DOI QR코드

DOI QR Code

Obstacle Detection for Unmanned Ground Vehicle on Uneven Terrain

비평지용 무인차량을 위한 장애물 탐지

Choe, Tok Son;Joo, Sang Hyun;Park, Yong Woon;Park, Jin Bae
최덕선;주상현;박용운;박진배

  • Received : 2015.10.26
  • Accepted : 2016.01.07
  • Published : 2016.02.01

Abstract

We propose an obstacle detection algorithm for unmanned ground vehicle on uneven terrain. The key ideas of the proposed algorithm are the use of two-layer laser range data to calculate the gradient of a target, which is characterized as either ground or obstacles. The proposed obstacle detection algorithm includes 4-steps: 1) Obtain the distance data for each angle from multiple lidars or a multi-layer scan lidar. 2) Calcualate the gradient for each angle of the uneven terrain. 3) Determine ground or obstacle for each angle on the basis of reference gradient. 4) Generate a new distance data for each angle for a virtual laser scanner. The proposed algorithm is verified by various experiments.

Keywords

Obstacle detection;Unmanned ground vehicle;Uneven terrain

References

  1. Badal, S., Ravela, S., Draper, B., and Hanson, A., "A practical obstacle detection and avoidance system", Proceedings of the Second IEEE Workshop on Applications of Computer Vision, pp. 97-104, 1994.
  2. Broggi, A., Bertozzi, M., Fascioli, A., Bianco, C. G. L., and Piazzi, A., "Visual perception of obstacles and vehicles for platooning", IEEE Transactions on Intelligent Transportation Systems, 1(3), 164-176, 2000. https://doi.org/10.1109/6979.892153
  3. Lacaze, A., Murphy, K., and DelGiorno, M., "Autonomous mobility for the Demo III experimental unmanned vehicles" in Assoc. for Unmanned Vehicle Systems Int. Conf. on Unmanned Vehicles (AUVSI), 2002.
  4. Hong, T., Abrams, M., Chang, T., and Shneier, M. O., "An intelligent world model for autonomous off-road driving", Computer Vision and Image Understanding, 2002.
  5. Manz, M., Himmelsbach, M., Luettel, T. and Wuensche, H.-J., "Detection and tracking of road networks in rural terrin by fusing vision and LIDAR", Int. Conf. on Intelligent Robots and Systems, San Fransisco, CA, USA, pp. 4562-4568, 25-30 Sep. 2011.
  6. Habermann, D., Hata, A., Wolf, D. and Osorio, F. S., "3D point clouds segmentation for autonomous ground vehicle", 2013 III Brazilian Symposium on Computing Systems Engineering, Niteroi, pp. 143-148, Dec. 4-8 2013.

Acknowledgement

Grant : 단위로봇 경로계획/제어기술(자율주행 7레벨)

Supported by : 국방과학연구소, LIG Nex1