. To understand the desirable impedance characteristics of prosthetic arms, we studied human control of a one-degree of-freedom virtual prosthetic limb with variable stiffness and damping in tasks involving (1) force minimization and (2) trajectory tracking. Subjects performed best with different patterns of impedance modulation depending on task goals and available feedback, suggesting that the ability to modulate the impedance of a prosthetic limb may be beneficial to the wearer. The results of this study inform the future design of prosthetic limbs in which the wearer can vary limb impedance to improve performance in a variety of manipulation tasks.

Recently several systems for magnetic resonance image (MRI) guided needle placement in the prostate have been reported. In comparison to conventional ultrasound-guided needle placement in the prostate, these MRI-guided systems promise improved targeting accuracy for prostate intervention procedures including biopsy, fiducial marker insertion, injection and focal therapy. In MRI-guided needle interventions, after a needle is inserted, the needle position is often confirmed with a volumetric MRI scan. Commonly used titanium needles are not directly visible in an MR image, but they generate a susceptibility artifact in the immediate neighborhood of the needle. This paper reports the results of a quantitative study of the relation between the true position of titanium biopsy needle and the corresponding needle artifact position in MR images. The titanium needle artifact was found to be displaced 0.38 mm and 0.32 mm shift in scanner's frequency and phase encoding direction, respectively. The artifact at the tip of the titanium needle was observed to bend toward the scanner's B(0) magnetic field direction.

This paper reports the results of an in-water laboratory evaluation of the state estimation accuracy of a commercially available inertial navigation system (INS), and the effect of variations in the accuracy and the update rate of INS correction data on the accuracy of the INS state estimate. The navigation accuracy of the INS state estimate is evaluated by comparison with navigation data from a highly accurate navigation system available in our laboratory that employs high-frequency acoustic time-of-flight ranging, precision pressure depth sensing, bottom-lock Doppler sonar, and a true-North-seeking gyrocompass that is integral to the INS.

This paper reports the development and in-water experimental evaluation of two new methods for the problem of in-situ calibration of the alignment rotation matrix between Doppler sonar velocity sensors and gyrocompass attitude sensors arising in the navigation of underwater vehicles. Most previously reported solutions to this alignment calibration problem require the use of absolute navigation fixes of the underwater vehicle, thus requiring additional navigation sensors and/or beacons to be located externally and apart from the underwater vehicle. We report two alignment calibration methods employing only internal vehicle navigation sensors for velocity, acceleration, attitude, and depth. Results from laboratory experiments comparing these methods to previously reported techniques indicate satisfactory performance of the proposed methods.

This paper reports the design, development, and magnetic resonance imaging (MRI) compatibility evaluation of an actuated transrectal prostate robot for MRI-guided intervention. The robot employs an actuated needle guide with the goal of reducing interventional procedure times and increasing needle placement accuracy. The design of the robot, employing piezo-ceramic-motor actuated needle guide positioning and manual needle insertion, is reported. Results of a MRI compatibility study show no reduction of MRI image signal-to-noise-ratio (SNR) with the motors disabled and a 40% to 60% reduction in SNR with the motors enabled. The addition of radio-frequency (RF) shielding is shown to significantly reduce image SNR degradation due to the presence of the robotic device.

This paper reports an overview of the navigation and control system design for the new Nereus hybrid underwater robotic vehicle (HROV). Vehicle performance during its first sea trials in November 2007 near Hawaii, and in May and June 2009 in the Challenger Deep of the Mariana Trench is reported. During the latter expedition, the vehicle successfully performed scientific observation and sampling operations at depths exceeding 10,903 m. The Nereus underwater vehicle is designed to perform scientific survey and sampling to the full depth of the ocean - significantly deeper than the depth capability of all other present-day operational vehicles. For comparison, the second deepest underwater vehicle currently operational worldwide can dive to 7,000 m maximum depth. Nereus operates in two different modes. For broad-area survey, the vehicle can operate untethered as an autonomous underwater vehicle (AUV) capable of exploring and mapping the sea floor with sonars and cameras. Nereus can be converted at sea to become a tethered remotely operated vehicle (ROV) to enable close-up imaging and sampling. The ROV configuration incorporates a lightweight fiber-optic tether (for high-bandwidth, real-time video and data telemetry to the surface), an electro-hydraulic manipulator arm, and sampling instruments. The Nereus vehicle is designed to render all parts of the Earth's seafloor accessible to oceanographic science.

