This article presents parallel method for computing inverse kinematics solitions for robots with closed-form solutions moving along a straight line trajectory specified in Cartesian space. Zhang and Paul's approach 1 is improved for accuracy and speed. Instead of using previous joint positions as proposed by Zhang and Paul, a first order prediction strategy is used to decouple the dependency between joint positions, and a zero order approximation solution is computed. A compensation scheme using Taylor series expansion is applied to obtain the trajectory gradient in joint space to replace the correction scheme proposed by Zhang and Paul. The configuration of a Mitsubishi RV-M1 robot is used for the stimulation of a closed-form inverse kinematics solutions. An Alta SuperLink/XL with four transputer nodes is used for parallel implementation. The stimulation results show a significant improvement in displacement tracking errors and joint configuration errors along the straight line trajectory. The computational latency is reduced as well. The modified approach proposed in this work is more accurate and faster than Zhang and Paul's approach for robots with closed-form inverse kinematics solutions.
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