Obstacle-avoidance navigation by an autonomous vehicle inspired by a bat biosonar strategy

Abstract

An autonomous vehicle controlled using real-time obstacle-avoidance algorithms and ultrasound was constructed to understand the active sensing system of the bat. The vehicle was designed to mimic bat behavior in which 1) the outgoing pulse was emitted toward the obstacle detected by the previous echo (obstacle aiming) and 2) the interpulse interval was adjusted using the distance to the detected object. As a result, the obstacle-aiming system facilitated obstacle avoidance by keeping the obstacle in the center of the beam sight of the vehicle. Behavioral experiments involving a bat avoiding obstacles demonstrated that the bat responds to multiple echoes and then decides the direction of the next outgoing pulse. Based on this behavior, a multi-object-detection navigation system was proposed to enable a vehicle to move in more complicated space that it failed to navigate previously. Our findings suggest that the bat behavioral strategies provide new perspectives for engineering involving simple sensing.