Manual palpation of tissue and organs during a surgical procedure provides clinicians with valuable information for diagnosis and surgical planning. In present-day robotassisted minimally invasive surgery systems, lack of perceptible haptic feedback makes it challenging to detect a tumor in an organ or a calcified artery in heart tissue. This study presents an automated tissue property estimation method and a real-time graphical overlay that allow an operator to discriminate hard and soft tissues. We first evaluate experimentally the properties of an artificial tissue and compare seven possible mathematical tissue models. Self-validation as well as cross-validation confirm that the Hunt-Crossley model best describes the experimentally observed phantom tissue properties and is suitable for our purpose. Second, we present the development of a system in which the phantom tissue is palpated using a teleoperated surgical robot, and the stiffness of the Hunt-Crossly model is estimated in real time by recursive least squares. A real-time visual overlay representing tissue stiffness is created using a hue-saturation-luminance representation on a semi-transparent disc at the tissue surface. Hue depicts the stiffness at a palpated point and saturation is calculated based on distance from the point. A simple interpolation technique creates a continuous stiffness color map. In an experiment, the graphical overlay successfully shows the location of an artificial calcified artery hidden in phantom tissue.

This paper reports the development and experimental evaluation of a novel navigation system for underwater vehicles that employs Doppler sonar, synchronous clocks, and acoustic modems to achieve simultaneous acoustic communication and navigation. The system reported herein, which is employed to renavigate the vehicle in post-processing, forms the basis for a vehicle-based real-time navigation system. Existing high-precision absolute navigation techniques for underwater vehicles are impractical over long length scales and lack scalability for simultaneously navigating multiple vehicles. The navigation method reported in this paper relies on a single moving reference beacon, eliminating the requirement for the underwater vehicle to remain in a bounded navigable area. The use of underwater modems and synchronous clocks enables range measurements based on one-way time-of-flight information from acoustic data packet broadcasts. The acoustic data packets are broadcast from the single, moving reference beacon and can be received simultaneously by multiple vehicles within acoustic range. We report experimental results from the first deep-water evaluation of this method using data collected from an autonomous underwater vehicle (AUV) survey carried out in 4000 m of water on the southern Mid-Atlantic Ridge. We report a comparative experimental evaluation of the navigation fixes provided by the proposed synchronous acoustic navigation system in comparison to navigation fixes obtained by an independent conventional long baseline acoustic navigation system.

This paper reports recent experimental results in the development and deployment of a synchronous-clock acoustic navigation system suitable for the simultaneous navigation of multiple underwater vehicles. The goal of this work is to enable the task of navigating multiple autonomous underwater vehicles (AUVs) over length scales of O(100 km), while maintaining error tolerances commensurate with conventional long-baseline transponder-based navigation systems (i.e., O(1 m)), but without the requisite need for deploying, calibrating, and recovering seafloor anchored acoustic transponders. Our navigation system is comprised of an acoustic modem-based communication/navigation system that allows for onboard navigational data to be broadcast as a data packet by a source node, and for all passively receiving nodes to be able to decode the data packet to obtain a one-way travel time pseudo-range measurement and ephemeris data. We present results for two different field experiments using a two-node configuration consisting of a global positioning system (GPS) equipped surface ship acting as a global navigation aid to a Doppler-aided AUV. In each experiment, vehicle position was independently corroborated by other standard navigation means. Initial results for a maximum-likelihood sensor fusion framework are reported.

