Abstract

Obstacle avoidance is a critical aspect of control for a mobile robot when navigating towards a goal in an unfamiliar environment. Where traditional methods for obstacle avoidance depend heavily on path planning to reach a specific goal location whilst avoiding obstacles, the method proposed uses an adaption of a potential fields algorithm to successfully avoid obstacles whilst the robot is being guided to a non-specific goal location. Details of a generalised finite state machine based control algorithm that enable the robot to pursue a dynamic goal location, whilst avoiding obstacles and without the need for specific path planning, are presented. We have developed a novel potential fields algorithm for obstacle avoidance for use within Robot Operating Software (ROS) and made it available for download within the open source community. We evaluated the control algorithm in a high-speed predator-prey scenario in which the predator could successfully catch the moving prey whilst avoiding collision with all obstacles within the environment.