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Updated: Jan 18, 2026

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对工业机器人武器采样和DRL运动规划方法的比较基准

Ignacio Fidalgo Astorquia1, Guillermo Villate-Castillo2, Alberto Tellaeche1

  • 1Department of Computing, Electronics and Communication Technologies, University of Deusto, Avenida de las Universidades 24, 48007 Bilbao, Spain.

Sensors (Basel, Switzerland)
|September 13, 2025
PubMed
概括

工业机器人的新型深度强化学习 (DRL) 运动计划器在速度和成功率上明显优于传统的采样方法. 这一进步为实时机器人控制提供了潜力.

关键词:
开放的运动规划图书馆 (OMPL)课程学习学习课程学习深度强化学习 (DRL) 是一种深度强化学习.混合动力运动规划.工业机器人工业机器人工业机器人运动规划 运动规划基于抽样的规划者.

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