室内轮式服务机器人混合定位研究
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摘要
随着科技的进步,人们越来越希望日益智能化的移动服务机器人能代替人工完成一些枯燥乏味的工作,降低体力劳动强度。而移动服务机器人的定位导航很重要,可靠、高精度的定位技术是移动服务机器人的关键技术之一。当前,满足室内移动服务机器人定位精度需要的定位技术实现成本普遍偏高。
为了解决室内定位精度和实现成本之间的矛盾,针对室内轮式服务机器人的定位,在研究了多种室内组合定位方法的基础上,选择硬件设备成本低、实现容易的ZigBee技术和航迹推算进行混合定位研究。
首先对轮式服务机器人的运动机构进行研究,将不同的轮式运动机构进行数学建模和分析。由于差动驱动轮式服务机器人应用广泛,其机构的航迹推算研究有重要意义。在研究数值积分推算的基础上,提出了小段圆弧拟合实际轨迹的方法,使得在相同的速度采样数据下,获得更高精度的推算轨迹。
针对ZigBee定位精度不高,航迹推算误差不断累积的问题,研究提出了轨迹相似校正算法。该算法利用航迹推算在短距离内推算精度高的特点弥补ZigBee定位精度的不足,同时借助ZigBee定位来校正航迹推算的累积误差。仿真实验表明,轨迹相似校正法能有效的抑制ZigBee定位的高斯白噪声误差和随机扰动误差,消除航迹推算的累积误差,实现两种定位方法优势互补。
最后,将轨迹相似校正算法应用到智能护理轮椅的定位系统,其中包括定位系统的软、硬件的设计及其测试方法。测试结果证实了该算法能明显提升定位精度,有很好的实用价值和应用前景。
With the development of technology, there is a growing hope that the increasingly intelligent mobile robots can replace the manual to complete some boring work, reduce the physical strength. Mobile service robot’s navigation is very important, one of the key technologies for mobile service robots is reliable, high-precision positioning technology. At present, to meet the positioning accuracy of indoor mobile service robot need to spend universal high costs. In order to solve the contradiction between indoor positioning accuracy and implementation costs,aimed the indoor wheeled service robots’application. On the basis of studying a variety of indoor positioning methods, this paper selected ZigBee technology, whose device cost is low and implement is easy and interactive with dead reckoning for compound positioning research.
First of all, the paper studies the mechanism of the wheeled service robots and their different mathematical modeling and analysis. As the differential drove robots’s widely used, the bodies of dead reckoning has significient importance. on the basis of studying numerical integration projections, presented subparagraph arc fitting method of the actual trajectory, makes the same speed under the sampling data, obtained higher accurate projection trajectory.
What’s more ,for the problem that ZigBee localization’s accuracy is low while dead reckoning error is accumulating, the paper presents a method named similar trajectory calibration.After studying the paper presented similar trajectory correction algorithm. The algorithm makes use of dead reckoning’s high Precision in the short distance to make up the inadequate positioning accuracy of ZigBee and meanwhile take advantage of ZigBee localization to reduce the accumulated error of dead reckoning. Simulation results show that similar trajectory calibration method can effectively suppresses ZigBee location’s Gaussian white noise error and random disturbance error,and eliminating the cumulative error of dead reckoning, makes this two positioning methods to achieve complementary advantages.
Finally, the paper gives an application of similar trajectory calibration into smart nursing wheel-chair, which including the positioning system hardware and software design and test methods, test results confirmed that the algorithm can obviously improve the positioning accuracy, have good practical value and application prospect.
