A Multi-Modal Mapping Unit for Autonomous Exploration and Mapping of Underground Tunnels

被引:0
|
作者
Mascarich, Frank [1 ]
Khattak, Shehryar [1 ]
Papachristos, Christos [1 ]
Alexis, Kostas [1 ]
机构
[1] Univ Nevada, Autonomous Robots Lab, Reno, NV 89557 USA
关键词
D O I
暂无
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The ability of autonomous exploration and mapping using aerial robots in GPS-denied dark visually-degraded environments is critical in multiple applications including those of inspection, exploration, search and rescue in tunnel environments, monitoring of mines, and mapping underground voids. This paper presents the design of a multi-modal mapping unit tailored to such missions. When combined with our previous work of the receding horizon volumetric exploration path planner, the unit enables robotic autonomy in such environments without any prior knowledge of the environment. The multi- modal mapping unit detailed in this work tightly synchronizes visible light cameras with inertial sensors as well as LEDs that flash only when the cameras' shutters are open. When used in conjunction with a visual-inertial odometry pipeline, the multi-modal mapping unit enables reliable robot navigation in darkness. With the further support of multiple miniature Time-of-Flight 3D depth sensors, dense and accurate maps are derived. The proposed system was evaluated using field experiments involving exploration and mapping of a railroad tunnel in conditions of darkness. Results show that a consistent and dense mapping of such challenging degraded visual environments was achieved.
引用
收藏
页数:7
相关论文
共 50 条
  • [41] Geographic mapping with unsupervised multi-modal representation learning from VHR images and POIs
    Bai, Lubin
    Huang, Weiming
    Zhang, Xiuyuan
    Du, Shihong
    Cong, Gao
    Wang, Haoyu
    Liu, Bo
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2023, 201 : 193 - 208
  • [42] A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping
    Gao, Peng
    Dong, Hao-Ming
    Liu, Si-Man
    Fan, Xue-Ru
    Jiang, Chao
    Wang, Yin-Shan
    Margulies, Daniel
    Li, Hai-Fang
    Zuo, Xi-Nian
    SCIENTIFIC DATA, 2022, 9 (01)
  • [43] Multi-modal temporal attention models for crop mapping from satellite time series
    Garnot, Vivien Sainte Fare
    Landrieu, Loic
    Chehata, Nesrine
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2022, 187 : 294 - 305
  • [44] Multi-Modal Lidar Dataset for Benchmarking General-Purpose Localization and Mapping Algorithms
    Li Qingqing
    Yu Xianjia
    Queralta, Jorge Pena
    Westerlund, Tomi
    2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, : 3837 - 3844
  • [45] MULTI-MODAL VISION TRANSFORMERS FOR CROP MAPPING FROM SATELLITE IMAGE TIME SERIES
    Follath, Theresa
    Mickisch, David
    Hemmerling, Jan
    Erasmi, Stefan
    Schwieder, Marcel
    Demir, Begiim
    IGARSS 2024-2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, IGARSS 2024, 2024, : 1937 - 1941
  • [46] MULTI-MODAL DEEP LEARNING FOR MULTI-TEMPORAL URBAN MAPPING WITH A PARTLY MISSING OPTICAL MODALITY
    Hafner, Sebastian
    Ban, Yifang
    IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 6843 - 6846
  • [47] Learning Autonomous Exploration and Mapping with Semantic Vision
    Zhi, Xiangyang
    He, Xuming
    Schwertfeger, Soren
    PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON IMAGE, VIDEO AND SIGNAL PROCESSING (IVSP 2019), 2019, : 8 - 15
  • [48] Mapping Multi-Modal Brain Connectome for Brain Disorder Diagnosis via Cross-Modal Mutual Learning
    Yang, Yanwu
    Ye, Chenfei
    Guo, Xutao
    Wu, Tao
    Xiang, Yang
    Ma, Ting
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2024, 43 (01) : 108 - 121
  • [49] Efficient Autonomous Exploration and Mapping in Unknown Environments
    Feng, Ao
    Xie, Yuyang
    Sun, Yankang
    Wang, Xuanzhi
    Jiang, Bin
    Xiao, Jian
    SENSORS, 2023, 23 (10)
  • [50] Deep Multi-modal Object Detection for Autonomous Driving
    Ennajar, Amal
    Khouja, Nadia
    Boutteau, Remi
    Tlili, Fethi
    2021 18TH INTERNATIONAL MULTI-CONFERENCE ON SYSTEMS, SIGNALS & DEVICES (SSD), 2021, : 7 - 11