3D Mesh Compression and Transmission for Mobile Robotic Applications

Yang, Bailin; Wang, Xun; Li, Frederick W.B.; Xie, Binbo; Liang, Xiaohui; Jiang, Zhaoyi

Abstract

Mobile robots are useful for environment exploration and rescue operations. In such applications, it is crucial to accurately analyse and represent an environment, providing appropriate inputs for motion planning in order to support robot navigation and operations. 2D mapping methods are simple but cannot handle multilevel or multistory environments. To address this problem, 3D mapping methods generate structural 3D representations of the robot operating environment and its objects by 3D mesh reconstruction. However, they face the challenge of efficiently transmitting those 3D representations to system modules for 3D mapping, motion planning, and robot operation visualization. This paper proposes a quality-driven mesh compression and transmission method to address this. Our method is efficient, as it compresses a mesh by quantizing its transformed vertices without the need to spend time constructing an a-priori structure over the mesh. A visual distortion function is developed to govern the level of quantization, allowing mesh transmission to be controlled under different network conditions or time constraints. Our experiments demonstrate how the visual quality of a mesh can be manipulated by the visual distortion function.

Citation

Yang, B., Wang, X., Li, F. W., Xie, B., Liang, X., & Jiang, Z. (2016). 3D Mesh Compression and Transmission for Mobile Robotic Applications. International Journal of Advanced Robotic Systems, 13, Article 9. https://doi.org/10.5772/62035

• Journal Article Type: Article
• Acceptance Date: Nov 24, 2015
• Online Publication Date: Jan 26, 2016
• Publication Date: Jan 26, 2016
• Deposit Date: Jul 6, 2016
• Publicly Available Date: Jul 6, 2016
• Journal: International Journal of Advanced Robotic Systems
• Print ISSN: 1729-8806
• Electronic ISSN: 1729-8814
• Publisher: SAGE Publications
• Peer Reviewed: Peer Reviewed
• Volume: 13
• Article Number: 9
• DOI: https://doi.org/10.5772/62035
• Public URL: https://durham-repository.worktribe.com/output/1408155