A unified quadratic-programming-based dynamical system approach to joint torque optimization of physically constrained redundant manipulators

In this paper, for joint torque optimization of redundant manipulators subject to physical constraints, we show that velocity-level and acceleration-level redundancy-resolution schemes both can be formulated as a quadratic programming (QP) problem subject to equality and inequality/bound constraints...

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Bibliographic Details
Published in:IEEE transactions on systems, man and cybernetics. Part B, Cybernetics Vol. 34; no. 5; pp. 2126 - 2132
Main Authors: Yunong Zhang, Ge, S.S., Tong Heng Lee
Format: Journal Article
Language:English
Published: United States IEEE 01.10.2004
Subjects:
Acceleration
Algorithms
Artificial Intelligence
Constraint optimization
Dynamical systems
Dynamics
Feedback
Kinematics
Linear matrix inequalities
Manipulator dynamics
Manipulators
Motion
Neural networks
Nonlinear Dynamics
Piecewise linear techniques
Programming, Linear
Quadratic programming
Redundant
Robot arms
Robotics - methods
Robots
Torque
Torque control
ISSN:1083-4419
Online Access:Get full text
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Summary:In this paper, for joint torque optimization of redundant manipulators subject to physical constraints, we show that velocity-level and acceleration-level redundancy-resolution schemes both can be formulated as a quadratic programming (QP) problem subject to equality and inequality/bound constraints. To solve this QP problem online, a primal-dual dynamical system solver is further presented based on linear variational inequalities. Compared to previous researches, the presented QP-solver has simple piecewise-linear dynamics, does not entail real-time matrix inversion, and could also provide joint-acceleration information for manipulator torque control in the velocity-level redundancy-resolution schemes. The proposed QP-based dynamical system approach is simulated based on the PUMA560 robot arm with efficiency and effectiveness demonstrated.
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ISSN:1083-4419
DOI:10.1109/TSMCB.2004.830347