1,093 research outputs found

    Trajectory generation of space telerobots

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    The purpose is to review a variety of trajectory generation techniques which may be applied to space telerobots and to identify problems which need to be addressed in future telerobot motion control systems. As a starting point for the development of motion generation systems for space telerobots, the operation and limitations of traditional path-oriented trajectory generation approaches are discussed. This discussion leads to a description of more advanced techniques which have been demonstrated in research laboratories, and their potential applicability to space telerobots. Examples of this work include systems that incorporate sensory-interactive motion capability and optimal motion planning. Additional considerations which need to be addressed for motion control of a space telerobot are described, such as redundancy resolution and the description and generation of constrained and multi-armed cooperative motions. A task decomposition module for a hierarchical telerobot control system which will serve as a testbed for trajectory generation approaches which address these issues is also discussed briefly

    Design and Evaluation of the LOPES Exoskeleton Robot for Interactive Gait Rehabilitation

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    This paper introduces a newly developed gait rehabilitation device. The device, called LOPES, combines a freely translatable and 2-D-actuated pelvis segment with a leg exoskeleton containing three actuated rotational joints: two at the hip and one at the knee. The joints are impedance controlled to allow bidirectional mechanical interaction between the robot and the training subject. Evaluation measurements show that the device allows both a "pa- tient-in-charge" and "robot-in-charge" mode, in which the robot is controlled either to follow or to guide a patient, respectively. Electromyography (EMG) measurements (one subject) on eight important leg muscles, show that free walking in the device strongly resembles free treadmill walking; an indication that the device can offer task-specific gait training. The possibilities and limitations to using the device as gait measurement tool are also shown at the moment position measurements are not accurate enough for inverse-dynamical gait analysis

    Robot Impedance Control and Passivity Analysis with Inner Torque and Velocity Feedback Loops

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    Impedance control is a well-established technique to control interaction forces in robotics. However, real implementations of impedance control with an inner loop may suffer from several limitations. Although common practice in designing nested control systems is to maximize the bandwidth of the inner loop to improve tracking performance, it may not be the most suitable approach when a certain range of impedance parameters has to be rendered. In particular, it turns out that the viable range of stable stiffness and damping values can be strongly affected by the bandwidth of the inner control loops (e.g. a torque loop) as well as by the filtering and sampling frequency. This paper provides an extensive analysis on how these aspects influence the stability region of impedance parameters as well as the passivity of the system. This will be supported by both simulations and experimental data. Moreover, a methodology for designing joint impedance controllers based on an inner torque loop and a positive velocity feedback loop will be presented. The goal of the velocity feedback is to increase (given the constraints to preserve stability) the bandwidth of the torque loop without the need of a complex controller.Comment: 14 pages in Control Theory and Technology (2016

    Learning and Reacting with Inaccurate Prediction: Applications to Autonomous Excavation

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    Motivated by autonomous excavation, this work investigates solutions to a class of problem where disturbance prediction is critical to overcoming poor performance of a feedback controller, but where the disturbance prediction is intrinsically inaccurate. Poor feedback controller performance is related to a fundamental control problem: there is only a limited amount of disturbance rejection that feedback compensation can provide. It is known, however, that predictive action can improve the disturbance rejection of a control system beyond the limitations of feedback. While prediction is desirable, the problem in excavation is that disturbance predictions are prone to error due to the variability and complexity of soil-tool interaction forces. This work proposes the use of iterative learning control to map the repetitive components of excavation forces into feedforward commands. Although feedforward action shows useful to improve excavation performance, the non-repetitive nature of soil-tool interaction forces is a source of inaccurate predictions. To explicitly address the use of imperfect predictive compensation, a disturbance observer is used to estimate the prediction error. To quantify inaccuracy in prediction, a feedforward model of excavation disturbances is interpreted as a communication channel that transmits corrupted disturbance previews, for which metrics based on the sensitivity function exist. During field trials the proposed method demonstrated the ability to iteratively achieve a desired dig geometry, independent of the initial feasibility of the excavation passes in relation to actuator saturation. Predictive commands adapted to different soil conditions and passes were repeated autonomously until a pre-specified finish quality of the trench was achieved. Evidence of improvement in disturbance rejection is presented as a comparison of sensitivity functions of systems with and without the use of predictive disturbance compensation

    Magneto-Rheological Actuators for Human-Safe Robots: Modeling, Control, and Implementation

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    In recent years, research on physical human-robot interaction has received considerable attention. Research on this subject has led to the study of new control and actuation mechanisms for robots in order to achieve intrinsic safety. Naturally, intrinsic safety is only achievable in kinematic structures that exhibit low output impedance. Existing solutions for reducing impedance are commonly obtained at the expense of reduced performance, or significant increase in mechanical complexity. Achieving high performance while guaranteeing safety seems to be a challenging goal that necessitates new actuation technologies in future generations of human-safe robots. In this study, a novel two degrees-of-freedom safe manipulator is presented. The manipulator uses magneto-rheological fluid-based actuators. Magneto-rheological actuators offer low inertia-to-torque and mass-to-torque ratios which support their applications in human-friendly actuation. As a key element in the design of the manipulator, bi-directional actuation is attained by antagonistically coupling MR actuators at the joints. Antagonistically coupled MR actuators at the joints allow using a single motor to drive multiple joints. The motor is located at the base of the manipulator in order to further reduce the overall weight of the robot. Due to the unique characteristic of MR actuators, intrinsically safe actuation is achieved without compromising high quality actuation. Despite these advantages, modeling and control of MR actuators present some challenges. The antagonistic configuration of MR actuators may result in limit cycles in some cases when the actuator operates in the position control loop. To study the possibility of limit cycles, describing function method is employed to obtain the conditions under which limit cycles may occur in the operation of the system. Moreover, a connection between the amplitude and the frequency of the potential limit cycles and the system parameters is established to provide an insight into the design of the actuator as well as the controller. MR actuators require magnetic fields to control their output torques. The application of magnetic field however introduces hysteresis in the behaviors of MR actuators. To this effect, an adaptive model is developed to estimate the hysteretic behavior of the actuator. The effectiveness of the model is evaluated by comparing its results with those obtained using the Preisach model. These results are then extended to an adaptive control scheme in order to compensate for the effect of hysteresis. In both modeling and control, stability of proposed schemes are evaluated using Lyapunov method, and the effectiveness of the proposed methods are validated with experimental results
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