期刊文献+

动态环境中移动机器人地图构建的研究进展 被引量:11

Advances on Map Building with Mobile Robots in Dynamic Environments
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摘要 大部分现有的移动机器人地图构建方法都是基于静态环境的假设,而实际应用中移动机器人的工作环境是随时间变化的。综述了动态环境中移动机器人地图构建的最新研究进展,介绍了基于地图、基于运动和基于跟踪的检测动态障碍物的各种方法,分析比较了动态环境中移动机器人过滤运动障碍物传感器观测信息和结合运动障碍物传感器观测信息构建环境地图的主要方法,并总结了各种方法的优缺点。探讨了动态环境中移动机器人地图构建存在的难点问题,并展望了该领域的研究方向。 Most existing map building methods for mobile robots are based on the assumption of static environments, while the working environments of mobile robots in real applications change over time. Advances on map building with a mobile robot in dynamic environments are overviewed. Various methods of detecting moving obstacles for a mobile robot such as map-based, motion-based and track-based methods are introduced. Approaches to map building in dynamic environments with a mobile robot which filter out and integrate sensor observations of moving obstaclos are analyzed and their advantages and disadvantages are further summarized. The difficult issues of map building with a mobile robot in dynamic environments are discussed and future research of this field is also proposed.
出处 《控制工程》 CSCD 2007年第3期231-235,269,共6页 Control Engineering of China
基金 国家自然科学基金重点资助项目(60234030) 国家基础研究基金资助项目(A1420060159)
关键词 动态环境 运动障碍物检测 地图构建 移动机器人 定位 dynamic environments moving obstacle detection map building mobile robots localization
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参考文献36

  • 1Thrun S.Robotic mapping:a survey[R].Pittsburgh:School of Computer Science,Carnegie Mellon University,2002.
  • 2Biswas R,Limketkai B,Sanner S,et al.Towards object mappingin non-stationary environments with mobile robots[C].Lausanne:International Conference on Intelligent Robots and Systems,2002.
  • 3Wolf D F,Sukhatme G S.Towards mapping dynamic environments[C].Portugal:International Conference on Advanced Robotics,2003.
  • 4Wolf D F,Sukhatme G S.Online simultaneous localization and mapping in dynamic environments[C].New Orleans:IEEE International Conference on Robotics and Automation,2004.
  • 5Wolf D F,Sukhatme G S.Mobile robot simultaneous localization and mapping in dynamic environments[J].Autonomous Robots,2005,19(1):53-65.
  • 6Wang C C,Thorpe C.Simultaneous localization and mapping with detection and tracking of moving objects[C].Washington DC:IEEE International Conference on Robotics and Automation,2002.
  • 7Hahnel D,Schulz D,Burgard W.Map building with mobile robots in populated environments[C].Lausanne:IEEE/RSJ International Conference on Intelligent Robots and Systems,2002.
  • 8Wang C C,Thorpe C,Thrun S.Online simultaneous localization and mapping with detection and tracking of moving objects:Theory and results from a ground vehicle in crowded urban areas[C].Taipei:IEEEInternational Conference on Robtics and Automation,2003.
  • 9Lindstrom M,Eklundh J O.Detecting and tracking moving objects froma mobile platform using a laser range scanner[C].Hawaii:International Conference on Intelligent Robots and Systems,2001.
  • 10Schulz D,Burgard W,Fox D,et al.Tracking multiple moving targets with a mobile robot using particle filters and statistical data association[C].Seoul:IEEE International Conference on Robtics and Automation,2001.

二级参考文献100

  • 1蒋新松.智能科学与智能技术[J].信息与控制,1994,23(1):38-39. 被引量:12
  • 2朱淼良,吴春明,张友军,金毅,李捷.基于多智能体的实时并发式智能机器人结构[J].高技术通讯,1995,5(10):20-24. 被引量:4
  • 3阎平凡.再励学习——原理、算法及其在智能控制中的应用[J].信息与控制,1996,25(1):28-34. 被引量:30
  • 4朱晓芸,杨建刚,何志钧.神经网络的多传感器数据融合基于新算法在障碍物识别中的应用[J].机器人,1997,19(3):166-172. 被引量:9
  • 5贺汉根 徐昕.增强学习在移动机器人导航控制中的应用[J].中南工业大学学报,2000,31:170-173.
  • 6徐昕.增强学习及其在移动机器人导航与控制中的应用[M].长沙:国防科技大学,2002..
  • 7张福学.机器人学智能机器人传感技术[M].电子工业出版社,. 1996.
  • 8[1]Jensfelt P, Cgrustebseb H. Laser based position acpuisition and tracking in an indoor environment[A]. Proceedings of IEEE International Symposium on Robotics and Automation[C]. Mexico: 1998,l. 331-338.
  • 9[2]Davison A J, Nobuyuki K. 3D simultaneous localization and map building using active vision for a robot moving on undulating terrain[A]. Proceedings of the IEEE International Conference on Computer Vision and Recognization[C]. Hawail: 2001,1. 384-391 .
  • 10[3]Se S, Lowe D, Little J. Vision-based mobile robot localization and mapping using scale-invariant features[A]. Proceedings of the IEEE International Conference on Robotics and Automation[C]. Korea: 2001. 2051-2058.

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