| Tao Yong (陶永)* **,Jiang Shan*,Ren Fan*,Wang Tianmiao*,Gao He*.[J].高技术通讯(英文),2021,27(3):227~237 |
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| An improved Gmapping algorithm based map construction method for indoor mobile robot |
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| DOI： |
| 中文关键词: |
| 英文关键词: complex indoor environment, single-line Lidar, map construction, improved Gmapping algorithm, sparse pose adjustment (SPA) optimization |
| 基金项目: |
| Author Name | Affiliation | | Tao Yong (陶永)* ** | (*School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, P.R.China)
(**Research Institute of Aero-Engine, Beihang University, Beijing 100191, P.R.China) | | Jiang Shan* | (*School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, P.R.China)
(**Research Institute of Aero-Engine, Beihang University, Beijing 100191, P.R.China) | | Ren Fan* | (*School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, P.R.China)
(**Research Institute of Aero-Engine, Beihang University, Beijing 100191, P.R.China) | | Wang Tianmiao* | (*School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, P.R.China)
(**Research Institute of Aero-Engine, Beihang University, Beijing 100191, P.R.China) | | Gao He* | (*School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, P.R.China)
(**Research Institute of Aero-Engine, Beihang University, Beijing 100191, P.R.China) |
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| 中文摘要: |
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| 英文摘要: |
| With the rapid development in the service, medical, logistics and other industries, and the increasing demand for unmanned mobile devices, mobile robots with the ability of independent mapping, localization and navigation capabilities have become one of the research hotspots. An accurate map construction is a prerequisite for a mobile robot to achieve autonomous localization and navigation. However, the problems of blurring and missing the borders of obstacles and map boundaries are often faced in the Gmapping algorithm when constructing maps in complex indoor environments. In this pursuit, the present work proposes the development of an improved Gmapping algorithm based on the sparse pose adjustment (SPA) optimizations. The improved Gmapping algorithm is then applied to construct the map of a mobile robot based on single-line Lidar. Experiments show that the improved algorithm could build a more accurate and complete map, reduce the number of particles required for Gmapping, and lower the hardware requirements of the platform, thereby saving and minimizing the computing resources. |
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