在人形接待员机器人中,在执行标志性手势失败后,关节的重新配置
Wisanu Jutharee1, Boonserm Kaewkamnerdpong2, Thavida Maneewarn1,3,4
1Institute of Field Robotics, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand.
Sensors (Basel, Switzerland)
|November 25, 2023
概括
人形机器人可以使用生物灵感的人工智能从执行器故障中恢复. 该研究为Namo等机器人开发了一种关节重新配置算法,使他们能够在损坏后也执行手势.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 控制系统 控制系统
背景情况:
- 带有人类形臂的人形机器人在任务中面临着执行器故障的挑战.
- 机器人执行器的故障可能会阻碍预先编程的动作和手势的执行.
研究的目的:
- 为Namo接待员机器人开发一个联合重新配置算法,以确保在执行器故障后的手势性能.
- 为了使人形机器人具有7-DOF臂的快速故障恢复响应.
主要方法:
- 利用生物启发的人工智能:遗传算法 (GA),细菌食优化算法 (BFOA) 和人工蜂群 (ABC).
- 提出了一种手势相似度测量作为关节重新配置的客观函数.
- 雇佣了对参数调整的网格搜索,并比较了AI方法的性能.
主要成果:
- 生物启发的AI方法在模拟关节运动失效后1秒内成功建议重新配置的手势.
- BFOA和ABC都提供了最佳的重新配置手势,ABC显示出更高的可靠性和更少的结果变化.
- 联合重新配置方法在所有可能的联合故障场景中都表现出有效性.
结论:
- 拟议的方法使人形机器人在严格的时间限制下能够有效地恢复关节故障.
- 生物灵感的人工智能算法,特别是ABC,为实时机器人故障恢复提供了强大的解决方案.
- 这一策略提高了人形机器人在动态环境中的运行弹性.
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