Robust Localization of Mobile Robot in Industrial Environments With Non-Line-of-Sight Situation
| Autor: | Hong-Xiang Xu, Li-Ting Dong, Xingzhen Bai, Jinchang Zhang, Leijiao Ge, Jun Yan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
non-line-of-sight (NLOS)
General Computer Science wireless localization Computer science Real-time computing General Engineering Process (computing) 020206 networking & telecommunications Mobile robot 02 engineering and technology Sample (graphics) Non-line-of-sight propagation Genetic algorithm 0202 electrical engineering electronic engineering information engineering Mobile robots 020201 artificial intelligence & image processing General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering Electrical and Electronic Engineering Particle filter lcsh:TK1-9971 improved particle filter |
| Zdroj: | IEEE Access, Vol 8, Pp 22537-22545 (2020) |
| ISSN: | 2169-3536 |
| Popis: | This paper proposes a new robust localization of mobile robot (MR) in the complex environment with non-line-of-sight (NLOS) situation. Two novel measurement processing strategies are proposed to achieve accurate recognition of NLOS measurements. In addition, an improved particle filter (PF) based on genetic algorithm (GA) is presented, where GA is introduced to improve the resampling process so PF can effectively overcome sample degradation while reducing computational complexity. The effectiveness of the algorithm is evaluated through a series of experiments and simulations. The proposed method demonstrates better accuracy than traditional methods, and can realize real-time, accurate and stable positioning of MRs in different types of NLOS environments. |
| Databáze: | OpenAIRE |
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