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Distributed coordinated adaptive tracking in networked redundant robotic systems with a dynamic leader

Science China(Technological Sciences) 2014年第5期57卷 905-913页

作者： ZHOU Jin WU XingJie LIU ZengRong Shanghai Institute of Applied Mathematics and Mechanics Shanghai Key Laboratory of Mechanics in Energy Engineering Shanghai University School of Mathematics and Statistics Hefei Normal University Institute of System Biology Shanghai University

Distributed coordinated control of networked robotic systems formulated by Lagrange dynamics has recently been a subject of considerable interest within science and technology communities due to its broad engineering applications involving complex and integrated production processes,where high flexibility,manipulability,and maneuverability are desirable *** this paper,we investigate the distributed coordinated adaptive tracking problem of networked redundant robotic systems with a dynamic *** provide an analysis procedure for the controlled synchronization of such systems with uncertain *** also find that the proposed control strategy does not require computing positional inverse kinematics and does not impose any restriction on the self-motion of the manipulators;therefore,the extra degrees of freedom are applicable for other sophisticated *** with some existing work,a distinctive feature of the designed distributed control algorithm is that only a subset of followers needs to access the position information of the dynamic leader in the task space,where the underlying directed graph has a spanning ***,we present a simulation example to verify the effectiveness of the proposed algorithms.

关键词： networked Lagrange system redundant robot distributed adaptive control tracking synchronization algorithm

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Two optimization algorithms for solving robotics inverse kinematics with redundancy

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控制理论与应用（英文版） 2010年第2期8卷 166-175页

作者： Jianxin XU, Wei WANG, Yuanguang SUN (Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576) Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

The kinematic redundancy in a robot leads to an infinite number of solutions for inverse kinematics, which implies the possibility to select a 'best' solution according to an optimization criterion. In this paper, two optimization objective functions are proposed, aiming at either minimizing extra degrees of freedom (DOFs) or minimizing the total potential energy of a multilink redundant robot. Physical constraints of either equality or inequality types are taken into consideration in the objective functions. Since the closed-form solutions do not exist in general for highly nonlinear and constrained optimization problems, we adopt and develop two numerical methods, which are verified to be effective and precise in solving the two optimization problems associated with the redundant inverse kinematics. We first verify that the well established trajectory following method can precisely solve the two optimization problems, but is computation intensive. To reduce the computation time, a sequential approach that combines the sequential quadratic programming and iterative Newton-Raphson algorithm is developed. A 4-DOF Fujitsu Hoap-1 humanoid robot arm is used as a prototype to validate the effectiveness of the proposed optimization solutions.

关键词： Inverse kinematics redundant robot Objective function Optimization Numerical approach

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