Szczegóły publikacji
Opis bibliograficzny
Real-time 3D mapping in isolated industrial terrain with use of mobile robotic vehicle / Tomasz BURATOWSKI, Jerzy Garus, Mariusz GIERGIEL, Andrii KUDRIASHOV // Electronics [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2079-9292. — 2022 — vol. 11 iss. 13 art. no. 2086, s. 1–11. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 9–11, Abstr. — Publikacja dostępna online od: 2022-07-03
Autorzy (4)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 140962 |
|---|---|
| Data dodania do BaDAP | 2022-08-01 |
| Tekst źródłowy | URL |
| DOI | 10.3390/electronics11132086 |
| Rok publikacji | 2022 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Electronics |
Abstract
Simultaneous localization and mapping (SLAM) is a dual process responsible for the ability of a robotic vehicle to build a map of its surroundings and estimate its position on that map. This paper presents the novel concept of creating a 3D map based on the adaptive Monte-Carlo location (AMCL) and the extended Kalman filter (EKF). This approach is intended for inspection or rescue operations in a closed or isolated area where there is a risk to humans. The proposed solution uses particle filters together with data from on-board sensors to estimate the local position of the robot. Its global position is determined through the Rao–Blackwellized technique. The developed system was implemented on a wheeled mobile robot equipped with a sensing system consisting of a laser scanner (LIDAR) and an inertial measurement unit (IMU), and was tested in the real conditions of an underground mine. One of the contributions of this work is to propose a low-complexity and low-cost solution to real-time 3D-map creation. The conducted experimental trials confirmed that the performance of the three-dimensional mapping was characterized by high accuracy and usefulness for recognition and inspection tasks in an unknown industrial environment.