This paper reports the analytical development and preliminary experimental evaluation of a class of exact nonlinear full state model-based observers for underwater vehicle navigation. This class of observers exploits exact knowledge of the vehicle's nonlinear dynamics, the forces and moments acting on the vehicle, and disparate position and velocity measurements. The reported observer is novel in that it estimates the full state of the vehicle and employs Lyapunov techniques to show stability. The performance of the observer is evaluated using data from single degree-of-freedom experiments with a laboratory remotely operated vehicle. High-precision measurements from a 300kHz long baseline (LBL) acoustic positioning systems serve as the basis for evaluating the performance of the observer. Error in the observer position estimate possesses a significantly lower standard deviation than measurements from 12kHz LBL systems alone. The performance of the observer is compared to the extended Kalman filter (EKF) and the error in the position estimates of these two estimators found to be comparable. These experiments are, to the best of our knowledge, the first report of the experimental implementation of exact nonlinear dynamic model-based observers and their comparison to EKFs for underwater vehicle navigation.

This paper reports a novel stable adaptive identifier on the group of rigid-body rotations, and its application to a sensor-calibration problem arising in underwater vehicle navigation. The problem addressed is the identification of an unknown rigid-body rotation map from input-output data. General least-squares (LS) and adaptive identification techniques are commonly employed to identify general linear maps from input-output data, but do not guarantee that the resulting identified map is a rigid-body rotation. At present, an LS singular value decomposition approach is the standard method for identification constrained to the group of rigid-body rotations. This paper reports the first exact adaptive identifier on the group of rigid-body rotations, together with a proof of asymptotic stability. Techniques for navigating underwater vehicles are reviewed, and the Doppler-alignment calibration problem is posed. The reported adaptive identifier is employed to solve this problem, and performance of this adaptive identifier is evaluated on both laboratory and field experimental data. The results reported herein compare favorably with results obtained via previously reported LS techniques. The methodology reported herein may be of broader interest because of its applicability to more general problems in the identification, dynamics, and control on the group of rigid-body motions

This paper reports a novel hybrid method of tracking the position and orientation of robotic medical instruments within the imaging volume of a magnetic resonance imaging (MRI) system. The method utilizes two complementary measurement techniques: passive MRI fiducial markers and MRI compatible joint encoding. This paper reports an experimental evaluation of the tracking accuracy of this system. The accuracy of this system compares favorably to that of a previously reported active tracking system. Moreover, the hybrid system is quickly and easily deployed on different MRI scanner systems

This paper reports a novel stable adaptive identifier on the group of rigid body rotations, and its application to a sensor calibration problem arising in underwater vehicle navigation. The problem addressed is the identification of a rigid-body rotation map from input-output data. General least-square and adaptive identification techniques are commonly employed to identify general linear maps from input-output data, but do not guarantee that the resulting identified map is a rigid body rotation. At present, a least-square singular value decomposition approach is the standard method for identification constrained to the group of rigid body rotations. This paper reports the first exact adaptive identifier on the group of rigid body rotations, together with a proof of stability. The performance of this adaptive identifier is evaluated on actual experimental data and found to compare favorably with results obtained via previously reported least-squares techniques. The methodology reported herein is of broader interest because of its applicability to general problems in the identification, dynamics, and control on the group of rigid body motions.

This paper reports the development of a real-time human-computer interface (HCI) system that enables a human operator to more effectively utilize the large volume of quantitative data (navigation, scientific, and vehicle status) generated in real-time by the sensor suites of underwater ro botic vehicles. The system provides interactive 3-D graphical interfaces that display, under user control, the quantitative spatial and temporal sensor data presently available to pilots and users only as two-dimensional plots and numerical dis plays. The system can presently display real-time bathymetric renderings of the sea-floor based upon vehicle navigation and sonar sensor data; vehicle trajectory data; a variety of scalar valued sensor data; and geo-referenced targets and waypoints. We report the accuracy of the real-time navigation and bathymetric sonar data processing by comparing the real-time sonar bathymetry of our test tank floor to a high-resolution laser scan of the same tank floor. The real-time sonar bathymetry is shown to compare favorably to the laser scan data

This work reports a novel remotely actuated manipulator for transrectal prostate imaging and intervention, designed for use in a standard cylindrical, high-field magnetic resonance imaging (MRI) scanner. The device provides three-dimensional MRI guided needle placement with millimeter accuracy under physician control. Candidate procedures enabled by this device include MRI guided needle biopsy, fiducial marker placements, and therapy delivery. Its compact size allows for use in both standard cylindrical and open configuration MRI scanners. Preliminary in-vivo canine experiments are reported.

