Effectiveness of 2D Path Planning in Real Time using Fuzzy Logic

Abstract

The effectiveness of 2D path planning of a UAV using fuzzy logic for the purpose of decision making in real time is explored in this paper. Previous work has shown that by using a fuzzy inference system, an agent can navigate an unknown environment. It does this by taking information about obstacles (if within the agent’s sensing range) and target location, and outputting a change in heading angle and speed. Often there are scenarios in which it is desirable for an aircraft to redirect its path midflight. These situations can involve threats, changing mission objectives, and/ or be very complex; with multiple and moving obstacles. A system that can handle these varying conditions rapidly and efficiently is imperative to the future of autonomous aircraft. A fuzzy logic approach is used here for its ability to imitate human heuristics and simplicity to implement. The effectiveness of this methodology is analyzed by comparing it to an optimal path planning approach. While the optimal path will give either the shortest path (or time to a target), control algorithms are incapable of being re-tasked. Presented here is a fuzzy inference system (FIS) for path planning with obstacle avoidance. This FIS has been tweaked and tested for robustness by comparing it to other 2D path planning methods on numerous obstacle environments.