微小型移动机器人组合导航定位系统的研究
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摘要
微小型移动机器人有其应用的特殊性,在体积、功耗、成本等方面都有要求。移动机器人的导航定位是利用环境信息以及传感器的观测值等输入信息,经过处理产生对机器人当前位姿的估计,导航定位技术是移动机器人的重要研究方向。本文比较了多种移动机器人导航定位技术,综合研究了几种已有的微小型移动机器人导航定位系统,针对现有的微小型移动机器人平台,提出了一种新的组合导航定位系统的解决和配置方案,并实现了捷联惯导的解算以及传感器的信息融合。本文的主要工作内容如下:
首先,本文采用了惯导法与测程法相结合的组合导航定位方式,并构建了微小型移动机器人的导航定位系统。系统的软硬件包括:基于ARM7处理器的中央硬件平台,采用MEMS陀螺和加速度计在空间上构建的微型捷联惯性测量单元,由随动轮机构以及CPLD码盘信号处理单元组成的位置测量模块,基于双缓冲队列并遵循自定通信协议的通信模块,以及移植μC/OS-II嵌入式操作系统进行任务设计的软件平台。
其次,研究并实现了在导航定位问题上的算法,包括针对MEMS器件的信号特点的数字信号处理算法,在此基础上进行了单轴航向与位置的解算。为了获得机器人实时的空间姿态,本文应用捷联惯导姿态方程进行解算,并通过计算量、误差分析以及静态误差实验对算法和解算效果进行了比较。为了实现更优的导航定位效果,本文还研究了一种基于模糊专家系统的移动机器人组合导航定位系统传感器信息融合技术,将本系统中加速度计、陀螺仪的数据进行融合并实现。
最后,为了验证导航定位系统软硬件及相关算法设计的有效性,本文构建了实验平台,通过不同的算法相应地进行了机器人航向角/姿态角估计及位置估计的实验验证及分析,并测试了系统的时漂特性,对系统的性能进行了实际检验。
The micro mobile robot is pariticular, which is limited in volume, power, cost and so on. The navigation and positioning system of mobile robot is to estimate the robot current position by dealing with the environmental information from sensor. Navigation and positioning technology is the important research of mobile robot.This paper compares some kinds of the mobile robot navigation and positioning technologies, and studies several systems of the existing micro mobile robot. A new solving and configuration method is then proposed. And the strap-down inertial system is solved and the information of sensor is fused.
Firstly, the project integrates range–finding method and inertial navigation. And the navigation and positioning system of micro mobile robot is established. The hardware and software of system includes: the core hardware platform implemented by ARM7 controller, the attitude determination module composed by the MEMS devices, the position measurement module including the slave wheel with CPLD-processed encoder, the communication module based on double buffer queue and the software platform for tasks scheduling based onμC/OS-II embedded system.
Secondly, some algorithms of navigation and positioning are researched, including digital signal processing targeting at MEMS devices. Based on it, this paper solves the equation of strap-down intertial navigation attitude. By calculating the computing quantity, analyzing the errors and doing the error experiment, the results of different algorithms are compared. In order to improve the effect of the navigation and positioning, furthermore, a sensor data fusion technology is studied based on fuzzy expert system to fuse the data of sensors.
Finally, the experimental platflam is constructed to verify the validity of the hardware, software and the related algorithms of navigation and positioning system. And relating experiments of robot phase angle/ attitude estimation, position estimation are conducted to testify the system performance.
首先,本文采用了惯导法与测程法相结合的组合导航定位方式,并构建了微小型移动机器人的导航定位系统。系统的软硬件包括:基于ARM7处理器的中央硬件平台,采用MEMS陀螺和加速度计在空间上构建的微型捷联惯性测量单元,由随动轮机构以及CPLD码盘信号处理单元组成的位置测量模块,基于双缓冲队列并遵循自定通信协议的通信模块,以及移植μC/OS-II嵌入式操作系统进行任务设计的软件平台。
其次,研究并实现了在导航定位问题上的算法,包括针对MEMS器件的信号特点的数字信号处理算法,在此基础上进行了单轴航向与位置的解算。为了获得机器人实时的空间姿态,本文应用捷联惯导姿态方程进行解算,并通过计算量、误差分析以及静态误差实验对算法和解算效果进行了比较。为了实现更优的导航定位效果,本文还研究了一种基于模糊专家系统的移动机器人组合导航定位系统传感器信息融合技术,将本系统中加速度计、陀螺仪的数据进行融合并实现。
最后,为了验证导航定位系统软硬件及相关算法设计的有效性,本文构建了实验平台,通过不同的算法相应地进行了机器人航向角/姿态角估计及位置估计的实验验证及分析,并测试了系统的时漂特性,对系统的性能进行了实际检验。
The micro mobile robot is pariticular, which is limited in volume, power, cost and so on. The navigation and positioning system of mobile robot is to estimate the robot current position by dealing with the environmental information from sensor. Navigation and positioning technology is the important research of mobile robot.This paper compares some kinds of the mobile robot navigation and positioning technologies, and studies several systems of the existing micro mobile robot. A new solving and configuration method is then proposed. And the strap-down inertial system is solved and the information of sensor is fused.
