作者: Behzad Dariush , Youding Zhu , Arjun Arumbakkam , Kikuo Fujimura
DOI: 10.1109/ROBOT.2010.5509456
关键词: Control theory 、 Motion planning 、 Kinematics 、 Robot kinematics 、 Inverse kinematics 、 Collision 、 ASIMO 、 Motion control 、 Humanoid robot 、 Mathematics
摘要: This paper introduces a kinematically constrained closed loop inverse kinematics algorithm for motion control of robots or other articulated rigid body systems. The proposed strategy utilizes gradients collision and joint limit potential functions to arrive at an appropriate weighting matrix penalize dampen approaching constraint surfaces. method is particularly suitable self avoidance highly systems which may have multiple points among several segment pairs. In that respect, the has distinct advantage over existing gradient projection based methods rely on numerically unstable null-space projections when there are intermittent constraints. We also show how this approach can be augmented with previously reported redirection constraints along virtual surface manifolds. hybrid effective, robust, does not require parameter tuning. efficacy demonstrated problem where reference obtained from human observations. simulation experimental results humanoid robot ASIMO.