Off-Road Detection Analysis for Autonomous Ground Vehicles: A Review.
autonomous ground vehicles
drivable ground
negative obstacles
off-road environment
positive obstacles
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
03 Nov 2022
03 Nov 2022
Historique:
received:
21
09
2022
revised:
28
10
2022
accepted:
31
10
2022
entrez:
11
11
2022
pubmed:
12
11
2022
medline:
15
11
2022
Statut:
epublish
Résumé
When it comes to some essential abilities of autonomous ground vehicles (AGV), detection is one of them. In order to safely navigate through any known or unknown environment, AGV must be able to detect important elements on the path. Detection is applicable both on-road and off-road, but they are much different in each environment. The key elements of any environment that AGV must identify are the drivable pathway and whether there are any obstacles around it. Many works have been published focusing on different detection components in various ways. In this paper, a survey of the most recent advancements in AGV detection methods that are intended specifically for the off-road environment has been presented. For this, we divided the literature into three major groups: drivable ground and positive and negative obstacles. Each detection portion has been further divided into multiple categories based on the technology used, for example, single sensor-based, multiple sensor-based, and how the data has been analyzed. Furthermore, it has added critical findings in detection technology, challenges associated with detection and off-road environment, and possible future directions. Authors believe this work will help the reader in finding literature who are doing similar works.
Identifiants
pubmed: 36366160
pii: s22218463
doi: 10.3390/s22218463
pmc: PMC9657584
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Références
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