动态环境下基于延迟语义的RGB-D SLAM算法

doi:10.16451/j.cnki.issn1003-6059.202310008

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Abstract Visual simultaneous localization and mapping(SLAM) cannot be applied to dynamic environment. The mainstream solution is to combine segmentation network and SLAM. However, real-time operation of SLAM systems is not guaranteed due to the processing speed constraints of segmentation network. Therefore, a RGB-D SLAM algorithm based on delayed semantic information in dynamic environment is proposed. Firstly, tracking and segmentation threads run in parallel. To obtain the latest delayed semantic information, a cross-frame segmentation strategy is employed for image processing, and real-time semantic information for the current frame is generated by the tracking thread according to the delaysemantic information. Then, the dynamic point set of the current frame is selected and the real motion state of the prior dynamic object in the environment is determined by combining successful tracking count and epipolar constraints. When the object is determined as moving, the object area is further subdivided into rectangular grids, and dynamic feature points are removed with the grid as the minimum unit. Finally, the camera pose is tracked by static feature points and an environment map is constructed. Experiments on TUM RGB-D dynamic scene dataset and real scenes show that the proposed algorithm performs well and its effectiveness is verified.

Key words： Simultaneous Localization and Mapping(SLAM) Dynamic Environment Instance Segmentation Network Delayed Semantic Information Grid Clustering

Received: 08 September 2023

ZTFLH:

TP391

Fund:National Natural Science Foundation of China(No.61872327), Natural Science Foundation of Anhui Province(No.2308085MF203),University Synergy Innovation Program of Anhui Province(No.GXXT-2022-055), Major Project of Key Laboratory of Flight Techniques and Flight Safety of CAAC(No.FZ2022ZZ02), Open Fund of Key Laboratory of Flight Techniques and Flight Safety of CAAC(No.FZ2022KF09)

Corresponding Authors: FANG Baofu, Ph.D., associate professor. His research interests include intelligent robot systems.

About author:: WANG Hao, Ph.D., professor. His research interests include distributed intelligent systems and robots.ZHOU Shenchao, master student. His research interests include visual SLAM.

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Cite this article:

WANG Hao,ZHOU Shenchao,FANG Baofu. RGB-D SLAM Algorithm Based on Delayed Semantic Information in Dynamic Environment[J]. Pattern Recognition and Artificial Intelligence, 2023, 36(10): 953-966.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202310008 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2023/V36/I10/953

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