This book describes the design and implementation of control strategies for the following topics: i) Whole-arm-grasping control for redundant robot manipulators, ii) Neural network grasping controller for continuum robots, and iii) Coordination control for haptic and teleoperator systems. A kinematic control, for whole-arm grasping of objects using redundant robot manipulators, which facilitates the encoding of both the end-effector position, as well as body self-motion positioning information as a desired trajectory signal for the manipulator joints is presented along with experimental results. An approach to whole-arm grasping control for hyper-redundant robots or continuum robots, is also illustrated. The grasping controller, developed in two stages; high level path planning for the grasping objective, and a low level joint controller using a neural network feedforward component to compensate for dynamic uncertainties, is presented along with some experimental results. Additionally, two controllers, developed for nonlinear haptic and teleoperator systems, are presented. The controllers ensure the tracking and coordination between the systems. Experimental results are included.
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This book describes the design and implementation of control strategies for the following topics: i) Whole-arm-grasping control for redundant robot manipulators, ii) Neural network grasping controller for continuum robots, and iii) Coordination control for haptic and teleoperator systems. A kinematic control, for whole-arm grasping of objects using redundant robot manipulators, which facilitates the encoding of both the end-effector position, as well as body self-motion positioning information as a desired trajectory signal for the manipulator joints is presented along with experimental results. An approach to whole-arm grasping control for hyper-redundant robots or continuum robots, is also illustrated. The grasping controller, developed in two stages; high level path planning for the grasping objective, and a low level joint controller using a neural network feedforward component to compensate for dynamic uncertainties, is presented along with some experimental results. Additionally, two controllers, developed for nonlinear haptic and teleoperator systems, are presented. The controllers ensure the tracking and coordination between the systems. Experimental results are included.
Nitendra Nath received the B.S. degree in electrical engineering from Pune University, Pune, India, in 2004 and the M.S. degree in electrical engineering with intelligent systems as the focus area from Clemson University, Clemson, SC, USA, in 2006. Currently, he is working towards his PhD degree in Clemson University.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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