通过优化扭矩规划实现轮式双足机器人精准跳高控制。
Height Control and Optimal Torque Planning for Jumping With Wheeled-Bipedal Robots
- 构建新动力学模型并结合贝叶斯优化设计连续扭矩曲线。
- 跳高误差降低82.3%，能耗减少26.9%，40次内快速收敛。
- 适合需要精准跳高且实验次数受限的机器人研发场景。
本文研究基于扭矩规划与能耗优化的轮式双足机器人精准跳高控制。由于系统存在欠驱动、非线性估计及跳跃过程中的瞬时冲击特性，精确控制跳高难度大。现实中机器人常跳得过高以确保安全，导致电机损耗增加、地面反作用力上升和能耗增大。为此，提出一种新型轮式双足跳跃动力学模型（W-JBD），虽效果良好但扭矩突变不适合真实机器人。因此进一步提出贝叶斯优化扭矩规划方法（BOTP），无需精确动力学模型即可在少数迭代中获得最优扭矩序列。该方法使跳高误差降低82.3%，能耗减少26.9%，且扭矩曲线连续。在Webots仿真平台验证有效，结合W-JBD缩小搜索空间后，平均仅需40次迭代即可快速收敛。二者协同可实现在有限实验次数下对真实机器人实现精准高度控制。
原文摘要 · Abstract (English)
This paper mainly studies the accurate height jumping control of wheeled-bipedal robots based on torque planning and energy consumption optimization. Due to the characteristics of underactuated, nonlinear estimation, and instantaneous impact in the jumping process, accurate control of the wheeled-bipedal robot's jumping height is complicated. In reality, robots often jump at excessive height to ensure safety, causing additional motor loss, greater ground reaction force and more energy consumption. To solve this problem, a novel wheeled-bipedal jumping dynamical model(W-JBD) is proposed to achieve accurate height control. It performs well but not suitable for the real robot because the torque has a striking step. Therefore, the Bayesian optimization for torque planning method(BOTP) is proposed, which can obtain the optimal torque planning without accurate dynamic model and within few iterations. BOTP method can reduce 82.3% height error, 26.9% energy cost with continuous torque curve. This result is validated in the Webots simulation platform. Based on the torque curve obtained in the W-JBD model to narrow the searching space, BOTP can quickly converge (40 times on average). Cooperating W-JBD model and BOTP method, it is possible to achieve the height control of real robots with reasonable times of experiments.
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