Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 5
1315-1318

Unscented FastSLAM algorithm based on adaptive fading unscented particle filter

Wang Qian1a
Zeng Qingjun1a
Zhang Jiamin1a
Yao Jinyi1a
Zhou Qirun1b
Dai Xiaoqiang1a,2
1. a. School of Electronic & Information, b. School of Computer Science & Engineering, Jiangsu University of Science & Technology, Zhenjiang Jiangsu 212003, China
2. Jiangsu Shiptek Automation Technology Co, Ltd, Zhenjiang Jiangsu 212003, China
DOI: 10.19734/j.issn.1001-3695.2017.11.0742

Abstract

For the unscented fast simultaneous localization and mapping(Unscented FastSLAM) algorithm in robot navigation, the sample particle was degraded due to resampling, which led to the problem of reduced accuracy. In order to solve the problem, this paper developed an improved Unscented FastSLAM algorithm based on adaptive fading unscented particle filter. The algorithm merged the unscented particle filter with the fading filter to form adaptive proposed distribution function. At the same time, the particles were optimally combined according to their weight, and only unstable particles were resampled. Through these two aspects could make the system highly adaptive, while ensuring the diversity of particles and mitigating the degradation of particles. Simulation experiments show that compared with Unscented FastSLAM algorithm, the proposed algorithm can achieve higher SLAM estimation accuracy with fewer particles, which greatly reduces the complexity of SLAM algorithm.

Foundation Support

国家自然科学基金资助项目(11574120)
江苏省自然科学基金资助项目(BK20160564)
江苏省国际科技合作项目(BZ2016031)
镇江市国际科技合作项目(GJ2015008)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.11.0742
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 5
Section: Algorithm Research & Explore
Pages: 1315-1318
Serial Number: 1001-3695(2019)05-008-1315-04

Publish History

[2019-05-05] Printed Article

Cite This Article

王倩, 曾庆军, 张家敏, 等. 基于自适应渐消无迹粒子滤波的Unscented FastSLAM算法 [J]. 计算机应用研究, 2019, 36 (5): 1315-1318. (Wang Qian, Zeng Qingjun, Zhang Jiamin, et al. Unscented FastSLAM algorithm based on adaptive fading unscented particle filter [J]. Application Research of Computers, 2019, 36 (5): 1315-1318. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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