Evolution and Adaptation of an Agent Driving a Scale Model of a Car with Obstacle Avoidance Capabilities
Ivan Tanev, Michal Joachimczak and Katsunori Shimohara
Simulation of Adaptive Behavior 2006 (SAB 2006)
Rome, Italy, 25-29 September 2006
Summary
We present an approach for evolutionary design of the driving style of an agent, remotely operating a scale model of a car running in a fastest possible way. The agent per-ceives the environment from a video camera and conveys its actions to the car via standard radio control transmitter. In order to cope with the video feed latency we propose an anticipa-tory modeling in which the agent considers its current actions based on the anticipated intrin-sic (rather than currently available, outdated) state of the car and its surrounding. The driving style is first evolved offline on a software model of the car and then adapted online to the real world. An online evolutionary adaptation of the offline-obtained best styles to the needs to avoid a small obstacle results in lap times that are virtually the same as the best lap times achieved on the same track without obstacles. Presented work is a step towards the automated design of the control software of remotely operated vehicles capable to find an optimal solu-tion to various tasks in different environmental situations. The results, also, can be seen as an attempt to explore the feasibility of developing a framework of adaptive racing games in which the human competes against a computer with matching capabilities, both operating physical, scale models of cars.