Path Planning for an Autonomous Electric Vehicle based on Attractors Dynamics and Differential Evolution

This paper introduces a way of planning the path for autonomous electric vehicles (AEV)or robots using attractors dynamics through a numeric optimization problem, which is solved by a meta-heuristic algorithm called differential evolution (DE). The information given by the attractor dynamic approach (ADA)is used as a set of variables into an optimization problem with constraints, based on these variables, some restrictions are activated in order to find the best possible path, minimizing the distance between the vehicle and the target position and avoiding obstacles at the same time, without prior information on the environment.