Firstly, the project integrates range–finding method and inertial navigation. And the navigation and positioning system of micro mobile robot is established. The hardware and software of system includes: the core hardware platform implemented by ARM7 controller, the attitude determination module composed by the MEMS devices, the position measurement module including the slave wheel with CPLD-processed encoder, the communication module based on double buffer queue and the software platform for tasks scheduling based onμC/OS-II embedded system.
Secondly, some algorithms of navigation and positioning are researched, including digital signal processing targeting at MEMS devices. Based on it, this paper solves the equation of strap-down intertial navigation attitude. By calculating the computing quantity, analyzing the errors and doing the error experiment, the results of different algorithms are compared. In order to improve the effect of the navigation and positioning, furthermore, a sensor data fusion technology is studied based on fuzzy expert system to fuse the data of sensors.
Finally, the experimental platflam is constructed to verify the validity of the hardware, software and the related algorithms of navigation and positioning system. And relating experiments of robot phase angle/ attitude estimation, position estimation are conducted to testify the system performance.
引文
1蔡自兴. 21世纪机器人技术的发展趋势.南京化工大学学报. 2002,22 (4):73-78
2徐国华,谭民.移动机器人的发展现状及其趋势.机器人技术与应用. 2001,3(3):7-15
3 Salichs M A, Moreno L. Navigation of mobile robots: open question. Robotica. 2000(18):227-234
4王志文.移动机器人导航技术现状与展望.机器人. 2003,25(5):470-474
5 Chatila R. Deliberation and reactivity in autonomous mobile robots. Robot and Autonomous System. 1995,16(4):197-211
6 Durrant-White H F. Where am I? Industrial Robot. 1994, 21(2):11-15
7 Leonard J, Durrant-Whyte H F. Mobile robot localization by tracking geometric beacons. IEEE Transactions on Robotics and Automation. 1991,7(3):376-382
8 Evans J M. HelpMate: an autonomous mobile robot courier for hospitals. International Conference on Intelligent Robots and Systems (1ROS '94). Munchen Germany. September 1994,5(4):1695-1700
9 Borenstein, J Everett, H. R., and Feng, L. Navigating Mobile Robots: Sensors and Techniques, Wellesley, MA: A. K. Peters, Ltd.1997,12(3):45-47
10 Borenstein J, Koren Y. Motion Control Analysis of a Mobile Robot. Transactions of ASME, Journal of Dynamics, Measurement and Control. 1987,109(2): 73-79
11 Hollingum J. Caterpillar make the earth move: automatically. The Industrial Robot. 1991,18(2):15-18
12 Borenstein J, Feng L. UMBmark-a method for measuring, comparing, and correcting dead-reckoning errors in mobile robots. Technical Report. University of Michigan, 1994,6(3):456-457
13 J Borenstein, H.R.Everett, L.Feng, et al. Mobile Robot Positioning-Sensors and Techniques. Journal of Robotic Systems. 1997,14(4):231-249
14 Barshan B, Durrant-White H F. Orientation estimate for mobile robots using gyroscopic Information. International Conference on Intelligent Robots andSystems (1ROS'94) Munchen, Germany. September 1994,17(3):1867-1874
