让机器人边走边搬东西时保持平衡，还能应对推拉干扰。
Humanoid Loco-Manipulations Pattern Generation and Stabilization Control
- 基于倒立摆模型，融合外部力影响设计控制策略。
- 仿真与实机实验均验证了轨迹规划与力补偿的有效性。
- 适合研究人形机器人运动操控与稳定性的研究人员。
为使人形机器人在行走过程中执行搬运等任务，需考虑由人形-物体接触产生的持续或交替外部力，而不仅仅是足底与地面的反作用力。本文提出一种双足控制策略，用于处理此类外部力。首先，推导了包含外部操作力影响的双足动力学基础公式，即线性倒立摆模型和发散运动分量。随后，提出一种轨迹生成器，规划与参考操作力轨迹一致的质心运动轨迹；并设计一个稳定器，以补偿期望与实际操作力之间的误差。所提控制器在仿真及真实人形机器人实机的移动搬运实验中均得到验证，效果良好。
原文摘要 · Abstract (English)
In order for a humanoid robot to perform loco-manipulation such as moving an object while walking, it is necessary to account for sustained or alternating external forces other than ground-feet reaction, resulting from humanoid-object contact interactions. In this letter, we propose a bipedal control strategy for humanoid loco-manipulation that can cope with such external forces. First, the basic formulas of the bipedal dynamics, i.e., linear inverted pendulum mode and divergent component of motion, are derived, taking into account the effects of external manipulation forces. Then, we propose a pattern generator to plan center of mass trajectories consistent with the reference trajectory of the manipulation forces, and a stabilizer to compensate for the error between desired and actual manipulation forces. The effectiveness of our controller is assessed both in simulation and loco-manipulation experiments with real humanoid robots.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。