Journal of Computer Applications ›› 2022, Vol. 42 ›› Issue (10): 3268-3274.DOI: 10.11772/j.issn.1001-9081.2021081522
• Frontier and comprehensive applications • Previous Articles Next Articles
Zhenghong QIN, Ran LIU, Yufeng XIAO, Kaixiang CHEN, Zhongyuan DENG, Tianrui DENG
Received:
2021-08-26
Revised:
2021-11-29
Accepted:
2021-12-03
Online:
2022-01-07
Published:
2022-10-10
Contact:
Ran LIU
About author:
QIN Zhenghong, ,born in 1996, M. S. candidate. Her research interests include WiFi localization, Simultaneous Localization And Mapping (SLAM).Supported by:
秦正泓, 刘冉, 肖宇峰, 陈凯翔, 邓忠元, 邓天睿
通讯作者:
刘冉
作者简介:
第一联系人:秦正泓(1996—),女,四川广安人,硕士研究生,主要研究方向:WiFi定位、同步定位与地图构建(SLAM)基金资助:
CLC Number:
Zhenghong QIN, Ran LIU, Yufeng XIAO, Kaixiang CHEN, Zhongyuan DENG, Tianrui DENG. Simultaneous localization and mapping for mobile robots based on WiFi fingerprint sequence matching[J]. Journal of Computer Applications, 2022, 42(10): 3268-3274.
秦正泓, 刘冉, 肖宇峰, 陈凯翔, 邓忠元, 邓天睿. 基于WiFi指纹序列匹配的机器人同步定位与地图构建[J]. 《计算机应用》唯一官方网站, 2022, 42(10): 3268-3274.
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URL: https://www.joca.cn/EN/10.11772/j.issn.1001-9081.2021081522
组别 | 高斯/m | 指纹序列/m | 高斯+指纹序列(加干扰)/m | ||||
---|---|---|---|---|---|---|---|
无干扰 | 删除部分AP | 高斯噪声3 | 高斯噪声5 | ||||
第一组 | 0.05 | 4.17 | 3.85 | 3.83 | 4.01 | 4.05 | 3.78 |
0.10 | 4.01 | 3.23 | 3.19 | 3.35 | 3.39 | 3.41 | |
0.20 | 4.43 | 3.43 | 3.09 | 3.48 | 3.02 | 3.11 | |
0.30 | 4.21 | 3.47 | 3.41 | 3.50 | 3.33 | 3.36 | |
0.40 | 4.40 | 3.56 | 3.45 | 3.97 | 3.58 | 3.88 | |
0.50 | 4.45 | 4.12 | 3.98 | 4.33 | 4.17 | 4.20 | |
0.60 | 5.75 | 5.82 | 5.68 | 5.69 | 4.99 | 5.55 | |
0.70 | 18.99 | 18.99 | 18.99 | 18.99 | 18.99 | 18.99 | |
第二组 | 0.05 | 14.78 | 13.85 | 12.13 | 13.66 | 12.56 | 13.18 |
0.10 | 9.15 | 5.63 | 5.27 | 5.88 | 5.14 | 6.23 | |
0.20 | 3.91 | 2.67 | 2.36 | 2.82 | 2.41 | 2.61 | |
0.30 | 3.88 | 2.83 | 2.65 | 2.74 | 2.57 | 2.78 | |
0.40 | 4.19 | 3.88 | 3.02 | 3.51 | 3.32 | 3.65 | |
0.50 | 4.44 | 4.95 | 4.13 | 4.37 | 3.99 | 4.27 | |
0.60 | 8.89 | 8.10 | 7.79 | 7.98 | 7.86 | 7.83 | |
0.70 | 10.12 | 10.12 | 10.12 | 10.12 | 10.12 | 10.12 |
Tab. 1 Influence of different loop closure detection methods and vs on SLAM algorithm accuracy
组别 | 高斯/m | 指纹序列/m | 高斯+指纹序列(加干扰)/m | ||||
---|---|---|---|---|---|---|---|
无干扰 | 删除部分AP | 高斯噪声3 | 高斯噪声5 | ||||
第一组 | 0.05 | 4.17 | 3.85 | 3.83 | 4.01 | 4.05 | 3.78 |
0.10 | 4.01 | 3.23 | 3.19 | 3.35 | 3.39 | 3.41 | |
0.20 | 4.43 | 3.43 | 3.09 | 3.48 | 3.02 | 3.11 | |
0.30 | 4.21 | 3.47 | 3.41 | 3.50 | 3.33 | 3.36 | |
0.40 | 4.40 | 3.56 | 3.45 | 3.97 | 3.58 | 3.88 | |