为了解决室内定位精度和实现成本之间的矛盾,针对室内轮式服务机器人的定位,在研究了多种室内组合定位方法的基础上,选择硬件设备成本低、实现容易的ZigBee技术和航迹推算进行混合定位研究。
首先对轮式服务机器人的运动机构进行研究,将不同的轮式运动机构进行数学建模和分析。由于差动驱动轮式服务机器人应用广泛,其机构的航迹推算研究有重要意义。在研究数值积分推算的基础上,提出了小段圆弧拟合实际轨迹的方法,使得在相同的速度采样数据下,获得更高精度的推算轨迹。
针对ZigBee定位精度不高,航迹推算误差不断累积的问题,研究提出了轨迹相似校正算法。该算法利用航迹推算在短距离内推算精度高的特点弥补ZigBee定位精度的不足,同时借助ZigBee定位来校正航迹推算的累积误差。仿真实验表明,轨迹相似校正法能有效的抑制ZigBee定位的高斯白噪声误差和随机扰动误差,消除航迹推算的累积误差,实现两种定位方法优势互补。
最后,将轨迹相似校正算法应用到智能护理轮椅的定位系统,其中包括定位系统的软、硬件的设计及其测试方法。测试结果证实了该算法能明显提升定位精度,有很好的实用价值和应用前景。
With the development of technology, there is a growing hope that the increasingly intelligent mobile robots can replace the manual to complete some boring work, reduce the physical strength. Mobile service robot’s navigation is very important, one of the key technologies for mobile service robots is reliable, high-precision positioning technology. At present, to meet the positioning accuracy of indoor mobile service robot need to spend universal high costs. In order to solve the contradiction between indoor positioning accuracy and implementation costs,aimed the indoor wheeled service robots’application. On the basis of studying a variety of indoor positioning methods, this paper selected ZigBee technology, whose device cost is low and implement is easy and interactive with dead reckoning for compound positioning research.
First of all, the paper studies the mechanism of the wheeled service robots and their different mathematical modeling and analysis. As the differential drove robots’s widely used, the bodies of dead reckoning has significient importance. on the basis of studying numerical integration projections, presented subparagraph arc fitting method of the actual trajectory, makes the same speed under the sampling data, obtained higher accurate projection trajectory.
What’s more ,for the problem that ZigBee localization’s accuracy is low while dead reckoning error is accumulating, the paper presents a method named similar trajectory calibration.After studying the paper presented similar trajectory correction algorithm. The algorithm makes use of dead reckoning’s high Precision in the short distance to make up the inadequate positioning accuracy of ZigBee and meanwhile take advantage of ZigBee localization to reduce the accumulated error of dead reckoning. Simulation results show that similar trajectory calibration method can effectively suppresses ZigBee location’s Gaussian white noise error and random disturbance error,and eliminating the cumulative error of dead reckoning, makes this two positioning methods to achieve complementary advantages.
Finally, the paper gives an application of similar trajectory calibration into smart nursing wheel-chair, which including the positioning system hardware and software design and test methods, test results confirmed that the algorithm can obviously improve the positioning accuracy, have good practical value and application prospect.
引文
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[21] GU Qinghua, LU Caiwu, etc. Dynamic management system of ore blending in an open pit mine based on GIS/GPS/GPRS[J]. Mining Science and Technology, 2010, 20(1): 132-137.
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[26]王鸿鹏,王耀宽.基于Cricket传感器网络室内定位系统的设计与实现[J].计算机工程与应用, 2008, 44(2): 211-214,244.
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[28]刘琚,李静.一种在非视距环境中的TDOA/AOA混合定位方法[J].通信学报,2005, 26(5): 63-64.
[29]张明华.基于WLAN的室内定位[D].上海:上海交通大学,计算机科学与工程系, 2009: 24-27
[30]张洁颖.基于ZigBee网络的定位跟踪研究与实现[D].上海:同济大学,电子与信息工程学院, 2007.
[31]余运昌,李绣峰,邓锦炽等.自主移动服务机器人现状与关键技术研究综述[J].机电产品开发与创新,2007,20(6): 41-42, 55.
[32]田国会,李晓磊,赵守鹏,路飞.家庭服务机器人智能空间技术研究与进展[J].山东大学学报(工学版),2007, 37 (5): 2-6.
[33]沈猛,徐德民等.轮式移动机器人组合导航方法及试验研究[J].计算机仿真,2005,22(7): 85-87.
[34]吴伟,刘兴刚等.多传感器融合实现机器人精确定位[J].东北大学学报(自然科学版),2007, 28(2): 161-164.
[35]常青,郑平等.车载GPS/DR组合导航系统数据融合算法研究[J].通信学报,2000,21(2): 42-46.
[36]郑利龙,曹志刚. GPS组合导航系统的数据融合[J].电子学报,2002, 9:1384-1385.
