System design of the Ultra Mobility Vehicle: A driving, balancing, and jumping bicycle robot

Abstract

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), that combines a bicycle and a reaction mass to move dynamically with minimal actuated degrees of freedom. We used 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 deep 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-kilogram robot is capable of high speeds ( v max = 8 meters per second) and jumping on and over large obstacles (1-meter tall or 130% of the robot’s nominal height).