Motion Planning of Non-Holonomic Wheeled Robots Using Modified Firefly Algorithm

The subject of motion planning for non-holonomic wheeled mobile robots moving on the plane and in particular the use of fuzzy and evolutionary strategies for achieving such motion tasks has been dealt with in this paper. The specific robotic system considered is a vehicle whose kinematics approximates that of a car. The configuration of this robot is represented by position and orientation of its main body in the plane and by angles of the steering wheels. Two control inputs are available for motion control viz. the velocity and the steering angle command. This treatise attempts to covers in a realistic manner many of the existing robotic vehicles by means of real hardware experiment. Moreover, the car-like robot is one of the simplest non-holonomic vehicles that displays the general characteristics and constrained maneuverability of systems with non-holonomicity. The car-like robotic system designed is able to parameterize its positions and surroundings and plan to execute trajectories through it while avoiding obstacles in its path. The control methods proposed in this paper does not require precise mathematical modeling of every aspect a car like system. The fuzzy controller provides a linguistic method of putting control task into action. The path planning task has been taken care of by an adaptive bio-inspired strategy commonly known as 'Firefly Algorithm'.