人形機器人於電動機車之平衡與轉向控制

Abstract

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Autonomous vehicles and (humanoid) robotics are two fields that have greatly benefited from the rapid pace of development of deep learning systems. With intricate systems, it is possible to perform complex tasks and behaviors directly from raw sensor data. In light of recent developments in the aforementioned fields, it is necessary to start making efforts towards challenges that lie on their junction. From the perspective of humanoid robots, if we want to reach truly general-purpose robots it is of importance that they are capable of operating in any human environment. That includes the operation of vehicles, which we believe pose an interesting challenge for the state-of-the-art in both fields. This work focuses on the control and operation of a two-wheeled scooter using a large sized humanoid robot. A 3D model of the robot and scooter system was developed using CAD software, as well as physics based simulation environments. The subject of this study was the development of a steering-based control system. Two controllers were developed, analyzed and compared: a PID controller and a reinforcement learning control. Both controls were able to balance and track trajectories, and both performed better under different conditions. Advantages and limitations of applying these controllers to the real robot are also discussed.