Improved noise-adapted semantic SLAM
文献类型：会议论文
| 作者 | Zhang Z(张铮)1,3,4; Li DC(李德才)1,4 ; He YQ(何玉庆)1,2,4
|
| 出版日期 | 2021 |
| 会议日期 | November 8-11, 2021 |
| 会议地点 | Shenyang, China |
| 关键词 | Simultaneous location and mapping Semantic map Loss function Currentropy |
| 页码 | 1-5 |
| 英文摘要 | Based on the rapid development of deep learning, semantic information has gradually become a research hotspot in the field of SLAM (Simultaneous Location and Mapping). The noise problem caused by the environment and sensor results in the lack of consistency of semantic maps, and affects the accuracy of the algorithms. Loss function can adjust the weights assigned to the outliers, so it can reduce the impact of the outliers. However, the model of loss function used by most semantic SLAM is fixed and cannot adapt well to the changing environment. To solve this problem, this paper proposes a improved noise-adapted semantic SLAM, which uses Gaussian mixture correntropy weight function as loss function. Its model structure is variable by adjusting the parameters in changing environment, so it can adapte the noise distribution to the greatest extent, which is more conducive to reducing the weight of the algorithm for outliers and improving robustness to the outliers. Experiments on the public KITTI dataset show that the average relative translation and rotation error of the proposed method are reduced by 4.08% and 5.55%, the constructed semantic maps are more consistent. |
| 产权排序 | 1 |
| 会议录 | 2021 3rd International Conference on Industrial Artificial Intelligence (IAI)
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| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-6654-3517-8 |
| 源URL | [http://ir.sia.cn/handle/173321/29971]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Zhang Z(张铮) |
| 作者单位 | 1.Institute of Robotics and IntelligentManufacturing Innovation Chinese Academy of Sciences, shenyang 110016 China 2.Shenyang Institute of Automation(Guangzhou), Chinese Academy of Sciences, Guangzhou, 511458 China 3.University of Chinese Academy of Sciences, Beijing 100049, China 4.State Key Laboratory of Robotics,Shenyang Institute of Automation Chinese Academy of Sciences, shenyang,110016 China |
| 推荐引用方式 GB/T 7714 | Zhang Z,Li DC,He YQ. Improved noise-adapted semantic SLAM[C]. 见:. Shenyang, China. November 8-11, 2021. |
入库方式： OAI收割
来源：沈阳自动化研究所
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