期刊文献+

未知环境下的移动机器人定位及实时避障 被引量:3

Localization and Real-time Obstacle Avoidance of Mobile Robots in an Unknown Environment
下载PDF
导出
摘要 针对未知环境下移动机器人实时动态避障及定位问题,考虑里程计定位的无界累加误差和动态障碍物环境下实时障碍躲避需要,提出了一种可行的避障定位的策略。该策略融合了机器人内部传感器、里程计、电子罗盘和激光测距仪的同步和异步信息,合理地解决了常规定位过程中的方向迷失问题,时于静态和动态障碍物都能很好地实时躲避,具有很强的抗干扰性和较高的定位精度。实验证明了该方法的有效性和实用性。 Localization and real-time dynamic obstacle avoidance are studied for mobile robot's navigation in an unknown environment. Concemed with the existance of dynamic obstacle and the boundless cumulated error in odometer localization, an available strategy is presented. The synchronous and asynchronous information from all kind of sensors, odometer, compass, laser radar are fused, so that the direction-lost problem of conventional localization method is reasonably solved, and the real-time collision avoidance of static and dynamic obstacle are implemented successfully with stronger anti-interference ability and higher accuracy of localization. The experiment results show the effectiveness and practicality of the scheme.
出处 《控制工程》 CSCD 2007年第B05期162-165,共4页 Control Engineering of China
基金 国家自然科学基金(50575029)
关键词 移动机器人 避障 定位 mobile robot obstacle avoidance localization
  • 相关文献

参考文献12

  • 1Borenstein J,Everett H R,Feng L,et al.Mobile robot positioning:sensors and techniques[J].Journal of Robotics System,Special Issue on Mobile Robots,1997,14(4):231-249.
  • 2Chong K S,Kleeman L.Mobile-robot map building from an advanced sonar array and accurate odometer[J].Int Journal of Robotics Research,1999,18(1):20-36.
  • 3Korten K D,Weynouth T.Topological mapping for mobile robots using a combination of sonar and vision sensing[A].Proc of the 12th National Conf on Artificial Intelligence[C].Menlo Park:AAAI Press,1994.
  • 4Dissana Y G,Newman P,Clark S,et al.A solution to the simultaneous localization and map building(SLAM) problem[J].IEEE Trans on Robotics and Automation,2001,17(3):229-241.
  • 5Fujimori A,Nikiforik P N,Gupta M M.Adaptive navigation of mobile robots with obstacle avoidance[J].IEEE Transactions on Robotics and Automation,1997,13(4):596-601.
  • 6Koren Y,Borenstein J.Potential field methods and their inherent limitations for mobile robot navigation[C].California:IEEE Conf Robotics and Automation,1991.
  • 7Maaref H,Barret C.Sensor-based fuzzy navigation of an autonomous mobile robot in an indoor environment[J].Control Engineering Practice,2000,8(7):757-768.
  • 8Moravec H P.Sensor fusion in certainty grids for mobile robots[J].AIMag,1988,9(2):61-74.
  • 9Simon X Y,Max M.An efficient neural network approach to dynamic robot motion planning[J].Neural Networks,2000,13(2):173-178.
  • 10Borenstein J,Feng L.UMBmark-a method for measuring,comparing,and correcting dead-reckoning errors in mobile robots[M].USA:University of Michigan,1994.

二级参考文献29

  • 1王小忠,孟正大.机器人运动规划方法的研究[J].控制工程,2004,11(3):280-284. 被引量:18
  • 2邰宜斌,席裕庚,李秀明.一种机器人路径规划的新方法[J].上海交通大学学报,1996,30(4):94-100. 被引量:14
  • 3Kruusmaa M, Willemson J. Covering the path space: a casebase analysis for mobile robot path planning[J]. Knowledge-Based Systems,2003,16(5-6): 235-242.
  • 4Yahja A, Singh S, Stentz A. An efficient on-line path planner for outdoor mobile robots[J]. Robotics and Autonomous Systems,2000,32(2): 129-143.
  • 5Koeing S, Likhachev M. Improved fast replanning for robot navigation in unknown terrain[C]. Washington DC:Proceedings 2002 IEEE International Conference on Robotics and Automation,2002.
  • 6Nilsson N J. Introduction to artificial intelligence principles[J]. Rivista di Informatica,1981,11(1): 13-38.
  • 7Stentz A. Optimal and efficient path planning for partially-known enviroments[C]. San Diego:In Proceedings of the IEEE International Conference on Robotics and Automation,1994.
  • 8Stentz A. The focussed D* algorithm for real-time replanning[C]. Montreal:In Proceedings of the International Joint Conference on Artificial Intelligence,1995.
  • 9Podsedkowski L, Nowakowski J, Idzikowski M,et al. A new solution for path planning in partially known or unknown environment for nonholonomic mobile robots[J]. Robotics and Autonomous Systems,2001,34(2-3):145-152.
  • 10Arkin R C. Behavior-based robotics[M]. London:The MIT Press,1998.

共引文献74

同被引文献29

  • 1王景川,陈卫东,曹其新.基于全景视觉与里程计的移动机器人自定位方法研究[J].机器人,2005,27(1):41-45. 被引量:23
  • 2杨忠,樊琼剑.基于胡须传感器的仿生机器人研究进展[J].机器人,2007,29(2):171-178. 被引量:7
  • 3何燕,尹蕾,胡捍英.用残差加权对抗NLOS误差的移动定位算法[J].无线电通信技术,2007,33(5):35-37. 被引量:1
  • 4Yan Wang, Yuanwei Jing, and Zixi Jia. An indoor mobile localization strategy for robot in NLOS environment [J].Intemational Journal of Distributed Sensor Networks, 2013: 1-8.
  • 5Velimirovic A S, Djordjevic G L, Velimirovic M M, et al. Fuzzy ring-overlapping range-free (FRORF) localization method for wireless sensor networks [J]. Computer Communications, 2012, 35(13): 1590-1600.
  • 6Jihua Zhu, Nanning Zheng and Zejian Yuan. An improved technique for robot global localization in indoor environments [J]. International Journal of Advanced Robotic Systems, 2011, 8(1): 21-28.
  • 7Jing L, Vadakkepat P. Interacting MCMC particle filter for tracking maneuvering target[J]. Digital Signal Processing, 2010, 20(2): 561-574.
  • 8Hu J S, Chan C Y, Wang C K, et al. Simultaneous Localization of a Mobile Robot and Multiple Sound Sources Using a Microphone Array[J]. Advanced Robotics, 2011, 25(1-2): 135-152.
  • 9Kalman R E. A new approach to linear filtering and prediction problems [J]. Journal of basic Engineering, 1960, 82(1): 35-45.
  • 10Kalman R E, Bucy R S. New results in linear filtering and prediction theory [J]. Journal of Basic Engineering, 1961, 83(3): 95-108.

引证文献3

二级引证文献12

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