Occupancy Grids have been widely used for perception of the environment as they allow to model the obstacles in the scene, as well as free and unknown space. Recently, there has been a growing interest in the unknown space due to the necessity of better understanding the situation. Although Occupancy Grids have received numerous extensions over the years to address emerging needs, currently, few works go beyond the delimitation of the unknown space area and seek to incorporate additional information. This work builds upon the already well-established LiDAR-based Dynamic Occupancy Grid to introduce a complementary Categorized Grid that conveys its estimation using semantic labels while adding new insights into the possible causes of unknown space. The proposed categorization first divides the space by occupancy and then further categorizes the occupied and unknown space. Occupied space is labeled based on its dynamic state and reliability, while the unknown space is labeled according to its possible causes, whether they stem from the perception system's inherent constraints, limitations induced by the environment, or other causes. The proposed Categorized Grid is showcased in real-world scenarios demonstrating its usefulness for better situation understanding.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Categorized Grid and Unknown Space Causes for LiDAR-Based Dynamic Occupancy Grids


    Contributors:


    Publication date :

    2024-09-24


    Size :

    8405574 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Environment Recognition with FMCW-LiDAR-based Dynamic Occupancy Grid Mapping

    Okuya, Tsubasa / Yoneda, Masaki / Ogawa, Takashi | IEEE | 2023


    Extended Occupancy Grid Method for Modeling Unknown Dynamic Environments

    Webber, R. E. / Zhang, Y. / Defence Research Establishment Suffield | British Library Conference Proceedings | 1991


    Parking space detection with hierarchical dynamic occupancy grids

    Schmid, M. R. / Ates, S. / Dickmann, J. et al. | IEEE | 2011


    Parking Space Detection with Hierarchical Dynamic Occupancy Grids

    Schmid, M.R. / Ates, S. / Dickmann, J. et al. | British Library Conference Proceedings | 2011


    LIDAR-based Dynamic Environment Modeling and Tracking Using Particles Based Occupancy Grid

    Li, Qiaohui / Dai, Bin / Fu, Hao | British Library Conference Proceedings | 2016