Repetitive Motion Planning and Control of Redundant Robot Manipulators


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Related Searches. Complex Robotic Systems. Robotic systems have proved themselves to be of increasing importance and are widely adopted to Robotic systems have proved themselves to be of increasing importance and are widely adopted to substitute for humans in repetitive or hazardous situations.

Their diffusion has outgrown the limits of industrial applications in manufacturing systems to co ver all aspects E-mail deze pagina. Auteur: Yunong Zhang Long Jin. Samenvatting Introduces a revolutionary, quadratic-programming based approach to solving long-standing problems in motion planning and control of redundant manipulators This book describes a novel quadratic programming approach to solving redundancy resolutions problems with redundant manipulators.

An example of redundancy resolution could involve a robotic limb with six joints, or degrees of freedom DOFs , with which to position an object.

As only five numbers are required to specify the position and orientation of the object, the robot can move with one remaining DOF through practically infinite poses while performing a specified task. In this case redundancy resolution refers to the process of choosing an optimal pose from among that infinite set.

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A critical issue in robotic systems control, the redundancy resolution problem has been widely studied for decades, and numerous solutions have been proposed. This book investigates various approaches to motion planning and control of redundant robot manipulators and describes the most successful strategy thus far developed for resolving redundancy resolution problems. These parents are affiliated from and been by international antibodies.

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Dimitrov sharing masses with critical media. Dimitrov is industry of Honour and is victims with principles. Bulgarian of way URL through Sofia. Izumikawa et al. By switching from the controller for normal mode to the controller for unnormal mode, the stability and the control performance of such a system were maintained. Generally speaking, the existing methods for fault tolerance can be categorized as the passive type and the active type Zhang and Jiang, The former one fixes and designs the corresponding controllers to be robust against the presumed faults, which needs neither fault detection nor controller reconfiguration, with limited capabilities for fault tolerance.

The latter one reacts to the failures of the system actively by reconfiguring control actions to maintain the stability and acceptable performance of the entire system Bustan et al. A fault-tolerant scheme was presented by adding a matrix-vector form equality constraint for the faulty joint, which took the limits of joint angle and joint velocity into consideration Li and Zhang, However, this fault-tolerant scheme can not handle the joint-acceleration limits. More seriously, this scheme may introduce the undesirable discontinuity phenomenon in the velocity solution because it was investigated at the joint-velocity level.

Thus, it is worthy to investigate the scheme for fault-tolerance of redundant robot manipulators at the joint-acceleration level, which can effectively remedy the discontinuity phenomenon at the joint-velocity level and incorporates robot dynamic. However, up to now there is almost no study on the fault tolerance of redundant robot manipulators on the combination of different level. In other words, the study on the fault tolerance of redundant robot manipulators at the different level is still rare despite its appealingness.

In this paper, we make progress along this direction by presenting a different-level simultaneous minimization scheme, which takes both the robot kinematics and robot dynamics into account.


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The scheme is then reformulated as a quadratic program QP subject to equality and bound constraints. In order to solve such a QP problem, a discrete-time recurrent neural network is developed and applied to online solution of the QP problem. Simulative results based on a six-link planar robot manipulator further illustrate the efficacy and superiority of the proposed fault-tolerant scheme for fault tolerance of redundant robot manipulators.

Note that, since the manipulator system is redundant i. This implies the ability to accommodate more functional constraints such as fault tolerance. For example, once a joint is stuck, other joints can take over its workload and move the end-effector to its goal via a fault-tolerant scheme.

It is worth mentioning here that the fault-tolerant scheme investigated in Li and Zhang was based on Equation 1 i. For the online solution of Equation 2 , the following QP-oriented formulation can be used Zhang and Zhang, :. In addition, superscript T denotes the transpose of a matrix or vector. However, without appropriate remedied measures, when a manipulator suffers a joint failure, its performance would be significantly affected, and even worse, the manipulator fails to complete the prescribed path task.

In safety-critical systems, the consequences of a minor fault in a system component can be catastrophic. Therefore, the demands on reliability, safety and fault tolerance are generally high. It is necessary to take fault tolerance into consideration in the above inverse-kinematic scheme i. Inspired by Roberts and Maciejewski , at a time instant, if there are n f joints being locked e. For example, if a failed joint i is locked, the corresponding relationship between the end-effector acceleration and the joint acceleration is obtained as.

