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基于视觉的多机器人协作SLAM问题 被引量:5

A survey on the cooperative SLAM problem of multi-robots systems based on visual
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摘要 视觉SLAM仅采用图像作为外部信息,用于估计机器人位置的同时构建环境地图。SLAM是机器人自主性的基本前提,如今在小动态环境采用激光或者声呐传感器构建2D地图得到较好地解决。然而动态、复杂和大范围下的SLAM仍存在问题,使用视觉作为基本的外部传感器是解决问题的一个新颖热门的研究方法。在视觉SLAM中使用计算机视觉技术,如特征检测、特征描述和特征匹配,图像识别和恢复,还存在很多改善的空间。本文在视觉SLAM领域的最新技术的基础上,对基于视觉的多机器人协作SLAM领域的前沿技术进行综述。 Visual SLAM using only images as external information estimates the robot position while building the environment map. SLAM is a basic prerequisite for autonomous robots. Now it has been solved by using a laser or sonar sensor to build 2D map in a small dynamic environment. However, in a dynamic, wide range and complex environment there are still problems to be solved, and the use of vision as the basic external sensor is a new area of research. The use of computer vision techniques in visual SLAM, such as feature detection, characterization, feature matching, image recognition and recovery, has still much room for improvement. The paper offers a brief overview on visual SLAM about the latest and easy to understand technologies in the field. Multi-robot systems have many advantages over a single robot, which can improve the precision of SLAM system, and better adapt to the dynamic and complex environment. This paper expounds the methods of multi-robot SLAM, with emphasis on the map fusion methods.
出处 《科技导报》 CAS CSCD 北大核心 2015年第23期110-115,共6页 Science & Technology Review
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参考文献58

  • 1Durrant-Whyte H, Bailey T. Simultaneous localization and mapping:part I[J]. Robotics & Automation Magazine, IEEE, 2006, 13(2): 99-110.
  • 2陈卫东,张飞.移动机器人的同步自定位与地图创建研究进展[J].控制理论与应用,2005,22(3):455-460. 被引量:60
  • 3Bailey T, Durrant-Whyte H. Simultaneous localization and mapping (SLAM): Part II[J]. Robotics & Automation Magazine, IEEE, 2006, 13(3): 108-117.
  • 4Paz L M, Pini6s P, Tard6s J D, et al. Large-scale 6-DOF SLAM with stereo-in-hand[J]. Robotics, IEEE Transactions on, 2008, 24(5): 946-957.
  • 5I)avistm A J, l~qd I I), Mohotl N I). ct ah MonoSLAM: I~eal-lime single camera SI,AM[.I]. I'altern Anahsis and Machine Inl~lligcnc~~. IEEE Transactions on, 2007. 29(6): 1052-1067.
  • 6Klein G, Murray D. Parallel tracking and mapping for small AR workspaces[C]//Mixed and Augmented Reality, 2007. ISMAR 2007. 6th IEEE and ACM International Symposium on. IEEE, 2007: 225-234.
  • 7S6ez J M, Escolano F. 6dof entropy minimization slam[C]//Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on. IEEE, 2006: 1548-1555.
  • 8Pini6s P, Tard6s J D. Large-scale slam building conditionally independent local maps: Application to monocular vision[J]. Robotics, IEEE Transactions on, 2008, 24(5): 1094-1106.
  • 9Engel J, Sch~ps T, Cremers D. LSD-SLAM: Large-scale direct monocular SLAM[My/Computer Vision-ECCV 2014. Springer International Publishing, 2014: 834-849.
  • 10Endres F, Hess J, Sturm J, et al. 3-d mapping with an rgb-d camera/J]. Robotics, IEEE Transactions on, 2014, 30(1): 177-187.

二级参考文献42

  • 1ELFES A, MORAVEC H. High resolution maps from wide angle sonar [C] // Proc of the IEEE lnt Conf on Robotics and Automation.St. Louis MO: IEEE Press, 1985: 116-121.
  • 2BORENSTEIN J,EVERETT H R,FENG L,et al.Mobile robot positioning: sensors and techniques [J]. J of Robotic Systems, Special Issue on Mobile Robots,1997,14(4):231 - 249.
  • 3SMITH R, SELF M, CHEESEMAN P. A stochastic map for uncertain spatial relationships [C]//Ptrg, of the 4th Int Symposium on Robotic Research. Cambridge MA: MIT Press, 1987:467 - 474.
  • 4THRUN S, BUCKEN A. Integrating grid-based and topological maps for mobile robot navigation [ C]//Proc of the 13th National Conf on Artificial Intelligence. Portland950.
  • 5ORIOLO G, ULIVI G,VENDITTELLI M.Fuzzy maps: A new tool for mobile robot perception and planning [J]. J of Robotic System,1997,14(3) : 179 - 197.
  • 6OHYA A,NAGASHIMA Y, YUTA S. Explore unknown environment and map construction using ultrasonic sensing of normal direction of walls [C]//Proc of the IEEE Int Conf on Robotics and Automation.San Diego CA: IEEE Press, 1994:485 - 492.
  • 7CHONG K S, KLEEMAN L. Mobile-robot map building from an advanced sonar array and accurate odometry [J].Int J of Robotics Research, 1999,18(1):20-36.
  • 8KORTENKAMP D, WEYNOUTH T. Topological mapping for mobile robots using a combination of sonar and vision sensing [C]//Proc of the 12th National Conf on Artificial Intelligence. Menlo Park: AAAI Press, 1994:979 - 984.
  • 9THRUN S,FOX D, BURGARD W. A probabilistic approach to concurrent mapping and localization for mobile robots [J]. Machine Learning, 1998,31 (1-3):29 - 53.
  • 10CASTELLANOS J.ANOS J A, NEIRA J, TARDOS J D. Multisensor fusion for simultaneous localization and map building [J].IEEE Trans on Robotics and Automation,2001,17(6):908- 914.

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