Design of a Multi-Layer UAV Path Planner for Cluttered Environments

Abstract

There is an ever-increasing urge to integrate unmanned air systems (UAS) into the same airspace as manned aircraft. A step towards achieving this goal is to develop Sense and Avoid (SAA) capabilities to provide UAS with the required technology to detect and maneuver around traffic. This paper details an algorithm which enables an unmanned vehicle to reach a target waypoint by following the shortest path and avoiding fixed obstacles and moving traffic. In this context, a multi-layer planner is developed to enable planning of trajectories in cluttered environment containing fixed and moving obstacles. The planner is segmented into three layers; a high-level planner using Voronoi techniques that enable the planner to segregate individual obstacles into broad no-fly zones; a mid-level planner for representing the no-fly zones as convex hulls and a low-level planner that solves the resulting planning problem using mixed-integer linear programming (MILP), taking into account the convex no-fly zones and all neighboring traffic. Preliminary performance results suggest that the multi-layer planner is able to consistently identify optimal conflict-free paths in cluttered environments with execution speeds that are suitable for fast off-line planning operations.