The development of autonomous or semi-autonomous surgical robots stands to improve the performance of existing teleoperated equipment, but requires fine hand-eye calibration between the free-moving endoscopic camera and patient-side manipulator arms (PSMs). A novel method of solving this problem for the da Vinci® robotic surgical system and kinematically similar systems is presented. First, a series of image-processing and optical-tracking operations are performed to compute the coordinate transformation between the endoscopic camera view frame and an optical-tracking marker permanently affixed to the camera body. Then, the kinematic properties of the PSM are exploited to compute the coordinate transformation between the kinematic base frame of the PSM and an optical marker permanently affixed thereto. Using these transformations, it is then possible to compute the spatial relationship between the PSM and the endoscopic camera using only one tracker snapshot of the two markers. The effectiveness of this calibration is demonstrated by successfully guiding the PSM end effector to points of interest identified through the camera. Additional tests on a surgical task, namely grasping a surgical needle, are also performed to validate the proposed method. The resulting visually-guided robot positioning accuracy is better than the earlier hand-eye calibration results reported in the literature for the da Vinci® system, while supporting intraoperative update of the calibration and requiring only devices that are already commonly used in the surgical environment.

This paper presents algorithms for three-dimensional tracking of surgical needles using the stereo endoscopic camera images obtained from the da Vinci® Surgical Robotic System. The proposed method employs Bayesian state estimation, computer vision techniques, and robot kinematics. A virtual needle rendering procedure is implemented to create simulated images of the surgical needle under the da Vinci ® robot endoscope, which makes it possible to measure the similarity between the rendered needle image and the real needle. A particle filter algorithm using the mentioned techniques is then used for tracking the surgical needle. The performance of the tracking is experimentally evaluated using an actual da Vinci® surgical robotic system and quantitatively validated in a ROS/Gazebo simulation thereof.

In order to realize many of the potential benefits associated with robotically assisted minimally invasive surgery, the robot must be more than a remote controlled device. Currently, using a surgical robot can be challenging, fatiguing, and time-consuming. Teaching the robot to actively assist surgical tasks, such as suturing, has the potential to vastly improve both the patient's outlook and the surgeon's efficiency. One obstacle to completing surgical sutures autonomously is the difficulty in tracking surgical suture threads. This paper presents novel stereo image processing algorithms for the detection, initialization, and tracking of a surgical suture thread. A nonuniform rational B-spline (NURBS) curve is used to model a thin, deformable, and dynamic length thread. The NURBS model is initialized and grown from a single selected point located on the thread. The NURBS curve is optimized by minimizing the image matching energy between the projected stereo NURBS image and the segmented thread image. The algorithms are evaluated using suture threads, a calibrated test pattern, and a simulated thread image. In addition, the accuracies of the algorithms presented are validated as they track a suture thread undergoing translation, deformation, and apparent length changes. All of the tracking is in real time.

This paper presents an approach to supervisory control of a DaVinci surgical robot. At present, such robots are controlled by teleoperation, with dissimilar kinematics of the operator interface vs. the robot. As a result, it can be difficult for the operator to visualize the kinematic restrictions on the robot, particularly for desired extended, precise trajectories, such as circular needle driving. The interface presented here constitutes a means to elevate the operator from teleoperation mode to supervisory mode. The operator interacts directly with a point-cloud display, allowing selection of task specifications from which the system automatically computes and executes precise trajectories to achieve the task goals. The intent is to allow the operator to focus on task specifications and rely on automation to achieve faster and more precise execution.

In order to realize many of the potential benefits associated with robotically assisted minimally invasive surgery, the robot must be more than a remote controlled device. Currently using a surgical robot can be challenging, fatiguing, and time consuming. Teaching the robot to actively assist surgical tasks, such as suturing, has the potential to vastly improve both patient outlook and the surgeon's efficiency. One obstacle to completing surgical sutures autonomously is the difficulty in tracking surgical suture threads. This paper proposes an algorithm which uses a Non-Uniform Rational B-Spline (NURBS) curve to model a suture thread. The NURBS model is initialized from a single selected point located on the thread. The NURBS curve is optimized by minimizing the image match energy between the projected stereo NURBS image and the segmented thread image. The algorithm is able to accurately track a suture thread as it translates, deforms, and changes length in real-time.

