System Design of the Ultra Mobility Vehicle: A Driving, Balancing, and Jumping Bicycle Robot
Benjamin Bokser, Daniel Gonzalez, Aaron Preston, Alex Bahner, Annika Wollschläger, Arianna Ilvonen, Asa Eckert-Erdheim, Ashwin Khadke, Bilal Hammoud, Dean Molinaro, Fabian Jenelten, Henry Mayne, Howie Choset, Igor Bogoslavskyi, Itic Tinman, James Tigue, Jan Preisig, Kaiyu Zheng, Kenny Sharma, Kim Ang
- 发表年份
- 2026
- 访问权限
- 开放获取
摘要
Trials cyclists and mountain bike riders can hop, jump, balance, and drive on one or both wheels. This versatility allows them to achieve speed and energy-efficiency on smooth terrain and agility over rough terrain. Inspired by these athletes, we present the design and control of a robotic platform, Ultra Mobility Vehicle (UMV), which combines a bicycle and a reaction mass to move dynamically with minimal actuated degrees of freedom. We employ a simulation-driven design optimization process to synthesize a spatial linkage topology with a focus on vertical jump height and momentum-based balancing on a single wheel contact. Using a constrained Reinforcement Learning (RL) framework, we demonstrate zero-shot transfer of diverse athletic behaviors, including track-stands, jumps, wheelies, rear wheel hopping, and front flips. This 23.5 kg robot is capable of high speeds (8 m/s) and jumping on and over large obstacles (1 m tall, or 130% of the robot's nominal height).
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