Lidar-based Traversable Region Detection in Off-road Environment

被引:0
|
作者
Liu, Tong [1 ]
Liu, Dongyu [1 ]
Yang, Yi [1 ]
Chen, Zhaowei [1 ]
机构
[1] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China
关键词
3D Lidar; Obstacles Detection; Traversable Region Detection; Off-road Environment; ROBOT;
D O I
10.23919/chicc.2019.8865250
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Traversable region detection is a fundamental problem in the field of autonomous driving. This paper proposes a fast method to detect obstacles and obtain the traversable region in the off-road environment. Our method takes advantage of both radial features and transverse features based on the high definition of 3D Lidar points. First, we manage Lidar points by scanning lines and sectors in the polar system at the same time. Then the most obstacles can be quickly detected by using radial features in the polar system. For the false detection, transverse features are applied to verify the results. Finally, the constrained region within the nearest obstacle points in each sector defines the traversable region around the vehicle. Our method can detect positive obstacles, negative obstacles, and hanging obstacles in real-time. The experimental results show the robustness and accuracy of the proposed method in different kinds of off-road environments.
引用
收藏
页码:4548 / 4553
页数:6
相关论文
共 50 条
  • [1] Knowledge Distillation for Traversable Region Detection of LiDAR Scan in Off-Road Environments
    Kim, Nahyeong
    An, Jhonghyun
    SENSORS, 2024, 24 (01)
  • [2] LiDAR-based Terrain Recognition in Off-road Mobile Robot
    Wang, Xinao
    Walters, Joseph G.
    PROCEEDINGS OF THE 33RD INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS+ 2020), 2020, : 2590 - 2604
  • [3] A Novel Method of Traversable Area Extraction Fused With LiDAR Odometry in Off-road Environment
    Zhu, Baochang
    Xiong, Guangming
    Di, Huijun
    Ji, Kaijin
    Zhang, Xin
    Gong, Jianwei
    2019 IEEE INTERNATIONAL CONFERENCE OF VEHICULAR ELECTRONICS AND SAFETY (ICVES 19), 2019,
  • [4] LiDAR Based Traversable Regions Identification Method for Off-Road UGV Driving
    Shan, Yunxiao
    Fu, Yao
    Chen, Xiangchun
    Lin, Hongquan
    Zhang, Ziquan
    Lin, Jun
    Huang, Kai
    IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2024, 9 (02): : 3544 - 3557
  • [5] LiDAR-based robust localization for field autonomous vehicles in off-road environments
    Ren, Ruike
    Fu, Hao
    Xue, Hanzhang
    Li, Xiaohui
    Hu, Xiaochang
    Wu, Meiping
    JOURNAL OF FIELD ROBOTICS, 2021, 38 (08) : 1059 - 1077
  • [6] Lidar Based Off-road Negative Obstacle Detection and Analysis
    Larson, Jacoby
    Trivedi, Mohan
    2011 14TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2011, : 192 - 197
  • [7] From one to many: unsupervised traversable area segmentation in off-road environment
    Tang, Li
    Ding, Xiaqing
    Yin, Huan
    Wang, Yue
    Xiong, Rong
    2017 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (IEEE ROBIO 2017), 2017, : 787 - 792
  • [8] LIDAR-Based Road and Road-Edge Detection
    Zhang, Wende
    2010 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2010, : 845 - 848
  • [9] Off-Road LiDAR Intensity Based Semantic Segmentation
    Viswanath, Kasi
    Jiang, Peng
    Sujit, P. B.
    Saripalli, Srikanth
    EXPERIMENTAL ROBOTICS, ISER 2023, 2024, 30 : 608 - 617
  • [10] A tightly coupled LIDAR-IMU SLAM in off-road environment
    Zhang, Zhehua
    Liu, Haiou
    Qi, Jianyong
    Ji, Kaijin
    Xiong, Guangming
    Gong, Jianwei
    2019 IEEE INTERNATIONAL CONFERENCE OF VEHICULAR ELECTRONICS AND SAFETY (ICVES 19), 2019,