A limitation of robotic surgery is deprivation of sensation of contact forces. Gentle interactions with tissue are desired, but at the same time kinematic constraints of the access portal must be obeyed. A new combination of previous algorithms of hybrid force/position control and Natural Admittance Control is described that achieves these objectives. This new algorithm is compared to a variation of Natural Admittance Control to show the need for the merger of two known algorithms. The hybrid controller is shown to be 3.5 times stiffer than the pure NAC controller in conforming to the portal constraint, without reducing tool tip responsiveness.

We present here a framework for the generation, application, and assessment of assistive models for the purpose of aiding automated robotic parameter optimization methods. Our approach represents an expansion of traditional machine learning implementations by employing models to predict the performances of input parameter sequences and then filter a potential population of inputs prior to evaluation on a physical system. We further provide a basis for numerically qualifying these models to determine whether or not they are of sufficient quality to be capable of fulfilling their predictive responsibilities. We demonstrate the effectiveness of this approach using an industrial robotic testbed on a variety of mechanical assemblies, each requiring a different strategy for completion.

Various “biologically-inspired” models of computation have been developed over the years. Though their inception may have been inspired by biology, most are not biologically plausible. The concepts of training neural networks by back propagation and global observers occurs nowhere in nature. In this paper, a novel variation on a Radial-Basis Function (RBF) network is proposed that is biologically plausible as supported by the literature. A case study is presented that demonstrate the efficacy of this method in producing functional approximations of difficult problems.

Independent Component Analysis (ICA) provides a pragmatic means to perform pattern classification using Bayes' Theorem. Use of ICA with Bayes' Theorem is reviewed and illustrated with examples from classification of images. It is described how ICA with Bayes can create a pattern-classification system that is trainable merely by presenting examples. A specific algorithmic approach is advocated, and demonstrations of its versatility and ease of use show how this technique offers promise for industrial applications.

This work investigates what makes a robotic assembly process “learnable” for the explicit purpose of improving the performance of that process. It has been observed that even stochastic search methods like Genetic Algorithms (GA) can benefit from advanced models of the assembly task. Models built from the results of random samplings of a parameter space have been used previously to predict the performances of parameter sequences not yet evaluated, but the question of what properties of the models actually benefit the optimization remained. A quantitative analysis algorithm is derived and tested on physical assemblies for validation. Results are provided that illustrate the efficacy of the analysis algorithm for prediction-based performance enhancement when such models are used.

Process control methods are developed that leverage compliant robot control, CAD model data extracts, self-acquired surface geometry measurements, and strategy based programming to finish grind cast turbine blades. The processes achieve high finishes, accommodate varying work needs, and require only a brief teaching session to program for new parts.

We present a novel robot design concept intended for material removal in finishing operations. A key component of the design is a cable-driven transmission that exhibits low friction, negligible backlash and high linearity. Use of this transmission in a 2-DOF test rig demonstrated the capacity for stable, smooth performance in grinding and polishing operations. The prototype could be programmed quickly to remove surface flaws using compliant lead-through for teaching. During grinding, the robot was capable of measuring surface profiles to monitor grinding progress. A full-mobility design concept is proposed for an advanced surface-finishing robot.

Design and implementation of an electrooculography based gaze-controlled robotic system is presented. The robot system consists of signal acquisition, pattern recognition, control strategy and robot motion modules. The user's eye gaze movements are reconstructed from electrooculogram (EOG) signals, which are recorded from the face in real time. The eye movement patterns, e.g., saccades, fixation and blinks are detected from the raw eye gaze movement data by a pattern recognition module. The control strategy module interprets the user's intention from the eye movement patterns based on predefined protocols. A horizontally mounted robot, emulating the skeletomuscular configuration of the human arm, is controlled by the robot motion control module to execute the interpreted user intention. The performance results of two control strategies are discussed.

