Laser & Optoelectronics Progress, Volume. 60, Issue 2, 0233001(2023)

3D Modeling System of Mobile Robot Based on Virtual Reality in Real Environment

Zhongyuan Guo1,2, Feng Xu1,2、*, Guiyang Wang1, Dongying Yu1,2, and Yunxuan Cui1,2
Author Affiliations
  • 1School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, Sichuan, China
  • 2Sichuan Key Laboratory of Robot Technology Used for Special Environment, Mianyang 621010, Sichuan, China
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    Traditional virtual reality (VR) technology generates indoor three-dimensional (3D) map models using artificial modeling, which has the challenges of slow speed and deviation between the model and real object scale. Therefore, this study proposes a real environment 3D modeling system for mobile robots based on VR. First, the indoor high-precision dense 3D point cloud map can be rapidly obtained by using visual simultaneous localization and mapping (SLAM) technology. Second, the 3D point cloud can be reconstructed into the indoor 3D model through the surface reconstruction algorithm and imported into unity 3D. Next, the indoor 3D model is placed in the 3D virtual environment with the VR equipment's aid. Finally, the relocation of the mobile robot to the indoor environment is achieved by visual SLAM technology, and the pose of the robot in the model is mapped in real time to complete the interaction. Using visual SLAM technology to build the 3D map model is quick, solves the problem of scene scale deviation, and attains the reuse of map. Simultaneously, VR technology also allows operators to obtain a strong sense of immersion to better understand the working environment of the robot.

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    Zhongyuan Guo, Feng Xu, Guiyang Wang, Dongying Yu, Yunxuan Cui. 3D Modeling System of Mobile Robot Based on Virtual Reality in Real Environment[J]. Laser & Optoelectronics Progress, 2023, 60(2): 0233001

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    Paper Information

    Category: Vision, Color, and Visual Optics

    Received: Sep. 17, 2021

    Accepted: Nov. 8, 2021

    Published Online: Jan. 6, 2023

    The Author Email: Xu Feng (xufeng@swust.edu.cn)

    DOI:10.3788/LOP212553

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