An improved Adaptive Monte Carlo Localization Algorithm Fused with Ultra Wideband Sensor

被引：0
|
作者：
Wang, Yang [2 ,3 ]
Zhang, Weimin [1 ,2 ,3 ]
Li, Fangxing [1 ,2 ,3 ]
Shi, Yongliang [1 ,2 ,3 ]
Chen, Zhuo [1 ,2 ,3 ]
Nie, Fuyu [1 ,2 ,3 ]
Zhu, Chi [4 ]
Huang, Qiang [1 ,2 ,3 ]
机构：
[1] Beijing Inst Technol, Sch Mech Engn, Beijing, Peoples R China
[2] Minist Educ, Beijing Inst Technol, Key Lab Biomimet Robots & Syst, Beijing, Peoples R China
[3] Beijing Adv Innovat Ctr Intelligent Robots & Syst, Beijing, Peoples R China
[4] Maebashi Inst Technol Gunma, Dept Syst Life Engn, Maebashi, Gunma, Japan
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS AND ITS SOCIAL IMPACTS (ARSO) | 2019年
基金：
国家重点研发计划;
关键词：
MCL; UWB; Fusion;
D O I：
10.1109/arso46408.2019.8948809
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, an optimization algorithm is proposed to achieve efficient global positioning and recovery from kidnap in open environment. Due to the ability of some sensors to achieve global localization efficiently, such as Ultra-Wideband (UWB), Wi-Fi, and camera, we take the UWB sensor to improve AMCL. By comparing various ranging and positioning schemes, we propose a specific analysis of UWB ranging and positioning methods, as well as an observation model for integrating UWB information. Finally, the efficiency of this method is proved by comparison with AMCL. Thus, the time to locate globally is about 3 seconds, while more than 100 seconds using AMCL.
引用
收藏
页码：421 / 426
页数：6
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