Reinforcement Learning-Based Reactive Obstacle Avoidance Method for Redundant Manipulators

Reinforcement Learning-Based Reactive Obstacle Avoidance Method for Redundant Manipulators

Redundant manipulators are widely used in fields such as human-robot collaboration due to their good flexibility. To ensure efficiency and safety, the manipulator is required to avoid obstacles while tracking a desired trajectory in many tasks. Conventional methods for obstacle avoidance of redundan...

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Bibliographic Details
Main Authors: Yue Shen, Qingxuan Jia, Zeyuan Huang, Ruiquan Wang, Junting Fei, Gang Chen
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Entropy
Subjects:
redundant manipulator
obstacle avoidance
reinforcement learning
null space
Online Access:https://www.mdpi.com/1099-4300/24/2/279

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