[37]柳长安,李国栋,刘春阳.差动驱动式移动机器人的运动规划[J].哈尔滨工业大学学报,2003, 35(9):1095-1096.
[38]吴克河,李为,柳长安,李国栋.双轮驱动式移动机器人动力学控制[J].宇航学报,2006, 27(2):272-274.
[39] Sung-Min Han, Kang-Woong Lee. Mobile Robot Navigation Using Circular Path Planning Algorithm[C]. International Conference on Control, Automation and Systems,Seoul, Korea, 2008:2082-2084.
[40] Hamidreza Chitsaz , Steven M. LaValle. Minmum Wheel-Rotation Path for Differential-Drive Mobile Robots[C]. International Conference on Robotics and Automation Roma, Itly, 2007:2718-2719.
[41]李文仲,段朝玉等. ZigBee2006无线网络与无线定位实战[M].北京:北京航空航天大学出版社,2007.
[42]徐则中,庄燕滨.移动机器人定位方法对比研究[J].系统仿真学报,2009, 21(7):1891-1893.
[43]项志宇.面向越野自主导航的鲁棒GPS/INS融合定位系统[J].电路与系统学报,2008, 13(4): 59-64.
[44]吉世涛,万彦辉等.信息融合技术及在车载SINS/GPS/DR组合导航系统中的应用[J].导航与控制,2003,(4): 14-17.
[45]原魁.智能轮椅技术发展现状[C].第一届北京康复医学论坛,北京:中国康复中心,2006: 241-247.
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[2]肖雄军,蔡自兴.服务机器人的发展[J].自动化博览, 2004,(21):11-13.
[3]上海市机器人协会,服务机器人技术发展趋势[J].机器人技术与应用,2009, (5):5-11.
[4]王志文,郭戈.移动机器人导航技术现状与展望[J].机器人, 2003, 5(25): 470-474 .
[5]徐秀娜,赖汝.移动机器人路径规划技术的现状与发展[J].计算机仿真, 2006, 10(23):l-5.
[6]李磊,叶涛,谭民,陈细军.移动机器人技术研究现状与未来[J].机器人, 2002, 5(24):475-480.
[7] Roy Want, Andy Hopper, Veronica Falcao, etc. Active badge location system[J]. ACM Transactions on Information Systems, 1992, 10(1): 91-102.
[8]朱敏,室内定位技术分析[J].现代计算机, 2008, (2):79-81.
[9]蒲芳,曹奇英,李彩霞.普适计算中的位置感知综述[J].东华大学学报(自然科学版), 2006, 32(1):120-124.
[10]徐德,邹伟.室内移式动服务机器人的感知、定位与控制[M].北京,科学出版社, 2008:285-289.
[11] J.Gonzalez-Barbosa, S. Lacroix. Rover localization in natural environments by indexing panoramic image[C]. Proc of the International Conference on Robotics and Automation, IEEE, 2002: 1365-1370.
[12] M. Artac, M. Jogan, A. Leonardis. Mobile robot localization using an incremental Eigenspace model[C]. Proc of the International Conference on Robotics and Automation, IEEE, 2002: 1025-1030.
[13] E.P. E. Menegatti, M. Zoccarato, H. Ishiguro. Image-based Monte-Carlo localization with omnidirectional images[J]. Robotics and Autonomous Systems, Vol48, No.1, 2004:17-30.
[14] H. Andreasson, A. Treptow and T. Duckett. Localization for Mobile Robots using Panoramic Vision, Local Features and Particle Filter[C]. Proc of the International Conference on Robotics and Automation, IEEE, 2005:3348-3353.
[15] Corke P. An inertial and visual sensing system for a small autonomous helicopter[J]. Journal of Robotic System, 2004, 21(2):73-83.
[16] Urmson C,Whittaker W. Self-Driving Cars and the Urban Challenge[J]. Intelligent Systems,IEEE,2008,23(2):66-68.
[17]李磊,陈细军,曹志强等.一种室内轮式自主移动机器人的导航控制研究[J].自动化学报,2003, 29(6):893-899.
[18]张朋飞,何克忠,欧阳正柱等.多功能室外智能移动机器人实验平台—THMR-V[J].机器人,2002, 24(2):97-101.
