基于DDPG算法的空间机器人避障运动规划

Hanying Sang, Shuquan Wang
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引用次数: 0

摘要

为了解决空间机器人的非结构化环境和复杂的操作任务问题,本文采用数据驱动、无模型的DDPG算法对自由漂浮基座七自由度空间机器人进行避障运动规划。针对DDPG算法收敛困难、收敛速度慢的问题,在传统稀疏奖励函数的基础上增加了人工制导项。本文提出了一种基于任务分解体系结构的奖励函数改进方法,该方法动态调整避障制导项和目标制导项的权重系数。仿真结果表明,该方法有效地提高了算法的收敛性能,使空间机器人能够更好地完成避碰和逼近目标点的任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Motion planning of space robot obstacle avoidance based on DDPG algorithm
In order to solve the problem of unstructured environment and complex operation task of space robot, this paper use DDPG algorithm which is data-driven and model free in the obstacle avoidance motion planning of 7-DOF space robot of free-floating base. Aiming at the difficulty and the low speed of the convergence of DDPG algorithm, artificial guidance term is added on the basis of traditional sparse reward function. This paper proposes an improved method of reward function based on task decomposition architecture, in which the weight coefficients of obstacle avoidance guidance term and target guidance term are dynamically adjusted. Simulation results show that the proposed method effectively improves the convergence performance of the algorithm, and enables the space robot to better complete the task of avoiding collision and approaching the target point.
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