Kinematic control of a redundant manipulator using inverse-forward adaptive scheme with a KSOM based hint generator

Swagat Kumar, Laxmidhar Behera, Martin McGinnity

    Research output: Contribution to journalArticle

    26 Citations (Scopus)

    Abstract

    This paper proposes an online inverse-forward adaptive scheme with a KSOM based hint generator forsolving the inverse kinematic problem of a redundant manipulator. In this approach, a feed-forwardnetwork such as a radial basis function (RBF) network is used to learn the forward kinematic map ofthe redundant manipulator. This network is inverted using an inverse-forward adaptive scheme until thenetwork inversion solution guides the manipulator end-effector to reach a given target position witha specified accuracy. The positioning accuracy, attainable by a conventional network inversion scheme,depends on the approximation error present in the forward model. But, an accurate forward map wouldrequire a very large size of training data as well as network architecture. The proposed inverse-forwardadaptive scheme effectively approximates the forward map around the joint angle vector provided by ahint generator. Thus the inverse kinematic solution obtained using the network inversion approach cantake the end-effector to the target position within any arbitrary accuracy.In order to satisfy the joint angle constraints, it is necessary to provide the network inversion algorithmwith an initial hint for the joint angle vector. Since a redundant manipulator can reach a given target end-effector position through several joint angle vectors, it is desirable that the hint generator is capable ofproviding multiple hints. This problem has been addressed by using a Kohonen self organizing map basedsub-clustering (KSOM-SC) network architecture. The redundancy resolution process involves selecting asuitable joint angle configuration based on different task related criteria.The simulations and experiments are carried out on a 7 DOF PowerCubeTM manipulator. It is shownthat one can obtain a positioning accuracy of 1 mm without violating joint angle constraints even whenthe forward approximation error is as large as 4 cm. An obstacle avoidance problem has also been solvedto demonstrate the redundancy resolution process with the proposed scheme.
    Original languageEnglish
    Pages (from-to)622-633
    JournalRobotics and Autonomous Systems
    Volume58
    Issue number5
    DOIs
    Publication statusPublished - 2010

    Keywords

    • Redundant manipulator
    • Inverse kinematic solution
    • Kohonen Self-Organizing Map (KSOM)
    • Network inversion
    • Radial Basis Function Network (RBFN)
    • KSOM-SC architecture
    • Redundancy resolution

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