Feedback Control for Autonomous Riding of Hovershoes by a Cassie Bipedal Robot
This work addresses multi-modal locomotion for bipedal robots, allowing them to navigate complex environments, though it appears incremental as it builds on existing control and planning methods.
The paper tackles the problem of enabling a bipedal robot to autonomously ride Hovershoes over diverse terrains, achieving capabilities such as balancing, velocity regulation, and navigation through obstacles like slopes and stairs with experimental validation.
Motivated towards achieving multi-modal locomotion, in this paper, we develop a framework for a bipedal robot to dynamically ride a pair of Hovershoes over various terrain. Our developed control strategy enables the Cassie bipedal robot to interact with the Hovershoes to balance, regulate forward and rotational velocities, achieve fast turns, and move over flat terrain, slopes, stairs, and rough outdoor terrain. Our sensor suite comprising of tracking and depth cameras for visual SLAM as well as our Dijkstra-based global planner and timed elastic band-based local planning framework enables us to achieve autonomous riding on the Hovershoes while navigating an obstacle course. We present numerical and experimental validations of our work.