Motion planning framework based on dual-agent DDPG method for dual-arm robots guided by human joint angle constraints
Keyao Liang,
Fusheng Zha,
Wei Guo
et al.
Abstract:IntroductionReinforcement learning has been widely used in robot motion planning. However, for multi-step complex tasks of dual-arm robots, the trajectory planning method based on reinforcement learning still has some problems, such as ample exploration space, long training time, and uncontrollable training process. Based on the dual-agent depth deterministic strategy gradient (DADDPG) algorithm, this study proposes a motion planning framework constrained by the human joint angle, simultaneously realizing the … Show more
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