Collision Recognition and Direction Changes Using Fuzzy Logic for Small Scale Fish Robots by Acceleration Sensor Data

For natural and smooth movement of small scale fish robots, collision detection and direction changes are important. Typical obstacles are walls, rocks, water plants and other nearby robots for a group of small scale fish robots and submersibles that have been constructed in our lab. Two of 2-axes acceleration sensors are employed to measure the three components of collision angles, collision magnitudes, and the angles of robot propulsion. These data are integrated using fuzzy logic to calculate the amount of propulsion direction changes. Because caudal fin provides the main propulsion for a fish robot, there is a periodic swinging noise at the head of a robot. This noise provides a random acceleration effect on the measured acceleration data at the collision instant. We propose an algorithm based on fuzzy logic which shows that the MEMS-type accelerometers are very effective to provide information for direction changes.