Automatic Path Search for Roving Robot Using Reinforcement Learning

Rapid advances in robot technology have been made in recent years. In connection with these advances, robots are expected to be utilized in a variety of places and environments. This study describes, (1) a method which allows a robot to measure the location of its destination in the real world based on an image obtained from a single camera, and (2) a method of navigating a robot to a destination which is selected by a user on a display showing the forward robot view. Consideration is also given to cases in which there are obstacles between the robot and the destination. Through the use of reinforcement learning, which is considered a promising candidate among autonomous control techniques, the roving robot tries to find the shortest way to the destination based on information concerning the locations of obstacles and the destination. This study also describes an image-based method of measuring a selected location, the results from a simulation of path finding using reinforcement learning, and the results from an experiment of navigation in a real environment. Finally, a summary of the main conclusions is provided.