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基于UWB室内定位的迎宾机器人系统研究 被引量:5

Study on Receptionist Robot System Based on UWB Indoor Localization
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摘要 针对室内复杂环境下移动机器人很难实现精确定位的问题,设计了一种基于UWB室内定位的迎宾机器人系统。通过架设4个UWB定位基站,以及安装于机器人上方位置的定位标签,对迎宾机器人进行实时定位。介绍了迎宾机器人的总体结构,对其机械系统和控制系统进行了详细说明;提出了一种融合PID和LQR的移动机器人混合路径跟踪算法。最后对迎宾机器人进行实验,验证整体方案的可行性和有效性。实验结果表明,自主研制的机器人系统软硬件运行稳定可靠,设计的UWB室内定位系统具有小于5cm的室内定位精度,重复精度小于1cm;所提出的混合路径跟踪算法具有较快的响应速度,跟踪精度小于5cm。 According to the difficulty of achieving precise positioning in complex indoor environment,a system of receptionist robot based on UWB(Ultra-wide Bandwidth)indoor localization was designed.Locating the robot was realized via four UWB base stations and the tag erected in the central part above the robot.The general structure of the robot was introduced,the mechanical system and the control system were described in detail.A mixed path tracking algorithm on account of PID and LQR(Linear Quadratic Regulator)was designed.At last,the experiment with the robot was made to verify the feasibility and effectiveness of the whole project.The experimental results show that the hardware and software run steadily,the error of the designed indoor localization system is less than 5 cm and repeatability is less than 1 cm.The mixed path tracking algorithm proposed has faster response speed and the tracking precision is less than 5 cm.
作者 李龙委 胡海燕 章仁辉 李春光 孙立宁 LI Longwei;HU Haiyan;ZHANG Renhui;LI Chunguang;SUN Lining(School of Mechanical and Electric Engineering,Soochow University,Suzhou 215021,China;Collaborative Innovation Center of Suzhou Nano Science and Technology,Suzhou 215021,China)
出处 《机械与电子》 2018年第12期58-63,68,共7页 Machinery & Electronics
基金 国家高技术研究发展计划资助项目(2015AA042301) 国家自然科学基金资助项目(61203349)
关键词 UWB 室内定位 路径跟踪 迎宾机器人 UWB indoor localization path tracking receptionist robots
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  • 1Larsson U, Forsberg J, Wemersson A. On robot navigation using identical landmarks: Integrating measurements from a time- of-flight laser[C]//IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems. Piscataway, NJ, USA: IEEE, 1994: 17-26.
  • 2Leonard J J, Durrant-Whyte H F. Mobile robot localization by tracking geometric beacons[J]. IEEE Transactions on Robotics and Automation, 1991, 7(3): 376-382.
  • 3Madhavan R, Dissanayake G, Durrant-Whyte H E Mapbuilding and map-based localization in an underground-mine by statistical pattern matching[CJ//14th International Conference on Pattern Recognition. Los Alamitos, CA, USA: IEEE Computer Society, 1998: 1744-1746.
  • 4MathPages. Perpendicular regression of a line[EB/OL]. [2010- 03-15]. http://mathpages.com/home/kmath110.htm.
  • 5Bailey T. Mobile robot localization and mapping in extensive outdoor environments[D]. Sydney, Australia: University of Sydney, 2002.
  • 6Negenborn R. Robot localization and Kalman filters: On finding your position in a noisy world[D]. Netherlands: Utrecht University, 2003.
  • 7Welch G, Bishop G. An introduction to the Kalman filter, TR 95-041[R]. USA: ACM, 2001.
  • 8Larsson U, Forsberg J, Wernersson A. Mobile robot localization: Integrating measurements from a time-of-flight laser[J]. IEEE Transactions on Industrial Electronics, 1996, 43(3): 422- 431.
  • 9Cox I J. Blanche - An experiment in guidance and navigation of an autonomous robot vehicle[J]. IEEE Transactions on Robotics and Automation, 1991, 7(2): 193-204.
  • 10Curran A, Kyriakopoulos K J. Sensor-based self-localization for wheeled mobile robots[C]//IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 1993: 8-13.

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