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Because the problem of the extended Kalman filter localization and mapping algorithm priori noise model is difficult to manage, this paper proposes an improved wild geese particle swarm algorithm based on the fuzzy adaptive Kalman filter localization and mapping algorithm. We take advantage of the the fractional calculus to improve particle speed of evolution, and make use of chaos to improve the initialization of the particle and the precocious one when processing. The improvement of wild geese particle swarm algorithm is shown in convergence rate and avoiding premature, then they can improve geese particle swarm algorithm for fuzzy adaptive extended Kalman filter localization and mapping algorithm training. in contrast with geese particle swarm algorithm fuzzy adaptive extended Kalman filter simultaneous localization and mapping algorithm, the new algorithm positioning and composition has greatly improved.
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Keywords:
- simultaneous localization and mapping /
- geese PSO /
- fractional calculus /
- Chaos
[1] Xu D J, He R, Shen F, Gai M 2011 Systems Engineering and Electronics 33 2696 (in Chinese) [徐定杰, 贺瑞, 沈峰, 盖猛 2011 系统工程与电子技术 33 2696]
[2] Chandima D P, Keigo W, Kiyotaka L 2008 Artifical Life and Robotics 13 155
[3] Gao Y G, Wang S C, Liu Z G, Zhao X 2012 Journal of Chinese Inertial Technology 20 315 (in Chinese) [高运广, 王仕成, 刘志国, 赵欣 2012 中国惯性技术学报 20 315]
[4] Ramazan H, Mohammad A N, Mohammad T 2010 International Journal of Computer Science Issues 7 15
[5] Amitava C, Fumitoshi M 2006 Proceedings of The 3rd IEEE Conference on Intelligent Systems Varna, Bulgaria, September, 4-6 2006 04
[6] Amitava C, Fumitoshi M 2010 Expert Systems with Application 37 5542
[7] Fu A L, Lei X J 2008 7th Word Congress on Intelligent Control and Automation Chongqing, Peoples R China, Jun 25-27, 2008 7045
[8] Solteiro P E J, Tenreiro M J A 2010 Nonlinear Dyn. 61 295
[9] Dong J P 2009 Ph. D. Dissertation (Jinan: Shandong University) (in Chinese) [董建平 2009 博士学位论文 (济南: 山东大学)]
[10] Micael S C, Rui P R, Fonseca N M, Tenreiro J A 2012 SIViP 6 343
[11] Zhou J, Liu Y A, Wu F, Zhang H G, Zu Y X 2011 Acta Phys. Sin. 60 9 (in Chinese) [周杰, 刘元安, 吴帆, 张洪光, 俎云霄 2011 物理学报 60 9]
[12] Pan X Y, Zhao H M 2012 Acta Phys. Sin. 61 20 (in Chinese) [潘欣裕, 赵鹤鸣 2012 物理学报 61 20]
[13] Indranil P, Anna K, Saptarshi D, Sevket D 2012 Nonlinear Dyn. 70 2445
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[1] Xu D J, He R, Shen F, Gai M 2011 Systems Engineering and Electronics 33 2696 (in Chinese) [徐定杰, 贺瑞, 沈峰, 盖猛 2011 系统工程与电子技术 33 2696]
[2] Chandima D P, Keigo W, Kiyotaka L 2008 Artifical Life and Robotics 13 155
[3] Gao Y G, Wang S C, Liu Z G, Zhao X 2012 Journal of Chinese Inertial Technology 20 315 (in Chinese) [高运广, 王仕成, 刘志国, 赵欣 2012 中国惯性技术学报 20 315]
[4] Ramazan H, Mohammad A N, Mohammad T 2010 International Journal of Computer Science Issues 7 15
[5] Amitava C, Fumitoshi M 2006 Proceedings of The 3rd IEEE Conference on Intelligent Systems Varna, Bulgaria, September, 4-6 2006 04
[6] Amitava C, Fumitoshi M 2010 Expert Systems with Application 37 5542
[7] Fu A L, Lei X J 2008 7th Word Congress on Intelligent Control and Automation Chongqing, Peoples R China, Jun 25-27, 2008 7045
[8] Solteiro P E J, Tenreiro M J A 2010 Nonlinear Dyn. 61 295
[9] Dong J P 2009 Ph. D. Dissertation (Jinan: Shandong University) (in Chinese) [董建平 2009 博士学位论文 (济南: 山东大学)]
[10] Micael S C, Rui P R, Fonseca N M, Tenreiro J A 2012 SIViP 6 343
[11] Zhou J, Liu Y A, Wu F, Zhang H G, Zu Y X 2011 Acta Phys. Sin. 60 9 (in Chinese) [周杰, 刘元安, 吴帆, 张洪光, 俎云霄 2011 物理学报 60 9]
[12] Pan X Y, Zhao H M 2012 Acta Phys. Sin. 61 20 (in Chinese) [潘欣裕, 赵鹤鸣 2012 物理学报 61 20]
[13] Indranil P, Anna K, Saptarshi D, Sevket D 2012 Nonlinear Dyn. 70 2445
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