Nalazite se na CroRIS probnoj okolini. Ovdje evidentirani podaci neće biti pohranjeni u Informacijskom sustavu znanosti RH. Ako je ovo greška, CroRIS produkcijskoj okolini moguće je pristupi putem poveznice www.croris.hr
izvor podataka: crosbi !

A Shadowcasting-Based Next-Best-View Planner for Autonomous 3D Exploration (CROSBI ID 305727)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Batinovic, Ana ; Ivanovic, Antun ; Petrovic, Tamara ; Bogdan, Stjepan A Shadowcasting-Based Next-Best-View Planner for Autonomous 3D Exploration // IEEE robotics & automation letters, 7 (2022), 2; 2969-2976. doi: 10.1109/lra.2022.3146586

Podaci o odgovornosti

Batinovic, Ana ; Ivanovic, Antun ; Petrovic, Tamara ; Bogdan, Stjepan

engleski

A Shadowcasting-Based Next-Best-View Planner for Autonomous 3D Exploration

In this paper, we address the problem of autonomous exploration of unknown environments with an aerial robot equipped with a sensory set that produces large point clouds, such as LiDARs. The main goal is to gradually explore an area while planning paths and calculating information gain in short computation time, suitable for implementation on an on-board computer. To this end, we present a planner that randomly samples viewpoints in the environment map. It relies on a novel and efficient gain calculation based on the Recursive Shadowcasting algorithm. To determine the Next-Best-View (NBV), our planner uses a cuboid-based evaluation method that results in an enviably short computation time. To reduce the overall exploration time, we also use a dead end resolving strategy that allows us to quickly recover from dead ends in a challenging environment. Comparative experiments in simulation have shown that our approach outperforms the current state- of-the-art in terms of computational efficiency and total exploration time.

Aerial systems, perception and autonomy, autonomous agents, mapping

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

Podaci o izdanju

7 (2)

2022.

2969-2976

objavljeno

2377-3766

10.1109/lra.2022.3146586

Povezanost rada

Elektrotehnika, Računarstvo

Poveznice
Indeksiranost