基于多传感器的智能机器人信息融合、控制结构和应用

摘要
图/表
参考文献
相关文章 (13)

全文: PDF (3097 KB) HTML ( ) 输出: BibTeX \| EndNote (RIS)
引用本文:
袁军, 黄心汉, 陈锦江. 基于多传感器的智能机器人信息融合、控制结构和应用[J]. 机器人, 1994, 16(5): 313-320..

摘要智能机器人能最佳地、综合地使用多传感器信息，具有完成某一特定任务所需的完备信息，从而实现在各种复杂的、动态的、不确定环境中的自主性．多传感器信息融合是指将经过集成处理的多传感器信息进行合成，形成对外部环境某一特征的一种表达方式．经过集成与融合的多传感器信息能完善地、精确地反映环境特征，而单一传感器只能获得环境特征的部分信息段，经过集成与融合的多传感器信息具有以下特征^[1]：信息冗余性、信息的互补性、信息的实时性和信息的低成本性，本文较为全面介绍智能机器人多传感器信息融合的一般方法，具体传感器信息融合，用于集成与融合的控制结构以及在机器人领域的具体应用，最后指出多传感器信息融合近期研究内容．

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	袁军
	黄心汉
	陈锦江

关键词 ：传感器集成与融合, 控制结构, 自主系统, 装配机器人

作者简介: 衷军，男，29岁，博士生;研究领域：机器人装配，机器人传感技术，控制理论．

链接本文:

https://robot.sia.cn/CN/ 或 https://robot.sia.cn/CN/Y1994/V16/I5/313

[1] LuoRC.Michael G Kay. Multisensor integration and fusion in intelligent systems. IEEE Trans System, Man and Cybernetics.1989, 19(5),901-931.
[2] Heeger D J,Hager G. Egomotion and the stabilized world. IEEE ICCV. 1988,435-440.
[3] Luo R C et al. Dynamic multi-sensor data fusion system for intelligent robots. IEEE Journ of Robotics and Automations, 1988,4(2),386-396.
[4] Durrant-Whyte. Sensor models and multisensor integration. Int Journ of Robotics Research, 1988.7(6),97-113.
[5] Rao B S Y et al. A fully decentralized multi-sensor system for tracking and surveillance. Int Journ of Robotics Research, 1993,12(1),20-45.
[6] Mckendall R. Mintz M. Robust fusion of location information. Proc of IEEE Int Conf on Robotics and Automations, 1988,1239-1244.
[7] Waltz E L. Llinas J. Sensor funion. Norwood,M A, Artec House, 1991.
[8] Belknap R et al. The information fusion problem and ruled-based hypotheses applied to complex aggregations of image events. IEEE Int Conf on Computer Vision and Pattern Recog, 1986,227-234.
[9] Huntsberger T L et al. A framework for multi-sensor fusion in the presence of uncertainty. Proc Worksahop Spatial Rea-coning and Multi-Sensor Fusion, 1987,345-350.
[10] Special issues on sensors integration and fusion. In Proc. SPIE. 1991 and 1992.
[11] Beni G et al. Dynamic sensing for robots,An analysis and implementation. Int J Robotics Research, 1983,2(2)51-61.
[12] Cameron A, Durrant-Whyte. A Bayesian approach to optimal sensor placement. Int J Robotics Research, 1990,9(5): 70-88.
[13] Henderson T C et al. MKS, A multisensor kernel system. IEEE Trans on Systems, Man Cybernetics, 1984,14(5), 784-791.
[14] Shneier M O“ol. Model-based strategies for high-level robot vision. Computer, Vision Graphics Image Process, 1986,33,293-306.
[15] Albus J S. Brains, behavior and robotics. Peterborough,NH,Byte Books.1981.
[16] Harmon S Y et al. Sensor data fusion through a distributed blackboard. Proc IEEE Conf Robotics and Automation, San Francisco. CA. 1986:1449-1454.
[17] Miller W T et al. Application of a general learning algorithm to thecontrol of robotics manipulator. Int J Robotics Re-search, 1987,6(2)84-98.
[18] Magee M J. Aggarwal J K. Using multiaensory images to derive the structure of three-dimensional object.-A review. Computer, Vision Graphics Image Process, 1985,32, 145-157.
[19] Porrill J. Optimal combination and contrainsts geometrical sensor data. Int J Robotics Research,1988.7(6),66-77.
[20] Allen P K. Integrating vision and touch for object recognition, tasks, Int J Robotics Research, 1988,7(6).15-33.
[21] Luo R C, Tsai W. Object recognition using tactile array sensor. Proc. IEEE Conf Robotics and Automation, San Fran-cisco. CA,1986;1248-1253.
[22] Stansfield S A. Visually-aided tactile exploration. Proc IEEE Conf Robotics and Automation, Raleigh,NC. 1987,1497-1492.
[23] Nandhakumar N et al. Integrated analysis of thermal and vision images for acence interpretation. IEEE Trans on Pat-tern Analysis and Machine Intelligent, 1988,10(4),469-481.
[24] Grimson W E L et al. Model-based recognition and location from sparse range or tactile data. Int J Robotics Research, 1984,3(3):3-35.
[25] Roggeri?ann M C et al. Multisensor information fusion for target detection and classification. Proc SPIE, Sensor Fu-lion,1988, 931, 8-13.
[26] Giralt G et al. A multi-level planning and navigation system for a mobile robot:A first approach to HLARE. Proc 6th Int Joint Conf.,Artificial Intelligent, Tokyo, Japan, 1979:335-337.
[27] Kriegman D J et al. A mobile robot, sensing, planning and locomotion, Proc IEEE Conf Robotics and Automation, Raleigh,NC, 1987,402-408.
[28] Goto Y. Stents A. The CMU system for mobile robot navigation. Proc IEEE Conf Robotics and Automation, Rsleigh, NC, 1987,99-105.
[29] Daily M et al. Autonomous cross-country navigation with the ALV. Proc IEEE Conf Robotics and Automation. Philadelphia,PA,1988:718-726.
[30] Groen F C A et al. Multisensor robot assembly station. Robotics,1986.2,205-214.
[31] Rembold U,Dillmann R. Autonomous robot of the University of Karlsruhe. Proc of the 15th ISIR. Tokyo, 1985, 11-13.
[32] Middelhoek S. Hoogerwerf A C. Smart sensors, When and where? sensors and actuators,1985,8,39-48