CTBC: Contact-Triggered Blind Climbing for Wheeled Bipedal Robots with Instruction Learning and Reinforcement Learning

Abstract: In recent years, wheeled bipedal robots have gained increasing attention due to their advantages in mobility, such as high-speed locomotion on flat terrain. However, their performance on complex environments (e.g., staircases) remains inferior to that of traditional legged robots. To overcome this limitation, we propose a general contact-triggered blind climbing (CTBC) framework for wheeled bipedal robots. Upon detecting wheel-obstacle contact, the robot triggers a leg-lifting motion to overcome the obstacle. By leveraging a strongly-guided feedforward trajectory, our method enables the robot to rapidly acquire agile leg-lifting skills, significantly enhancing its capability to traverse unstructured terrains. The approach has been experimentally validated and successfully deployed on LimX Dynamics' wheeled bipedal robot, Tron1. Real-world tests demonstrate that Tron1 can reliably climb obstacles well beyond its wheel radius using only proprioceptive feedback.