Biologically Inspired Mobile Robot Control Robust to Hardware Failures and Sensor Noise

Some bacteria present a movement which can be modeled as a biased random walk. Biased random walk can be used also for artificial creatures as a very simple and robust control policy for tasks like goal reaching. In this paper, we show how a very simple control law based on random walk is able to guide mobile robot equipped with an omnidirectional camera toward a target without any knowledge about the robot’s actuators or about the robot’s camera parameters. We verified, by several simulation experiments, the robustness of the random biased control law with respect to failures of robot’s actuators or sensor damages. These damages are similar to the ones which can occur during a RoboCup match. The tests show that the optimal behavior is obtained using a bias which is roughly proportional to the random walk step, with a coefficient dependent on the physical structure of the robot, on its actuators and on and its sensors after the damage. Finally, we validated the proposed approach with experiments in the real world with a wheeled robot performing a goal reaching task in a Middle-Size RoboCup field without any prior knowledge on the actuators and without any calibration of the very noisy omnidirectional camera mounted on the robot.