Natural Admittance Control (NAC) has been proposed as a means of implementing responsive force control that is both gentle and rapid while maintaining an end-effector admittance that is passive. Practical implementations, however, must deviate from the ideal NAC formulation, impacting the passivity of the manipulator. Issues arise particularly in the case where NAC is retrofitted to an existing industrial robot controller. Command input may be restricted to only position commands, and the servo algorithm may be fixed. Direct torque control is often not possible, precluding the use of torque feed-forward. Finally, the feedback sensors signals themselves often contain filters. Each of these three effects is examined and their effects on NAC implementations are identified by considering a simplified, continuous-time model of a typical NAC implementation.

A method for passivity analysis of a class of nonlinear systems is described. For linear plants controlled by sampled-data controllers, the resulting interaction admittance is nonlinear. It is shown that satisfying the linear requirements for passivity is insufficient to guarantee passivity of the nonlinear system. To analyze such plants, we first show that if a waveform constituting a counter-example of passivity exists, then a counter-example may also be found within a limited class of functions. By restricting attention to this class of functions, a numerical passivity evaluation is feasible. Examples using the method are presented.

Progress towards programming by demonstration for robotic assembly is presented, advocating the use of virtual impedance and virtual attractor trajectories as a means of encoding atomic behaviors. Switching among behaviors is invoked by recognition of events. Evidence is presented for associating these events with transients, such as impacts. The approach is shown to lead to robot skills that are fast, gentle and reliable.

A limitation of high-speed contact operations, including robotic assembly, is the magnitude of contact forces resulting from inertial effects. Directly attempting to reduce the apparent inertia of interacting systems through force feedback results in instability. It is shown here that one can introduce a mechanical filter to alter the open-loop system dynamics, making feedback much more effective. Experimental results are presented showing a reduction in apparent inertia by nearly two orders of magnitude.

Describes an experimental exploration in Internet-based control of robots. The motivation of this work is that Internet communications can be exploited to achieve greater productivity from machines with local intelligence. Local intelligent systems contact human experts to solicit advice when a problem facing the machine is beyond its cognitive capabilities. This topic is explored in the context of a robot performing a sample domestic task (sorting laundry). An experimental system was constructed that has limited autonomous competence, but which proved to be significantly more productive through the use of occasional Internet-based human supervision.

Robots performing assembly tasks have the opportunity to acquire extensive experience, which could be used to improve performance. This paper reports on a highly encouraging result in which a force-controlled robot exploits a form of genetic algorithm to discover program improvements for mechanical assemblies. In tests on assembly of industrial components, the parameters discovered autonomously by the robot resulted in performance levels significantly better than we were able to tune manually. The result was also significantly better than human performance with these parts.

In this paper we present recent experimental results using a novel parallel manipulator operating under natural admittance control performing difficult mechanical assemblies. The example assemblies are components from an automotive automatic transmission. Success depends on appropriate force responsiveness, rather than precise position control. The robotic assemblies are shown to be gentler than human assemblies while competitive with human assembly rates. The results show the potential for robotic automation in application areas that are currently limited to manual assembly.

Interpretation of force and moment data is used to guide the searching phase of a circular peg-in-hole assembly. It is shown that the available measurements carry varying quality of information, ambiguous in much of the search space and relatively precise in a small region. By interpreting the history of sensory data acquired during an assembly attempt, reliable interpretation of the data is possible. A feature-based technique is described for interpreting sensory data. Experiments with robotic peg-in-hole assembly demonstrated a speed-up of nearly an order of magnitude relative to a blind search.

