Abstract
We consider a motion planning problem with task space constraints in a complex environment for redundant manipulators. For this problem, we propose a motion planning algorithm that combines kinematics control with rapidly exploring random sampling methods. Meanwhile, we introduce an optimization structure similar to dynamic programming into the algorithm. The proposed algorithm can generate an asymptotically optimized smooth path in joint space, which continuously satisfies task space constraints and avoids obstacles. We have confirmed that the proposed algorithm is probabilistically complete and asymptotically optimized. Finally, we conduct multiple experiments with path length and tracking error as optimization targets and the planning results reflect the optimization effect of the algorithm.
Highlights
Task space constrains are common in robotic applications, both in service and in industrial applications
The sampling-based algorithm is very efficient and probabilistically complete. We use this type of algorithm to solve the obstacle avoidance motion planning problem with task constraints for kinematically redundant manipulators
The approach essentially uses the self-motion in null space to achieve obstacle avoidance, and the planned path will inevitably be redundant in joint space
Summary
Task space constrains are common in robotic applications, both in service and in industrial applications. Redundant robots,[1] such as humanoids or manipulators, possess the dexterity to plan multiple trajectories that meet the task constraints. They have the ability to pursue additional objectives, among which the most important is obstacle avoidance. The sampling-based algorithm is very efficient and probabilistically complete We use this type of algorithm to solve the obstacle avoidance motion planning problem with task constraints for kinematically redundant manipulators. We focus on kinematically redundant manipulators and the task is to follow a given end-effector path Such problems require the robot to follow a path with high precision in continuous time and meet the obstacle avoidance requirements at the same time. Several directions to improve the current work have been mentioned in the concluding section
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