通过力估计实现轮式双足机器人头部稳定，提升复杂地形下的传感器精度。
Head Stabilization for Wheeled Bipedal Robots via Force-Estimation-Based Admittance Control
- 基于模型的地面力估计算法，实时获取接触力信息。
- 采用阻抗控制使头部在世界坐标系中保持稳定，减少垂直晃动。
- 适合需高精度感知的野外探测类机器人，提升地形适应能力。
轮式双足机器人正成为野外勘探的灵活平台。然而，不平地形引起的头部不稳定会降低机载传感器精度或损坏脆弱载荷。现有研究多聚焦于移动平台的稳定，却忽视了头部在世界坐标系中的主动稳定，导致垂直振荡影响整体稳定性。为此，我们为6自由度轮式双足机器人开发了一种基于模型的地面力估计算法。利用这些力估计值，实现了增强地形适应性的阻抗控制。仿真实验验证了力估计算法的实时性能以及机器人在不平地形上行驶时的鲁棒性。
原文摘要 · Abstract (English)
Wheeled bipedal robots are emerging as flexible platforms for field exploration. However, head instability induced by uneven terrain can degrade the accuracy of onboard sensors or damage fragile payloads. Existing research primarily focuses on stabilizing the mobile platform but overlooks active stabilization of the head in the world frame, resulting in vertical oscillations that undermine overall stability. To address this challenge, we developed a model-based ground force estimation method for our 6-degree-of-freedom wheeled bipedal robot. Leveraging these force estimates, we implemented an admittance control algorithm to enhance terrain adaptability. Simulation experiments validated the real-time performance of the force estimator and the robot's robustness when traversing uneven terrain.
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