Controlling bicycle using deep deterministic policy gradient algorithm

摘要

Controlling a bicycle without human interaction is still a challenge for researchers. Most of the studies on this topic focus on the physical area of bicycle or designing controllers based on automatic control knowledge such as feedback controller, LQR controller. This study focuses on applying a state-of-the-art deep reinforcement learning algorithm called Deep Deterministic Policy Gradient to control the bicycle. The bicycle can use the learned controller (agent) to keep balancing or reach a specified goal.