Path Planning for Autonomous Vehicles

An evolutionary algorithm-based framework, a combination of modified breeder genetic algorithms incorporating characteristics of classic genetic algorithms, is utilized to design an offline/online path planner for unmanned aerial vehicles (UAVs) autonomous navigation. The path planner calculates a curved path line with desired characteristics in a three–dimensional (3-D) rough terrain environment, represented using B-Spline curves, with the coordinates of its control points being the evolutionary algorithm artificial chromosome genes.

Given a 3-D rough environment and assuming flight envelope restrictions, two problems are solved:

i) UAV navigation using an offline planner in a known environment

ii) UAV navigation using an online planner in a completely unknown environment.

The offline planner produces a single B-Spline curve that connects the starting and target points with a predefined initial direction. The online planner, based on the offline one, is given on-board radar readings which gradually produces a smooth 3-D trajectory aiming at reaching a predetermined target in an unknown environment; the produced trajectory consists of smaller B-Spline curves smoothly connected. Both planners have been tested under different scenarios, and they have been proven effective in guiding a UAV to its final destination, providing near-optimal curved paths quickly and efficiently. Index Terms—3-D path planning, B-splines, evolutionary algorithms, navigation, UAV.

Article by : Lobhas Patankar