Improved noise-adapted semantic SLAM

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 机器人学研究室

	Improved noise-adapted semantic SLAM
	Zhang Z(张铮)2,3,4; Li DC(李德才)2,3; He YQ(何玉庆)1,2,3
	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)
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
内容类型	会议论文
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.Shenyang Institute of Automation(Guangzhou), Chinese Academy of Sciences, Guangzhou, 511458 China 2.State Key Laboratory of Robotics,Shenyang Institute of Automation Chinese Academy of Sciences, shenyang,110016 China 3.Institute of Robotics and IntelligentManufacturing Innovation Chinese Academy of Sciences, shenyang 110016 China 4.University of Chinese Academy of Sciences, Beijing 100049, 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.