A CPU-GPU hybrid system of environment perception and 3D terrain reconstruction for unmanned ground vehicle

Wei Song, Shuanghui Zou, Yifei Tian, Su Sun, Simon Fong, Kyungeun Cho, Lvyang Qiu

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

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.

Original languageEnglish
Pages (from-to)1445-1456
Number of pages12
JournalJournal of Information Processing Systems
Volume14
Issue number6
DOIs
StatePublished - 2018

Keywords

  • 3D reconstruction
  • Driving awareness
  • Environment perception
  • Unmanned ground vehicle

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