🤖 AI Summary
When traversing uneven terrain, wheeled bipedal robots exhibit vertical head oscillations in the world frame due to ground-induced disturbances, degrading onboard sensor accuracy and risking payload damage. To address this, we propose a model-based ground contact force estimation algorithm integrated with an admittance control strategy, enabling— for the first time—active head stabilization of wheeled bipedal robots in the world coordinate frame. Our approach leverages a 6-DOF dynamic model to estimate ground reaction forces online and dynamically regulate head orientation in real time. Simulation results demonstrate millisecond-level computational latency for force estimation; head displacement fluctuations are reduced by 82%. The system exhibits high robustness and superior dynamic response across sloped, stepped, and randomly irregular terrains, significantly enhancing terrain adaptability and perceptual reliability.
📝 Abstract
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.