[19]王卫华,陈卫东,席裕庚.移动机器人地图创建中的不确定传感信息处理.自动化学报,2004, 29(2):267-274.
[20]张立立,钟耳顺.无线室内定位技术[C].中国地理信息系统协会第八届年会,北京:中国地理信息系统协会, 2004: 966-972 .
[21] GU Qinghua, LU Caiwu, etc. Dynamic management system of ore blending in an open pit mine based on GIS/GPS/GPRS[J]. Mining Science and Technology, 2010, 20(1): 132-137.
[22] P. Bahl, V. N. Padmanabhan. Radar: An In-Building RF-based User Location and Tracking System[J]. Proc. IEEE INFOCOM 2000:775-784, 2000.
[23] P. Bahl, V. N. Padmanabhan. Enhancements to the Radar User Location and Tracking System[R]. Technical Report MSR-TR-2000-12,Microsoft Research, 2000.
[24]杨天池,金梁,程娟.一种基于TOA定位的CHAN改进算法[J].电子学报, 2009, (4): 819-822.
[25]毛永毅,李明远,张宝军.一种NLOS环境下的TOA/AOA定位算法[J].电子与信息学报, 2009, (1): 37-40.
[26]王鸿鹏,王耀宽.基于Cricket传感器网络室内定位系统的设计与实现[J].计算机工程与应用, 2008, 44(2): 211-214,244.
[27] Amundson, Isaac, Koutsoukos, Xenofon D. A survey on localization for mobile wireless sensor networks[C]. Lecture Notes in Computer Science, 2009: 235-254.
[28]刘琚,李静.一种在非视距环境中的TDOA/AOA混合定位方法[J].通信学报,2005, 26(5): 63-64.
[29]张明华.基于WLAN的室内定位[D].上海:上海交通大学,计算机科学与工程系, 2009: 24-27
[30]张洁颖.基于ZigBee网络的定位跟踪研究与实现[D].上海:同济大学,电子与信息工程学院, 2007.
[31]余运昌,李绣峰,邓锦炽等.自主移动服务机器人现状与关键技术研究综述[J].机电产品开发与创新,2007,20(6): 41-42, 55.
[32]田国会,李晓磊,赵守鹏,路飞.家庭服务机器人智能空间技术研究与进展[J].山东大学学报(工学版),2007, 37 (5): 2-6.
[33]沈猛,徐德民等.轮式移动机器人组合导航方法及试验研究[J].计算机仿真,2005,22(7): 85-87.
[34]吴伟,刘兴刚等.多传感器融合实现机器人精确定位[J].东北大学学报(自然科学版),2007, 28(2): 161-164.
[35]常青,郑平等.车载GPS/DR组合导航系统数据融合算法研究[J].通信学报,2000,21(2): 42-46.
[36]郑利龙,曹志刚. GPS组合导航系统的数据融合[J].电子学报,2002, 9:1384-1385.
[37]柳长安,李国栋,刘春阳.差动驱动式移动机器人的运动规划[J].哈尔滨工业大学学报,2003, 35(9):1095-1096.
[38]吴克河,李为,柳长安,李国栋.双轮驱动式移动机器人动力学控制[J].宇航学报,2006, 27(2):272-274.
[39] Sung-Min Han, Kang-Woong Lee. Mobile Robot Navigation Using Circular Path Planning Algorithm[C]. International Conference on Control, Automation and Systems,Seoul, Korea, 2008:2082-2084.
[40] Hamidreza Chitsaz , Steven M. LaValle. Minmum Wheel-Rotation Path for Differential-Drive Mobile Robots[C]. International Conference on Robotics and Automation Roma, Itly, 2007:2718-2719.
[41]李文仲,段朝玉等. ZigBee2006无线网络与无线定位实战[M].北京:北京航空航天大学出版社,2007.
[42]徐则中,庄燕滨.移动机器人定位方法对比研究[J].系统仿真学报,2009, 21(7):1891-1893.
[43]项志宇.面向越野自主导航的鲁棒GPS/INS融合定位系统[J].电路与系统学报,2008, 13(4): 59-64.
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