Computer-aided manufacturing of laminated engineering materials (CAM-LEM), developed at Case Western Reserve University, is a layered-manufacturing approach utilizing automated stacking of parts laser-cut from sheet materials. This paper presents the design of a material-handling system and its integration with a modular laser-cutting system, completing the most recent version of CAM-LEM. Our material-handling system is required to: transfer individual sheets from at least three material stacks to the cutting table of the laser-cutting system; extract single-layer, laser-cut parts from the cutting table; and stack the parts onto a vertical-stack assembly, resulting in fabrication of a 3D object. Design philosophy, details, and stacking performance measurements of the constructed system are presented. It is shown that the resulting system is capable of assembling objects within a 150 mm cube with an assembly precision of approximately 0.050 mm. Further, the assembly operations are relatively fast, so that part build rates are limited primarily by the laser cutter.

Presents an approach to analysis and control of ParaDex, a 7-DOF closed-chain manipulator. The collision states of the manipulator were analyzed to construct the 7-D C-space, and this space was represented in a compact and efficient form. Fast, real-time interference evaluation was implemented and tested on the manipulator. The workspace analysis suggests how to optimize use of the kinematic redundancy. Based on the derived C-space, online collision avoidance was enabled. For quasi-static conditions, virtual repulsion from C-space obstacles insulate the boundaries of configuration space. For higher-speed dynamics, an online look-ahead algorithm is described that takes into account the manipulator dynamics and the actuator saturation limitations.

Computer-aided manufacturing of laminated engineering material (CAM-LEM) is a form of solid freeform fabrication involving feeding, cutting and stacking of sheet materials to form 3D objects. To improve build rates and surface finish, it is desired to cut layers of an object from relatively thick sheets with consideration of tangent angles about each layer's perimeter. Design of the cutting system is key to the success of this approach, since speed and accuracy must be high. This paper describes the evolution of our laser-cutting system from a 5-axis design with stationary optics to a 4-axis design with articulated optics. Detailed analysis and characterization of the competing designs shows that the 4-axis design offers an improvement in both speed and precision.

Calibration of a Motoman P8 robot using an SMX, Inc. laser-based coordinate measuring system is presented. Since the coordinate measuring device is capable of reporting absolute coordinates, unconstrained by any calibration template, it offers highly accurate measurement of poses selected for convenience of parameter identification. It is shown that measurements obtained using the circle-point analysis technique and the highly accurate SMX coordinate measuring device provide insight into the ability to successfully calibrate an industrial robot.

At the Cleveland Clinic, a novel means of cancer treatment, image-directed radiation therapy (IDRT), is being explored experimentally. Using a linear accelerator manipulated by a robot and computed tumor coordinates based on machine vision, this treatment means offers the potential for more highly targeted radiation dose delivery to tumors, reducing the collateral damage to surrounding healthy tissues. This paper presents the motivation for IDRT, identification of the challenges in accomplishing IDRT, and simulated and experimental results for evaluating the potential benefits of IDRT, specifically with respect to lung cancer treatment.

Workspace analysis of a novel manipulator design is presented. The manipulator is a closed-chain design offering high payload, high stiffness and low inertia, but at the expense of limited workspace. A 7 degree-of-freedom is incorporated to help expand the reachable workspace. It is shown that the resulting workspace is complex, but manageable. Methods for fast constraint detection are presented, and techniques for optimizing use of the kinematic redundancy are explained. The result is sufficiently efficient to enable online planning and collision avoidance.

Summarizes results of a five-year, multi-disciplinary, university-industry collaborative effort investigating design issues in agile manufacturing. The focus of the project is specifically on light mechanical assembly, with the demand that new assembly tasks be implementable quickly, economically, and effectively. Key to achieving these goals is the ease of equipment and software reuse. Design choices for both hardware and software must strike a balance between the inflexibility of special-purpose designs and the impracticality of overly general designs. We review both our physical and software design choices and make recommendations for the design of agile manufacturing systems.

Assembly tasks involving large position uncertainties are unsuitable for use of position-controlled robots. To automate such tasks, the assembly system must be responsive to contact forces. Issues in addressing force-responsive automated assembly include contact stability, the degree of force responsiveness required for success, the speed of a successful implementation, and the means to program a force-responsive system to perform a given assembly task. We examine these issues for robotic assembly in the context of automotive transmission components. We report on an impedance-based low-level algorithm and its interface to higher-level strategies that exhibits gentle, fast and reliable assembly of our example components.

