Article

PPO Enables Autonomous Balance and Navigation Control for a Bicycle Robot in PyBullet

This study takes a bicycle robot with a reaction pendulum as its subject, derives the roll dynamics and the speed-dependent instability mechanism, and uses proximal policy optimization (PPO) to train coordinated control of the steering, rear wheel, and reaction pendulum. Experiments are carried out in PyBullet: natural fall, training, balancing, navigation, and disturbance recovery, concluding with obstacle-avoidance training.

Part of the event: Tutorial Released on PPO-Based Balancing and Navigation for Bicycle Robot

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