Abstract

Motion planning is one of the fundamental technologies for robots to achieve autonomy. Free-floating space robots composed manipulators and base satellite that do not actively control its position and attitude has nonholonomic characteristics, and there is a first-order differential relationship between its joint angle and the base attitude. In addition, the planning framework which first converts the goal end-effector pose to its corresponding target configuration, and then plan the trajectory from the initial configuration to the goal configuration still has the following problems: the goal configuration and the initial configuration may not be in the same connected domain. Based on the RRT framework, the motion planning of a free-floating space robot from the initial configuration to the goal end-effector pose is studied. In the algorithm design, in order to deal with the differential constraints of the free-floating space robot, and the requirement that the attitude disturbance of its base cannot exceed its limit, a control-based local planner for random configuration guiding growth of the tree and a control-based local planner for goal end-effector pose guiding growth of the tree that can adjust the attitude of the base when necessary are proposed. The former can ensure the effective exploration of the configuration space, and the latter can avoid the occurrence of singularity while ensuring that the algorithm converges quickly and the base attitude disturbance meets the constraints. The present algorithm does not need to solve the inverse kinematics, can successfully complete the planning task, and ensure that the base attitude disturbance meets the requirements. The simulation verifies the effectiveness of the algorithm.

Highlights

  • ÉêME ëêê Mr􀭴0g éê JTw ùú ëêHwφ ûú

  • Non⁃inverse kinematics of free⁃floating space robot based on motion planning of sampling

  • The planning framework which first converts the goal end⁃effector pose to its corresponding target configuration, and plan the trajectory from the initial configuration to the goal configuration still has the follow⁃ ing problems: the goal configuration and the initial configuration may not be in the same connected domain

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Summary

Introduction

ÉêME ëêê Mr􀭴0g éê JTw ùú ëêHwφ ûú Algorithm 1 GB⁃RRT for FFSR 1 tree.V.init( qI ) 2 for i = 1 to K do 3 if rand( )

Results
Conclusion
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