1A2-K15 Adaptation of Leg/Wheeled Autonomous Rover by Reinforcement Learning(Space Robotics and Mecahtoronics)
Year: 2011
Type: conference-paper
Abstract: An autonomous rover that is used as planetary exploration or rescue should work in unknown environment. Therefore, the rover needs to adapt to a new environment and should have to change its moving form. Therefore, a rover needs to judge situations around it, and should select the best action autonomously. This study aims at creating a rover which gets the best motion strategy for the environment or the action to recover from a stacked situation autonomously by using legs and wheels. For the adaptation method, we use a Reinforcement Learning scheme. To investigate availability of rover and to see the effect of learning, this study prepared virtual situations to escape from irregular ground as the experiments. As a result, the effectiveness of the method was shown. However, the result shows that the parameter largely effects over learning speed and the quality of solutions.
Institution: The Future University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2627373571