This paper reports the development of a new miniature force sensor designed to measure contact forces at the tip of a microsurgical instrument in three dimensions, and its application to scaled force feedback using a cooperatively manipulated microsurgical assistant robot. The principal features of the sensor are its small size of 12.5 mm in diameter and 15 mm in height, a novel configuration of flexure beams and strain gauges in order to measure forces isotropically at the instrument tip 40 mm from the sensor body, and sub-mN three-axis force-sensing resolution.

Addresses a practical problem arising in the calibration of bottom-lock Doppler sonar for the navigation of underwater robot vehicles. Employing a least-squares method, the rotational alignment offset between a bottom-lock Doppler sonar and a north-seeking gyroscope can be experimentally determined using sensors commonly deployed with a vehicle in the field. It requires sensor values from the vehicle's Doppler sonar and 3-axis gyroscope, and absolute vehicle position fixes from a long-baseline or short-baseline acoustic navigation system. The performance of the calibration method is evaluated with simulated Doppler data possessing measurement noise typical of that found in actual in-water vehicle sensor data.

This paper reports an experimental investigation of the effect of two specific errors on a class of model based controllers for the low-speed maneuvering of fully actuated underwater vehicles. First, we review previously reported studies and a commonly accepted simplified plant model that has been experimentally validated for this class of vehicles. Second, we review a family of associated model-based nonlinear controllers, both fixed and adaptive, for trajectory tracking, as well as the commonly employed proportional-derivative (PD) controller. Third, we report an experimental evaluation of the performance of this entire family of controllers in the presence of two commonplace modelling errors: plant parameter mismatch, and thruster saturation. In the presence of plant model parameter errors, the fixed model based controllers often perform worse than PD control, and the adaptive controllers "learn" the correct parameters to provide asymptotically superior performance. In the presence of unmodelled thruster saturation, the adaptive controllers performs worst, and the model-based controllers perform no worse than PD.

This paper addresses the development, implementation, and evaluation of a novel application of robot force control called position based force scaling. We report the first results in the implementation of asymptotically exact force scaling, as well as the first results in on-line environment compliance adaptation while performing the task of force scaling. One previously reported and two new (one adaptive and one non-adaptive) force scaling algorithms are reviewed. Extensive comparative experiments quantify the performance of all three algorithms and show that the new adaptive force scaling algorithm significantly outperforms both its non-adaptive counterpart as well as the previously reported set-point-regulator based force scaling algorithm over a wide range of user applied input force trajectories and force scale factors.

This paper addresses the problem of achieving exact dynamic force control with manipulators possessing low-level position and/or velocity controllers typically employed in industrial robot arms. Previously reported approaches and experimental results are reviewed. A new adaptive force control algorithm for velocity/position controlled robot arms in contact with surfaces of unknown linear compliance is reported. The controller provably guarantees global asymptotic convergence of force trajectory tracking errors to zero when the robot is under exact or asymptotically exact inner loop velocity control. An additional result which guarantees arbitrarily small force errors for bounded inner loop velocity tracking errors is presented. Comparative experiments show the new adaptive velocity (position) based controller and its nonadaptive counterpart to provide performance superior to that of previously reported position-based force controllers.

The finite-dimensional nonlinear thruster models (Bachmayer et al. (2000)) employing empirically determined lift/drag curves have been shown to accurately model both the transient and steady state response of marine thrusters. This paper first reports on the development of an asymptotically stable open-loop thrust tracking controller that exploits this new nonlinear thruster model. To the best of our knowledge, this is the first stable model based thrust control law reported for this class of marine thrusters.