15 Barshan B, Durrant-Whyte. An inertial navigation system for a mobile robot. In Proceedings of the 1st IAV, Southampton, England. 1993,4:54-59
16张军宇,何克忠.移动机器人THMR-V的组合定位系统.计算机工程与应用. 2001,15:69
17 J Borenstein, H.R.Everett, L.Feng, et al. Mobile Robot Positioning-Sensors and Techniques. Journal of Robotic Systems. 1997,14(4):231-249
18张飞,陈卫东.具有声纳环的移动机器人及其自主行为研究.测控技术. 2003,22(6):4650
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. 2003,29(2):267-274
20 Boley D L, Sutherland K T. A rapidly converging recursive method for mobile robot localization. International Journal of Robotics Research. 1998,17(10):1027-1039
21陈哲.捷联惯导系统原理.宇航出版社. 1986:50-98
22胡小平.自主导航理论与应用.国防科技大学出版社. 2002:160-183
23郭秀中.惯导系统陀螺仪理论.国防工业出版社. 1996:13-297
24李新刚,袁建平.微机械陀螺的发展现状.力学进展. 2003,4(3):289-300
25周世勤.新型惯性技术的发展.控制与制导. 2001,7(6):72-74
26刘俊,石云波,李杰.微惯性技术.电子工业出版社. 2005:15-20
27何友等.多传感器信息融合及应用.电子工业出版社. 2000:7-15
28 Mahajan, A.Wang, K.Ray, P.K. Multisensor integration and fusion model that uses a fuzzy inference system. IEEE/ASME Transactions on Mechatronics. 2001,6(2):452-454
29 Kail O. Arras, Nicola Tomatis, Roland Siegwart. Multisensor on the Fly Location Using Laser and Vision. Proceeding of the 2000 IEEE(RS). 2000,8(11):462-467
30 Araujo, David Lourenco, Gil Ferreira. Integrating Laser and Infrared Sensors for Learning Dynamic Self-organizing World Maps,IEEE. 2002,6(4):293-298
31 H. Benjamin, Brown. Jr, J. Michael Vande Weghe, Curt A. Bererton Millibot Trains for Enhanced Mobility IEEE/ASME Transactions on Mechatronics. 2002,12(7):346-347
32韩广,王田苗,梁建宏,赵建昌.一种有效爬越楼梯的模块化可重组履带结构.机器人. 2004,9(2):45-47
33 LPC2148 User Manual. Philips Semiconductor Corporation. 2002
34 ADIS16255 User Manual. Analog Devices Inc. 2006-2007
35 ADIS16201 User Manual. Analog Devices Inc. 2006
36 MAX7000 Programmable Logic Device Family. Altera Corporation. 2001
37梅晓榕,柏桂珍,张卯瑞.自动控制元件及线路.科学出版社. 2005:10-19
38王田苗.嵌入式系统设计与实例开发——基于ARM微处理器与μC/OS-II实时操作系统.清华大学出版社. 2005:3-5
39 Labrosse J J.嵌入式实时操作系统μC/OS-II .北京航天航空大学出版社. 2003:68-78
40周航慈.基于嵌入式操作系统的程序设计技术.北京航空航天大学出版社. 2006:56-59
41王烈军.一种基于FIR的自适应滤波器算法设计与实现.武汉大学学报. 2000,4(3):25-26
42秦永元,张洪钺,汪叔华.卡尔曼滤波与组合导航原理.电子工业出版社. 1998:124-130
43王积伟,吴振顺.现代控制理论与工程.高等教育出版社. 2003:25-30
44 Greg Welch, Gary Bishop. An Introduction to the Kalman Filter. Department of Computer Science University of North Carolina at Chapel Hill. 2004,5(8):234-240
45吴勃英.数值分析原理.科学出版社. 2003:135-144
46邓正隆.惯性导航原理.哈尔滨工业大学出版社. 1994:210-256
47徐丽娜,谢青.捷联系统航姿算法分析.自动化技术与应用. 2000,5:6-9
48薛祖瑞.关于捷联惯导系统圆锥误差的论释.中国惯性技术学报. 2000,8(4):46-69
49李士勇.模糊控制、神经控制和智能控制论.哈尔滨工业大学出版社. 1996:156-245
2徐国华,谭民.移动机器人的发展现状及其趋势.机器人技术与应用. 2001,3(3):7-15
3 Salichs M A, Moreno L. Navigation of mobile robots: open question. Robotica. 2000(18):227-234
4王志文.移动机器人导航技术现状与展望.机器人. 2003,25(5):470-474
5 Chatila R. Deliberation and reactivity in autonomous mobile robots. Robot and Autonomous System. 1995,16(4):197-211
6 Durrant-White H F. Where am I? Industrial Robot. 1994, 21(2):11-15
7 Leonard J, Durrant-Whyte H F. Mobile robot localization by tracking geometric beacons. IEEE Transactions on Robotics and Automation. 1991,7(3):376-382
8 Evans J M. HelpMate: an autonomous mobile robot courier for hospitals. International Conference on Intelligent Robots and Systems (1ROS '94). Munchen Germany. September 1994,5(4):1695-1700
