RT Conference Proceedings
T1 Fast Cost-aware Lazy-Theta over Euclidean distance functions for 3D planning of aerial robots in building-like environments
A1 Cobano-Suárez, José-Antonio
A1 Rey Arcenegui, Rafael
A1 Merino, Luis
A1 Caballero, Fernando
K1 Costs
K1 Heuristic algorithms
K1 Euclidean distance
K1 Approximation algorithms
K1 Autonomous aerial vehicles
AB 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.
PB IEEE
YR 2022
FD 2022-12-26
LK https://hdl.handle.net/10433/23114
UL https://hdl.handle.net/10433/23114
LA en
NO 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Kyoto, Japan, 2022, pp. 13486-13493
NO This work has been supported by the Spanish Ministry of Science, Innovation and Universities (COMCISE RTI2018-100847-B-C22, MCIU/AEI/FEDER, UE) and by Programa Operativo FEDER Andalucia 2014-2020 and Consejeria de Econom´ıa y Conocimiento (PY20 00817 DeepBot).
NO Deporte e Informática
DS RIO
RD May 10, 2026