期刊文献+

基于视觉的移动机器人可通行区域识别研究综述 被引量:8

Research on vision-based traversable region recognition for mobile robots
下载PDF
导出
摘要 实现实时准确的可通行区域识别,是户外环境下移动机器人导航的重要组成部分。对基于视觉的移动机器人可通行区域识别研究进行了综述,首先介绍了移动机器人视觉导航常用的视觉系统,并从障碍物检测、地形分类两个方面介绍了该问题研究的进展,最后对该领域的技术发展趋势进行了探讨。 Realizing accurate and real-time traversable region recognition is indispensable, to mobile robots navigation in out- door environments. This paper gave a research on vision-based traversable region recognition for mobile robots. It introduced the common-used vision systems in vision-based mobile robots navigation and described the development of this issue from two aspects: obstacle detection and terrain classification. In the end, it proposed the prospective technical trends.
出处 《计算机应用研究》 CSCD 北大核心 2012年第6期2009-2013,共5页 Application Research of Computers
关键词 移动机器人 视觉 障碍物检测 地形分类 可通行区域 mobile robot vision obstacle detection terrain classification traversable region
  • 相关文献

参考文献50

  • 1LANGER D, ROSENBLATT J, HERBERT M. A behavior based system for off-road navigation[J]. IEEE Trans on Robotics and Auto- mation,1994,10(6) : 776-783.
  • 2UGUR E, SAHIN E. Traversability: a case study for learning and perceiving affordances in robots [ J ]. Adaptive Behavior: Animals, Animats, Software Agents, Robots, Adaptive Systems,2010, 18(3-4) : 258-284.
  • 3HELMICK D, ANGELOVA A, MATTHIES L. Ten:ain adaptive navigation for planetary rovers[ J ]. Journal o1 Field Robotics,2009,26 (4) : 391-410.
  • 4WILLIAMSON T A. A high-performance stereo vision system for obstacle detection[ D]. Pittsburgh: Camegie Mellon University, 1998.
  • 5ARGYROS A A, BEKRIS K E, ORPHANOUDAKIS S C, et al. Robot homing by exploiting panoramic vision[ J]. ,Journal of Autonomous Robots,2005,19( 1 ) : 7-25.
  • 6GURKAHRAMAN K, UNSAL E, CEBI Y. Omni-directional vision system with fibre grating device for obstacle detection[J], lET Computer Vision ,20ll ,5(5 ) : 267-281.
  • 7YUAN Pei-hsuan, YANG Kuo-feng, TSAI Wen-hsiang. Security monitoring around a video surveillance car with a pair of two-camera omni-directional imaging devices [ C ]//Proc of International Computer Symposium. 2010:325-330.
  • 8SU Lian-cheng, LUO Chuau-jiang, ZHU Feng. Obtaining obstacle information by an omni-directional stereo vision system [ C ]//Proc of IEEE International Conference on Information Acquisition. 2006 : 48- 52.
  • 9ULRICH I, NOURBAKHSH I. Appearance-based obstacle detection with monocular color vision [ C ]//Proc of the 17th AAAI National Conference on Artificial Intelligence. 2000: 886-871.
  • 10BHOITE A, BEKE N, NANDURI S, et al. Advanced situational awareness and obstacle detection using a monocular camera [ C ]// Proc of Western New York Image Processing Workshop. 2010: 30- 33.

二级参考文献104

  • 1胡斌,何克忠.计算机视觉在室外移动机器人中的应用[J].自动化学报,2006,32(5):774-784. 被引量:16
  • 2Bosch A, Zisserman A, Munoz X. Scene classification via PLSA. In: Proceedings of European Conference on Computer Vision. Graz, Austria: Springer, 2006. 517-530.
  • 3Oliva A, Torralba A. Scene-centered description from spatial envelope properties. In: Proceedings of the 2nd International Workshop on Biologically Motivated Computer Vision. Tubingen, Germany: Springer, 2002. 263-272.
  • 4Heitz G, Koller D. Learning spatial context: using stuff to find things. In: Proceedings of the European Conference on Computer Vision. Marseille, France: ECCV, 2008. 30-43.
  • 5Manduchi R, Castano A, Talukder A, Matthies L. Obstacle detection and terrain classification for autonomous off-road navigation. Autonomous Robots, 2005, 18(1): 81-102.
  • 6Huertas A, Matthies L, Rankin A. Stereo-besed tree traversability analysis for autonomous off-road navigation. In: Proceedings of the 7th IEEE Workshops on Application of Computer Vision. Washington D. C., USA: IEEE, 2005. 210-217.
  • 7Dima C, Hebert M, Stentz A T. Enabling learning from large datasets: applying active learning to mobile robotics. In: Proceedings of the International Conference on Robotics and Automation. New Orleans, USA: IEEE, 2004. 108-114.
  • 8Rosenberg C, Hebert M, Schneiderman H. Semi-supervised self-training of object detection models. In: Proceedings of the 7th IEEE Workshops on Application of Computer Vision. Washington D. C., USA: IEEE, 2005. 29-36.
  • 9Jansen P, van der Mark W, van den Heuvel J C, Groen F C A. Colour based off-road environment and terrain type classification. In: Proceedings of the IEEE Conference on Intelligent Transportation Systems. Vienna, Austria: IEEE, 2005. 216-221.
  • 10Karlsen R E, Witus G. Terrain understanding for robot navigation. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robotics and Systems. San Diego, USA: IEEE, 2007. 895-900.

共引文献26

同被引文献77

引证文献8

二级引证文献33

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部