Combining Local and Global Perception for Autonomous Navigation on Nano-UAVs

Autor:	Lamberti, Lorenzo, Rutishauser, Georg, Conti, Francesco, Benini, Luca
Rok vydání:	2024
Předmět:	Computer Science - Robotics Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
Popis:	A critical challenge in deploying unmanned aerial vehicles (UAVs) for autonomous tasks is their ability to navigate in an unknown environment. This paper introduces a novel vision-depth fusion approach for autonomous navigation on nano-UAVs. We combine the visual-based PULP-Dronet convolutional neural network for semantic information extraction, i.e., serving as the global perception, with 8x8px depth maps for close-proximity maneuvers, i.e., the local perception. When tested in-field, our integration strategy highlights the complementary strengths of both visual and depth sensory information. We achieve a 100% success rate over 15 flights in a complex navigation scenario, encompassing straight pathways, static obstacle avoidance, and 90{\deg} turns. Comment: 5 pages, 2 figures, 1 table, 1 video
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2403.11661 Zobrazit plný text záznamu View this record from Arxiv