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.
Framework
Ablation Experiments in Sim
Hole-Escape
Stair-Climbing
Multi-Step Stairs
BibTeX
@misc{li2025ctbccontacttriggeredblindclimbing,
title={CTBC: Contact-Triggered Blind Climbing for Wheeled Bipedal Robots with Instruction Learning and Reinforcement Learning},
author={Rankun Li and Hao Wang and Qi Li and Zhuo Han and Yifei Chu and Linqi Ye and Wende Xie and Wenlong Liao},
year={2025},
eprint={2509.02986},
archivePrefix={arXiv},
primaryClass={cs.RO},
url={https://arxiv.org/abs/2509.02986 },
}