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A CPU-GPU hybrid system of environment perception and 3D terrain reconstruction for unmanned ground vehicle
Wei Song1; Shuanghui Zou1; Yifei Tian2; Su Sun1; Simon Fong2; Kyungeun Cho3; Lvyang Qiu3
2018-12
Source PublicationJournal of Information Processing Systems
ISSN2092-805X
Volume14Issue:6Pages:1445-1456
Abstract

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

KeywordDriving Awareness Environment Perception Unmanned Ground Vehicle 3d Reconstruction
DOI10.3745/JIPS.02.0099
URLView the original
Indexed ByESCI
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems
WOS IDWOS:000457174500013
PublisherKOREA INFORMATION PROCESSING SOC, 1002HO YONGSUNGBIZTEL 314-1 2GA HANKANGRO YONGSAN-GU, SEOUL, 140-750, SOUTH KOREA
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Cited Times [WOS]:3   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorWei Song
Affiliation1.Dept. of Digital Media Technology North China University of Technology Beijing, China
2.Dept. of Computer and Information Science, University of Macau, Macau, China
3.Dept. of Multimedia Engineering, Dongguk University, Seoul, Korea
Recommended Citation
GB/T 7714
Wei Song,Shuanghui Zou,Yifei Tian,et al. A CPU-GPU hybrid system of environment perception and 3D terrain reconstruction for unmanned ground vehicle[J]. Journal of Information Processing Systems,2018,14(6):1445-1456.
APA Wei Song,Shuanghui Zou,Yifei Tian,Su Sun,Simon Fong,Kyungeun Cho,&Lvyang Qiu.(2018).A CPU-GPU hybrid system of environment perception and 3D terrain reconstruction for unmanned ground vehicle.Journal of Information Processing Systems,14(6),1445-1456.
MLA Wei Song,et al."A CPU-GPU hybrid system of environment perception and 3D terrain reconstruction for unmanned ground vehicle".Journal of Information Processing Systems 14.6(2018):1445-1456.
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