In support of rapid-response manufacturing, we propose a new technique for automated design and fabrication of fixture and gripper tooling for mechanical assembly. Our technique uses geometric computations on CAD part descriptions to derive form and frictional form closure tooling. In addition, we invoke rapid prototyping technology to fabricate the computed tooling directly from the derived CAD descriptions. This paper introduces the concepts of our approach to automatic tooling generation, illustrates initial results, and surveys the additional work to be done to further exploit the technique.

This paper describes the design and implementation of a flexible parts feeding system. While flexibility encompasses every part of the workcell design, including hardware and control software, the ability to feed parts in a wide variety of sizes and shapes is crucial. Conventional feeding methods, such as vibratory bowl feeders, are not practical for flexible workcells because of their specialized nature. This system is composed of three conveyors working together. The first conveyor is inclined and lifts parts from a bulk hopper in a quasi-singulated manner. Parts fall from the first conveyor onto the second, horizontally mounted, conveyor. An underlit window at the end of the second conveyor presents a silhouette image of the parts to a vision system. After the pose of a part has been determined, a robotic arm is used to acquire it. Parts which are in unfavorable orientations or are overlapping are returned to the bulk hopper by a third conveyor. Guidelines for part design which improve the feeding system's performance are also presented.

This paper describes the design of a tool for rapid analysis and implementation of flexible material handling systems. The work incorporates a commercial discrete-event and 3D animation simulation system and extends its functionality with respect to material handling systems. Logical clusters of commercial, modular conveyor components are defined and installed as additions to the simulator's component libraries. These logical groupings, plus the material-flow logic specified by the user in a given simulation analysis, are used to enable automatic generation of control code for the corresponding physical implementation of the simulated system. Key elements in accomplishing this connection are the definition of component logical groupings and a novel, reactive-agent based software organization of the real-time material-handling control code.

The need to rapidly reconfigure an agile manufacturing system makes it especially difficult to test the system's control software. Although thorough testing is essential for system reliability, the time available for testing may be short. With a simulator, however, the software can be developed and tested independently from the actual workcell, while production continues or the workcell is reconfigured for the next target product. To facilitate testing of agile manufacturing software, a 3D graphical simulator has been developed at Case Western Reserve University. It permits workcell control software to be tested with a virtual workcell, which exhibits much of the behavior of the real workcell. The simulator has been extensively used in the Agile Manufacturing Project at Case Western Reserve University (CWRU), and most of the actual control software was tested and debugged with it. Considerable time and effort have been saved by simulating various workcell scenarios, some of which are difficult to create in a real workcell, e.g., device failure. In this paper, the architecture of the graphical simulator is described, and a framework for virtual testing is presented. Actual errors found during virtual testing are also described.

An agile workcell has been developed for light mechanical assembly in collaboration with industrial sponsors. The workcell includes multiple Adept robots, a Bosch conveyor system, multiple flexible parts feeders at each robot's workstation, CCD cameras for parts feeding and hardware registration, and a dual VMEbus control system. Our flexible pairs feeder design uses multiple conveyors to singulate the parts and machine vision to locate them. Specialized hardware is encapsulated on modular grippers and modular worktables which can be quickly interchanged for assembly of different products. Object-oriented software (C++) running under VxWorks, a real-time operating system, is used for workcell control. An agile software architecture was developed for rapid introduction of new assemblies through code re-use. A simulation of the workcell was developed so that controller software could be written and tested off-line, enabling the rapid introduction of new products.

