Planning optimal trajectories for mobile robots using an evolutionary method with fuzzy components

This study describes a generation of globally time optimal trajectories for a mobile robot in predefined environment. The primary task in the study is to apply Differential Evolution (DE) method for definition of globally time-optimal trajectories under environmental and dynamical constraints. The planned trajectories are composed of line segments and curve segments. The structures of the curve segments are determined by using only two parameters such as a turn angle 6 and a translation velocity on the curve v_{t_start}. All possible curve segments in parameters range θ∈ (0, π] ^ο, v_{t_start} [0,40] inch and a_{t_turn} ∈[-a_{t_max}a_{t_max}] inch/sec² form a curve segments set. Then DE, is used to find time optimal trajectory from this set. Experimental results are given and the results are shown successfully.