This paper addresses the problem of achieving exact dynamic force control with manipulators possessing the low level position and/or velocity controllers typically employed in industrial robot arms. Previously reported approaches and experimental results are reviewed. A new adaptive force control algorithm for velocity/position controlled robot arms in contact with surfaces of unknown linear compliance is reported. The controller provably guarantees global asymptotic convergence of force trajectory tracking errors to zero when the robot is under exact or asymptotically exact inner loop velocity control. An additional result which guarantees arbitrarily small force errors for bounded inner loop velocity tracking errors is presented. Comparative experiments show the new adaptive velocity (position) based controller and its non-adaptive counterpart to provide performance superior to that of previously reported position based force controllers.

This paper presents a stable online adaptive identification technique for the identification of finite-dimensional dynamical models of dynamically positioned underwater robotic vehicles. A direct comparison of this method to a conventional, off-line, least-squares method is presented. Based on experimental data obtained using the JHU remotely operated vehicle, both methods are employed to develop decoupled, single degree of freedom dynamical plant models. Performance of the resulting dynamical models is compared to the logged experimental motion of the actual vehicle.

Reports preliminary experiments with a robot system designed to cooperatively extend a human's ability to perform fine manipulation tasks requiring human judgement, sensory integration and hand-eye coordination. A completed steady-hand robot is reported. A stable force control law is reviewed. Preliminary experiments validate theoretical predictions of stable one-dimensional control of tool-tip forces in contact with both linearly and nonlinearly compliant objects. Preliminary feasibility experiments demonstrate stable one-dimensional robotic augmentation and "force scaling" of a human operator's tactile input.

This paper reports the mechanical design, structural analysis, and experimental verification of a new high performance semi-direct drive robot arm. A design optimization methodology employing finite element analysis (FEA) is reviewed, and a resulting arm design is reported. FEA simulations of the final design predict high structural vibration frequencies throughout the arm workspace. Extensive structural vibration experiments with the completed manipulator confirm the predicted structural vibration characteristics throughout the arm workspace.

In this paper we present a methodology for high resolution acoustic bathymetric mapping from a robotic underwater vehicle. Based on data obtained from navigation, attitude, and bathymetric sensors we show that precise calibration of attitude sensors is critical to obtaining high precision bathymetric surveys. We present an in-situ method for precision attitude sensor calibration based upon specific vehicle maneuvers. This method is demonstrated using data from an acoustic bathymetric survey of an archaeological site in the Mediterranean conducted by the authors with the Jason remotely operated vehicle.

The development of two new classes of commercial underwater robotic vehicles-deep diving work-class remotely operated vehicles and survey-class autonomous vehicles-is being driven by the needs of deep water oil production and deep ocean telecommunication cable operations. The paper presents a survey of the present state and future directions of commercial underwater robotics, examines principal technical challenges, and outlines new enabling technologies for commercial underwater robotic vehicles.

New low-cost commercially available bottom-lock Doppler sonars can augment or replace the acoustic time-of-flight navigation systems commonly employed for three-dimensional underwater robot vehicle navigation. The paper first reviews conventional techniques for underwater vehicle navigation, and describes a Doppler-based navigation system developed by the authors. Second, we identify principal limitations to the bottom-track precision of Doppler based navigation systems. Third, we analyze the effect of heading-sensor errors on Doppler bottom-track precision. Experimental results compare bottom-track error resulting from a Doppler navigation using low-precision magnetic heading sensor with bottom-track error resulting from a high-precision a ring-laser gyroscope. The experiments were conducted during a field deployment in which the new robot navigation system enabled precision acoustic and optical survey as well as minimally invasive object recovery from hydrothermal vents in the Guaymas Basin, Gulf of California at 27/spl deg/N 111.5/spl deg/W, at 2000 m depth.

This paper reports the structural design of a new high-performance robot arm. Design objectives for the new arm include large (1-2m) workspace, low weight, 5 kg payload capacity, high stiffness, high structural vibration frequencies, precise joint-level torque control, a total of three degrees-of-freedom, and mechanical simplicity. A comparative analysis is reported for four very different two degree-of-freedom linkage candidates using the finite element method.