This paper introduces a design for agile manufacturing workcells intended for light mechanical assembly of products made from similar components (i.e. parts families). We define agile manufacturing as the ability to accomplish rapid changeover from the assembly of one product to the assembly of another product. Rapid hardware changeover is made possible through the use of robots, flexible part feeders, modular grippers and modular assembly hardware. The flexible feeders rely on belt feeding and binary computer vision for Dose estimation. This has a distinct advantage over non-flexible feeding schemes such as bowl feeders which require considerable adjustment to changeover from one part to another. Rapid software changeover is being facilitated by the use of a real-time, object-oriented software environment, modular software, graphical simulations for off-line software development, and an innovative dual VMEbus controller architecture. These agile features permit new products to be introduced with minimal downtime and system reconfiguration.

This research focuses on the implementation of a natural admittance controller on an industrial manipulator. Natural admittance control is a particular type of interaction controller which guarantees stability with any passive environment. The admittance criterion is presented along with methods of control. A robot model is proposed and the model parameters are found experimentally. A controller is designed which takes into consideration the aforementioned model. Also, a convenient technique that allows "on the fly" modification of controller gains and desired dynamics has been developed. The controller was designed and implemented on an industrial robot and performance results are presented. The implemented scheme is shown to offer high performance and guaranteed stability with good friction rejection.>

Remotec's Andros VI mobile robot is physically capable of ascending and descending stairs. However, the teleoperated control of the robot climbing stairs is difficult, as the operator's feedback is limited to visual and audio cues only. Our analysis and experiments show that this tracked mobile robot is inherently unstable in open-loop stair climbing, and the robot under telemanipulation is prone to falling. We describe the design and validation of a feedback system for automatic heading control for stabilization of stair climbing. The design incorporates solid-state attitude sensors as inputs to an on-board multiprocessor system. We have experimentally demonstrated stability of the robot in stair climbing, even in the presence of large disturbances and noise. With the addition of the on-board computing, control of the robot is elevated from teleoperation to supervisory control.>

This paper presents an improved method for deducing kinematic parameters from constrained calibration data. The method assumes that the calibration data is constrained such that for each recorded set of joint angles, the endpoint of the robot satisfies some parameterized mathematical constraint. Suitable mathematical constraint equations include points, lines, circles, spheres, planes, hyperplanes, and others. The constraint equations do not need to be fully known; some parameters of the constraints can be unknown, and the method can still be employed. The method prescribes a nonlinear transformation of the solution equations into a new space in which a vector function of parameters multiplies a vector function of joint variables. In this transformed space, the vector function of parameters can be identified using a linear, least-squares approach. Subsequently, the transformed parameter-function vector is solved analytically for the actual parameter values. This approach differs from existing, iterative techniques in that there are no numerical problems of local-minima traps, slow convergence rates, null-space wandering or instability. Examples are presented to illustrate the method, and results are presented for calibration of an AdeptOne robot.>

An online motion planning algorithm in 2D configuration space is presented for right-handed manipulators. Critical points on the boundaries of obstacles in configuration space are identified. A graph is constructed using simple wall-following to determine connections between the critical points. Motion between connected critical points may be executed through the definition of potential functions and critical point subgoals without encountering local minima. The planning problem was solved by modifying line-of-sight and wall-following algorithms to resort to the critical point graph in finding exit points to goal locations. The results was extremely fast plan generation, which has been crucial in achieving online 3D planning.>

The authors present an analysis of why control systems are ineffective in compensating for acceleration disturbances due to Coulomb friction. Linear arguments indicate that the effects of Coulomb friction on a body are most difficult to reject when the control actuator is separated from the body of compliance. The linear arguments were illustrated in a nonlinear simulation of optimal linear tracking control in the presence of nonlinear friction. The results of endpoint acceleration measurements for four robot designs are presented and are compared with simulation and with equivalent measurements on a human. It is concluded that Coulomb friction in common bearings and transmission induces unacceptable levels of endpoint acceleration, that these accelerations cannot be adequately attenuated by control, and that robots for microgravity work will require special design considerations for inherently low friction.>