0.50 | 4.45 | 4.12 | 3.98 | 4.33 | 4.17 | 4.20 | |
0.60 | 5.75 | 5.82 | 5.68 | 5.69 | 4.99 | 5.55 | |
0.70 | 18.99 | 18.99 | 18.99 | 18.99 | 18.99 | 18.99 | |
第二组 | 0.05 | 14.78 | 13.85 | 12.13 | 13.66 | 12.56 | 13.18 |
0.10 | 9.15 | 5.63 | 5.27 | 5.88 | 5.14 | 6.23 | |
0.20 | 3.91 | 2.67 | 2.36 | 2.82 | 2.41 | 2.61 | |
0.30 | 3.88 | 2.83 | 2.65 | 2.74 | 2.57 | 2.78 | |
0.40 | 4.19 | 3.88 | 3.02 | 3.51 | 3.32 | 3.65 | |
0.50 | 4.44 | 4.95 | 4.13 | 4.37 | 3.99 | 4.27 | |
0.60 | 8.89 | 8.10 | 7.79 | 7.98 | 7.86 | 7.83 | |
0.70 | 10.12 | 10.12 | 10.12 | 10.12 | 10.12 | 10.12 |
第一组 | 第二组 | |||
---|---|---|---|---|
高斯 | 指纹序列 | 高斯 | 指纹序列 | |
0.05 | 233 518 | 196 523 | 279 074 | 218 567 |
0.10 | 124 120 | 95 621 | 123 973 | 85 472 |
0.20 | 46 252 | 31 258 | 24 355 | 18 865 |
0.30 | 24 453 | 19 843 | 9 366 | 7 546 |
0.40 | 9 300 | 4 562 | 3 045 | 1 488 |
0.50 | 1 770 | 612 | 619 | 257 |
0.60 | 35 | 0 | 32 | 0 |
0.70 | 0 | 0 | 0 | 0 |
0.80 | 0 | 0 | 0 | 0 |
0.90 | 0 | 0 | 0 | 0 |
Tab. 2 Influence of loop closure detection methods and vs on loop closure number
第一组 | 第二组 | |||
---|---|---|---|---|
高斯 | 指纹序列 | 高斯 | 指纹序列 | |
0.05 | 233 518 | 196 523 | 279 074 | 218 567 |
0.10 | 124 120 | 95 621 | 123 973 | 85 472 |
0.20 | 46 252 | 31 258 | 24 355 | 18 865 |
0.30 | 24 453 | 19 843 | 9 366 | 7 546 |
0.40 | 9 300 | 4 562 | 3 045 | 1 488 |
0.50 | 1 770 | 612 | 619 | 257 |
0.60 | 35 | 0 | 32 | 0 |
0.70 | 0 | 0 | 0 | 0 |
0.80 | 0 | 0 | 0 | 0 |
0.90 | 0 | 0 | 0 | 0 |
(n,m) | 第一组( | 第二组( | ||||||
---|---|---|---|---|---|---|---|---|
无干扰 | 删除部分AP | 高斯噪声3 | 高斯噪声5 | 无干扰 | 删除部分AP | 高斯噪声3 | 高斯噪声5 | |
(10,15) | 3.49 | 3.64 | 3.55 | 3.59 | 2.77 | 2.96 | 3.12 | 3.25 |
(20,25) | 3.09 | 3.35 | 3.02 | 3.11 | 2.36 | 2.74 | 2.41 | 2.61 |
(30,35) | 3.42 | 3.29 | 3.49 | 3.58 | 2.86 | 2.81 | 2.39 | 2.58 |
(40,45) | 3.66 | 3.93 | 3.85 | 3.90 | 3.00 | 3.37 | 2.81 | 3.24 |
(50,55) | 3.54 | 4.01 | 3.97 | 4.12 | 3.15 | 3.50 | 3.37 | 3.59 |
Tab. 3 Influence of length of fingerprint sequence on SLAM algorithm accuracy under Gauss+fingerprint sequence method
(n,m) | 第一组( | 第二组( | ||||||
---|---|---|---|---|---|---|---|---|
无干扰 | 删除部分AP | 高斯噪声3 | 高斯噪声5 | 无干扰 | 删除部分AP | 高斯噪声3 | 高斯噪声5 | |
(10,15) | 3.49 | 3.64 | 3.55 | 3.59 | 2.77 | 2.96 | 3.12 | 3.25 |
(20,25) | 3.09 | 3.35 | 3.02 | 3.11 | 2.36 | 2.74 | 2.41 | 2.61 |
(30,35) | 3.42 | 3.29 | 3.49 | 3.58 | 2.86 | 2.81 | 2.39 | 2.58 |
(40,45) | 3.66 | 3.93 | 3.85 | 3.90 | 3.00 | 3.37 | 2.81 | 3.24 |
(50,55) | 3.54 | 4.01 | 3.97 | 4.12 | 3.15 | 3.50 | 3.37 | 3.59 |
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