Simulation of optical flow and fuzzy based obstacle avoidance system for mobile robots
This work addresses obstacle avoidance for mobile robots, but it is incremental as it applies known methods (optical flow and fuzzy logic) in a simulation context.
The paper tackled obstacle avoidance for mobile robots by simulating a system that uses optical flow vectors as inputs to a fuzzy logic controller, resulting in effective navigation through complex static and dynamic environments.
Honey bees use optical flow to avoid obstacles effectively. In this research work similar methodology was tested on a simulated mobile robot. Simulation framework was based on VRML and Simulink in a 3D world. Optical flow vectors were calculated from a video scene captured by a virtual camera which was used as inputs to a fuzzy logic controller. Fuzzy logic controller decided the locomotion of the robot. Different fuzzy logic rules were evaluated. The robot was able to navigate through complex static and dynamic environments effectively, avoiding obstacles on its path.