Xiaoting Dong1,2,3,4, Guangxi Wan1,2,3, Peng Zeng1,2,3

  • 1State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.

PubMed
概括

本研究介绍了一个统一的机器人任务序列和轨迹规划 (TSTP) 模型,通过深度强化学习 (DRL) 来解决它. 与传统方法相比,DRL方法显著减少了能源消耗和计算时间.

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