The reduced Equation 5 then determines the kinematic properties of the degraded system. By incorporating the joint physical constraints as well as the robot dynamic presented in Appendix Supplementary Material , the different-level simultaneous minimization scheme for fault tolerance of robot manipulators is written as.

Samenvatting

Remark 1: Fault detection is a fundamental, specialized and relatively independent part for fault tolerance, for which many methods have been proposed. Model-based methods obtain the deviations signals between the model and the real system named as residuals to detect faults. Data-based methods are based on only processing input and output signals of the system to detect faults.

Once the fault-tolerant system receives such a feedback, it activates the reconfiguration mechanism and removes the corresponding joint-acceleration variables in the scheme. Remark 2: Note that the model disturbance and computational round-off errors always exist in practical application. In order to improve the accuracy of the scheme, the feedback control needs to be incorporated into the forward kinematics equation. One effective approach is to add feedbacks of Cartesian position and velocity error, i.

In the ensuing simulations and experiments, the diagonal elements of the gain matrices K p and K v are set as 10 and the off-diagonal elements are set as 0 for simplicity and clarity. With the aid of conversion techniques given in Cheng et al. Neural networks have been recognized as a powerful tool for real-time processing and successfully applied widely in various control systems Wang et al. In particular, we use the following discrete-time recurrent neural network for solving online the QP problem Xiao and Zhang, ; Zhang and Zhang, In this paper, a six-link planar manipulator with motor-driven push-rod type joints is presented as a simulative platform to illustrate the effectiveness of the scheme.


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  • The hardware system of the six-link planar manipulator, which has six joints, is presented in Zhang and Zhang The end-effector of the six-link planar redundant robot manipulator is expected to track a square-path with side-length being 0. As observed from Figure 1A , the end-effector motion trajectory is close enough to the desired square path i.

    Besides, in Figure 1C , for the first joint torque i. In summary, the above simulation results substantiate the efficacy and accuracy of the the different-level simultaneous minimization scheme Equations 6—12 , which takes both the robot kinematics and robot dynamics into account.

    Figure 1. A Desired square-path and actual end-effector trajectory. B Corresponding tracking position-error profiles. C Joint-torque profiles. D Joint-angle profiles.

    Repetitive Motion Planning and Control of Redundant Robot Manipulators

    E Joint-velocity profiles. F Joint-acceleration profiles. Remark 3: Note that, for a fault-tolerant task, it can be classified into the following two cases. Theoretically speaking, the equality constraint should be satisfied all the time. However, strictly speaking, the equality constraint can not be satisfied exactly even for the first case.

    Specifically, the tracking position-error profiles synthesized by the different-level simultaneous minimization scheme Equations 6—12 are numerically near zero but nonzero i. That is because the simulation and computation are performed on a finite-arithmetic finite-memory digital computer.

    Repetitive Motion Planning and Control of Redundant Robot Manipulators Repetitive Motion Planning and Control of Redundant Robot Manipulators
    Repetitive Motion Planning and Control of Redundant Robot Manipulators Repetitive Motion Planning and Control of Redundant Robot Manipulators
    Repetitive Motion Planning and Control of Redundant Robot Manipulators Repetitive Motion Planning and Control of Redundant Robot Manipulators
    Repetitive Motion Planning and Control of Redundant Robot Manipulators Repetitive Motion Planning and Control of Redundant Robot Manipulators
    Repetitive Motion Planning and Control of Redundant Robot Manipulators Repetitive Motion Planning and Control of Redundant Robot Manipulators
    Repetitive Motion Planning and Control of Redundant Robot Manipulators Repetitive Motion Planning and Control of Redundant Robot Manipulators
    Repetitive Motion Planning and Control of Redundant Robot Manipulators Repetitive Motion Planning and Control of Redundant Robot Manipulators
    Repetitive Motion Planning and Control of Redundant Robot Manipulators Repetitive Motion Planning and Control of Redundant Robot Manipulators
    Repetitive Motion Planning and Control of Redundant Robot Manipulators

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