一个人形机器人使用三粒子模型预测控制和全身控制的坐运动
Hongxiang Chen1, Xiuli Zhang1, Mingguo Zhao2
1School of Mechanical Electrical and Control Engineering, Beijing Jiaotong University, Beijing 100044, China.
Sensors (Basel, Switzerland)
|January 25, 2025
概括
人形机器人现在可以使用新的三粒子模型预测控制 (TP-MPC) 和全身控制 (WBC) 算法,以更高的精度进行连续. 这种方法增强了轨迹跟踪,并减少了膝盖扭矩峰值,以提高机器人的性能.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统 控制系统
- 人类型机器人运动
背景情况:
- 是人形机器人的一个基本运动,对于机器人调试,服务行业和跳跃等动态动作等任务至关重要.
- 精确和持续的坐对于推进人形机器人的能力和应用至关重要.
研究的目的:
- 开发和评估一种新的控制算法,以在人形机器人中实现准确和连续的坐动作.
- 为了改善轨迹跟踪并减轻诸如坐时膝盖扭矩峰值过高等问题.
主要方法:
- 一种三粒子模型预测控制 (TP-MPC) 方法与基于体重的全身控制 (WBC) 结合起来.
- 人形机器人动态被简化为三个粒子 (手臂,腿,干) 用于TP-MPC优化.
- TP-MPC生成了优化的参考轨迹,然后由WBC遵循.
主要成果:
- 与单独的WBC相比,联合TP-MPC和WBC算法显示出更高的轨迹跟踪精度.
- 拟议的方法有效地减少了坐期间在WBC观察到的过度膝盖扭矩峰值.
- 该算法被证明是计算效率高,在100 Hz的频率下运行.
结论:
- 将TP-MPC与WBC集成为控制人形机器人坐动作提供了重大进步.
- 这种方法提高了精度,减少了不必要的扭矩峰值,并保持了计算效率.
- 这些发现有助于开发更有能力和更强大的类人机器人,用于各种应用.
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