This paper reports comparative experiments with a new model-based adaptive force control algorithm for robot arms. This controller provides simultaneous position and force trajectory tracking of a robot arm whose tool tip is in point contact with a smooth rigid surface. The algorithm is provably stable with respect to the commonly accepted rigid-body nonlinear dynamical model for robot arms. Comparative experiments show the new adaptive model-based controller to provide performance superior to that of both nonmodel-based controllers and nonadaptive controllers over a wide range of operating conditions.

This paper presents experiments with a new algorithm for the unsteady (transient) thrust control bladed-propeller marine thrusters. Comparative experiments over a wide range of unsteady operating conditions with three different thrust control algorithms demonstrate the model-based control algorithm to offer transient thrust-control performance superior to that of its nonmodel-based counterpart. The use of improved unsteady thrust control on underwater vehicles promises to reduce the well-documented limit-cycling of dynamically-positioned marine vehicle position during low-speed manuevering.

This paper reports comparative experiments with a provably correct model-based adaptive robot control algorithm for simultaneous position and force trajectory tracking of a robot arm whose gripper is in point contact with a smooth surface. The experiments show the new adaptive model-based offers performance superior to that of its non-model-based counterpart over a wide variety of operating conditions.

A learning control scheme for robot manipulators whose endpoint is moving under geometrical constraints on a surface is proposed. In this scheme, the input torque command is composed of two signals updated separately at every trial by different laws. One is updated by the angular velocity error vector which is projected to the tangent plane of the constraint surface in joint space. The other is updated by the magnitude of contact force error at the endpoint. A theoretical proof of the uniform boundedness of velocity and position trajectories and the convergence of these to their desired ones is given, together with the convergence of force errors. Computer simulation remits by using a 3-DOF manipulator are presented to demonstrate the effectiveness of the proposed method.>

The design, implementation, and deployment of a new computer system for closed loop control of the JASON underwater robot at full ocean depth is described. Several design principles for the rapid development of large scale robot control systems are articulated and illustrated with examples from the JASON system. The use of subsystems with differing computer architectures permit effective matching of capability to function. A two-part system design partitions safety-critical from nonsafety-critical subsystems for cost-effective implementation and enhancement. A machine-independent message-passing communication protocol, JasonTalk, enables integration of disparate computer architectures into a unified system. Results from a recent JASON deployment in the Pacific Ocean are discussed.

A model-based adaptive controller and proof of its global asymptotic stability with respect to the standard rigid-body model of robot-arm dynamics are presented. Experimental data from a study of one new and several established globally asymptotically stable adaptive controllers on two very different robot arms: (1) demonstrate the superior tracking performance afforded by the model-based algorithms over conventional PD control; (2) demonstrate and compare the superior performance of adaptive model-based algorithms over their nonadaptive counterparts; (3) reconcile several previous contrasting empirical studies; and (4) examine contexts that compromise their advantage.>

An approach to the problem of controlling automated assembly tasks using artificial potential functions is described. The authors address the automatic generation of actuator commands for a robot manipulator that result in the motion of a collection of rigid-body parts from disassembled initial configurations to an assembled final configuration. A simple class of tasks, 2D sphere assemblies, is examined. A primitive constructive theory for the control of this class of tasks is presented. Preliminary computer simulations demonstrate that the proposed approach may provide surprisingly good performance.>

An adaptive controller is discussed and a proof of its global asymptotic stability with respect to the standard rigid body model of robot arm dynamics is presented. Experimental data from a study of this and other globally asymptotically stable adaptive controllers on two very different robot arms are used to reconcile several previous contrasting empirical studies, demonstrate and compare their superior tracking performance, and examine contexts that compromise their advantage.>

An approach to the problem of automated assembly planning and control using artificial potential functions is described. A simple class of tasks, 2D sphere assemblies, is examined. A constructive theory for the planning and control of this class of tasks is presented. Computer simulations demonstrate that the approach may provide surprisingly good performance.>

The performance of real-time distributed control systems is shown to depend critically on both communication and computation costs. A taxonomy for distributed system performance measurement is introduced. A roughly accurate method of performance prediction for simple systems is presented. Experimental results demonstrate the effects of communication protocols on real-world system performance.>