Fast Cost-aware Lazy-Theta over Euclidean distance functions for 3D planning of aerial robots in building-like environments

Abstract

This paper presents a fast cost-aware any-angle path planning algorithm for aerial robots in 3D building-like environments. The approach integrates Euclidean Distance Fields (EDF) and Lazy Theta* algorithm to compute safe and smooth paths. We show how to consider the analytical proper-ties of EDFs for polygonal obstacles to get an approximation of the cost along the line of sight segments of the planner, reducing the computational requirements. Numerous tests in a realistic building-like environment are performed to evaluate the proposed algorithm with respect to other heuristic search algorithms considering the distance cost by using an EDF. The results show that the proposed algorithm considerably reduces the computation time in indoor and outdoor environments enabling fast, safe and smooth paths.