A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Multi-Sensor Fusion for Navigation and Mapping in Autonomous Vehicles: Accurate Localization in Urban Environments
Tekijät: Qingqing Li, Jorge Peña Queralta, Tuan Nguyen Gia, Zhuo Zou, Tomi Westerlund
Kustantaja: WORLD SCI PUBL CO INC
Julkaisuvuosi: 2020
Journal: Unmanned Systems
Tietokannassa oleva lehden nimi: UNMANNED SYSTEMS
Lehden akronyymi: UNMANNED SYST
Vuosikerta: 8
Numero: 3
Aloitussivu: 229
Lopetussivu: 237
Sivujen määrä: 9
ISSN: 2301-3850
eISSN: 2301-3869
DOI: https://doi.org/10.1142/S2301385020500168
Verkko-osoite: https://doi.org/10.1142/S2301385020500168
The combination of data from multiple sensors, also known as sensor fusion or data fusion, is a key aspect in the design of autonomous robots. In particular, algorithms able to accommodate sensor fusion techniques enable increased accuracy, and are more resilient against the malfunction of individual sensors. The development of algorithms for autonomous navigation, mapping and localization have seen big advancements over the past two decades. Nonetheless, challenges remain in developing robust solutions for accurate localization in dense urban environments, where the so-called last-mile delivery occurs. In these scenarios, local motion estimation is combined with the matching of real-time data with a detailed pre-built map. In this paper, we utilize data gathered with an autonomous delivery robot to compare different sensor fusion techniques and evaluate which are the algorithms providing the highest accuracy depending on the environment. The techniques we analyze and propose in this paper utilize 3D lidar data, inertial data, GNSS data and wheel encoder readings. We show how lidar scan matching combined with other sensor data can be used to increase the accuracy of the robot localization and, in consequence, its navigation. Moreover, we propose a strategy to reduce the impact on navigation performance when a change in the environment renders map data invalid or part of the available map is corrupted.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
