Design And Optimization Of A Fuzzy Logic Controller For A Simulated Autonomous Robot

Abstract

Real-time obstacle avoidance is a desired behavior for a robot in an unknown environment. Intelligent control techniques have offered have offered a lot of opportunities to design efficient controllers for a safe navigation in a real-world environment. This paper presents some ideas that use fuzzy logic as a simple and intuitive way to design controllers for obstacle avoidance. Two second one is optimized using genetic algorithms, and both structures are tested in a simulation environment.