A novel roller-gear traction drive has been designed, built, and evaluated for use in a robot joint. The drive incorporates steel rollers integrated with precision gearing in parallel. Evaluation of a 23.2:1 ratio, 300-W, 26-N-m output torque, prototype drive is presented. Due to the relatively high stiffness, zero backlash, smooth torque production, and back-drivability, the transmission permits smooth motion control and exceptionally good performance under closed-loop output torque control. Under impedance control, the drive is shown to be responsive to external torques, yet is stable upon impact with rigid environments.>

A computationally efficient method to achieve reflexive collision avoidance is described. The system consists of four parallel, asynchronous control layers: a conventional servo tracking controller, a reactive trapezoidal velocity profiler, a joint-by-joint reflexive collision avoidance layer, and a guiding potential-function layer. The lowest two layers guarantee that the robot will not overshoot any joint-space position setpoint. The higher two layers compute successive set points based on a continuous, online inspection of configuration space. The guiding potential-function layer incorporates task-space-based attraction to a hand goal, while the reflexes permit use of kinematic redundancy for obstacle avoidance. In many cases, no explicit path planning is required to achieve competent, collision-free motion to a task-space goal while moving in a cluttered environment. Experimental results are described for the physical implementation of the system on the first four joints of a kinematically redundant robot.>

A control method that achieves impedance control of redundant degree-of-freedom manipulators is proposed. The technique combines reduced-order impedance control with configuration control to achieve impedance control of the hand and integrable control of the redundancy. The resulting controlled dynamics is shown to present a passive physical equivalent impedance, thus guaranteeing stability in contact with arbitrary passive environment. In addition, it is shown that there are severe restrictions in choosing the desired hand inertia.>

Redesign of the controller for an AdeptOne robot is described. The focus is on the production of controllable torque from Adept's nonlinear three-phase variable-reluctance motors. An experimental motor characterization and a linearizing commutation algorithm are described. Results of the torque controller are presented. Initial measurements of AdeptOne dynamic parameters obtained using the torque controller are reported. Organization of the controller within an open-architecture multiprocessor system permits rapid prototyping of a variety of control algorithms.>

Mathematical properties of configuration space are presented, and algorithms invoking those properties for efficient computation of obstacles in configuration space are described. Simple elements in Cartesian space which can be transformed into configuration space rapidly are identified. Transformations of complex workspace shapes into configuration space are described in terms of multiple transformations of such simpler primitives. Computational considerations and examples are presented for the first three degrees of freedom of an industrial robot.>

Experiments in automatic collision avoidance for robots using acceleration-based reflex control are described. Acceleration-based reflex control responds to acceleration commands from higher levels, as opposed to prior reflex control approaches based on position commands from higher levels. Reflex control is exerted in configuration space and assumes either inherent dynamic decoupling of the robot links or feedback decoupling. Implementation of acceleration-based reflex control for 3-D collision avoidance using a General Electric GP132 robot is described. Collision avoidance with respect to stationary obstacles is guaranteed. In addition, performance measurements illustrate how the reflexes introduce no significant distortion to higher-level controllers when reflex action is not required.>

A reflex control system is proposed for the realization of automatic collision avoidance in an environment that is compatible with arbitrary higher-level torque-based controllers. The system has the virtue of being failsafe without introducing unnecessary interference in the execution of higher-level controls. The reflex controller is useful for safely experimenting with new, possibly unstable control algorithms. Operation of the reflexes proposed here, although implemented as a decision-making process, is equivalent to the action of repulsive potential fields plus dissipative terms. The equivalent potential fields have a finite range of influences and combine through logic and set operations rather than linear superposition. Reflex control has been demonstrated to work effectively in the presence of moving, albeit quasi-static, obstacles.>

Time-optimal control of robot motion for dynamically decoupled manipulators is described in terms of potential functions. Avoidance of moving obstacles is incorporated via protective potential functions. An energy interpretation of the potential functions leads to rules for construction of avoidance functions and logical operations among them. Simple expressions for combining obstacle fields with an obstacle-free time-optimal solution result in the minimum safe influence of obstacles. Simulation results are given demonstrating high-speed target interception in the presence of obstacles.