Sample-Efficient Deep Reinforcement Learning of Mobile Manipulation for 6-DOF Trajectory Following

• Published in: IEEE transactions on automation science and engineering Vol. 22; pp. 11381 - 11391
• Main Authors: Zhou, Yifan, Feng, Qiyu, Zhou, Yixuan, Lin, Jianghao, Liu, Zhe, Wang, Hesheng
• Format: Journal Article
• Language: English
• Published: IEEE 2025
• Subjects: 6-DOF; Adaptation models; Automation; Computational modeling; Deep reinforcement learning; experience replay; Manipulators; mobile manipulation; Robots; Training; Trajectory; trajectory following; Vehicle dynamics

The whole-body control of mobile manipulators for the 6-DOF trajectory following task is the basis of many continuous tasks. However, traditional control strategies rely on accurate models and expert knowledge for solving the trajectory following task. Deep reinforcement learning (DRL) provides a pr...