9 Borenstein, J Everett, H. R., and Feng, L. Navigating Mobile Robots: Sensors and Techniques, Wellesley, MA: A. K. Peters, Ltd.1997,12(3):45-47
10 Borenstein J, Koren Y. Motion Control Analysis of a Mobile Robot. Transactions of ASME, Journal of Dynamics, Measurement and Control. 1987,109(2): 73-79
11 Hollingum J. Caterpillar make the earth move: automatically. The Industrial Robot. 1991,18(2):15-18
12 Borenstein J, Feng L. UMBmark-a method for measuring, comparing, and correcting dead-reckoning errors in mobile robots. Technical Report. University of Michigan, 1994,6(3):456-457
13 J Borenstein, H.R.Everett, L.Feng, et al. Mobile Robot Positioning-Sensors and Techniques. Journal of Robotic Systems. 1997,14(4):231-249
14 Barshan B, Durrant-White H F. Orientation estimate for mobile robots using gyroscopic Information. International Conference on Intelligent Robots andSystems (1ROS'94) Munchen, Germany. September 1994,17(3):1867-1874
15 Barshan B, Durrant-Whyte. An inertial navigation system for a mobile robot. In Proceedings of the 1st IAV, Southampton, England. 1993,4:54-59
16张军宇,何克忠.移动机器人THMR-V的组合定位系统.计算机工程与应用. 2001,15:69
17 J Borenstein, H.R.Everett, L.Feng, et al. Mobile Robot Positioning-Sensors and Techniques. Journal of Robotic Systems. 1997,14(4):231-249
18张飞,陈卫东.具有声纳环的移动机器人及其自主行为研究.测控技术. 2003,22(6):4650
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. 2003,29(2):267-274
20 Boley D L, Sutherland K T. A rapidly converging recursive method for mobile robot localization. International Journal of Robotics Research. 1998,17(10):1027-1039
21陈哲.捷联惯导系统原理.宇航出版社. 1986:50-98
22胡小平.自主导航理论与应用.国防科技大学出版社. 2002:160-183
23郭秀中.惯导系统陀螺仪理论.国防工业出版社. 1996:13-297
24李新刚,袁建平.微机械陀螺的发展现状.力学进展. 2003,4(3):289-300
25周世勤.新型惯性技术的发展.控制与制导. 2001,7(6):72-74
26刘俊,石云波,李杰.微惯性技术.电子工业出版社. 2005:15-20
27何友等.多传感器信息融合及应用.电子工业出版社. 2000:7-15
28 Mahajan, A.Wang, K.Ray, P.K. Multisensor integration and fusion model that uses a fuzzy inference system. IEEE/ASME Transactions on Mechatronics. 2001,6(2):452-454
29 Kail O. Arras, Nicola Tomatis, Roland Siegwart. Multisensor on the Fly Location Using Laser and Vision. Proceeding of the 2000 IEEE(RS). 2000,8(11):462-467
30 Araujo, David Lourenco, Gil Ferreira. Integrating Laser and Infrared Sensors for Learning Dynamic Self-organizing World Maps,IEEE. 2002,6(4):293-298
31 H. Benjamin, Brown. Jr, J. Michael Vande Weghe, Curt A. Bererton Millibot Trains for Enhanced Mobility IEEE/ASME Transactions on Mechatronics. 2002,12(7):346-347
32韩广,王田苗,梁建宏,赵建昌.一种有效爬越楼梯的模块化可重组履带结构.机器人. 2004,9(2):45-47
33 LPC2148 User Manual. Philips Semiconductor Corporation. 2002
34 ADIS16255 User Manual. Analog Devices Inc. 2006-2007
35 ADIS16201 User Manual. Analog Devices Inc. 2006
36 MAX7000 Programmable Logic Device Family. Altera Corporation. 2001
37梅晓榕,柏桂珍,张卯瑞.自动控制元件及线路.科学出版社. 2005:10-19
38王田苗.嵌入式系统设计与实例开发——基于ARM微处理器与μC/OS-II实时操作系统.清华大学出版社. 2005:3-5
39 Labrosse J J.嵌入式实时操作系统μC/OS-II .北京航天航空大学出版社. 2003:68-78
40周航慈.基于嵌入式操作系统的程序设计技术.北京航空航天大学出版社. 2006:56-59
41王烈军.一种基于FIR的自适应滤波器算法设计与实现.武汉大学学报. 2000,4(3):25-26
42秦永元,张洪钺,汪叔华.卡尔曼滤波与组合导航原理.电子工业出版社. 1998:124-130
43王积伟,吴振顺.现代控制理论与工程.高等教育出版社. 2003:25-30
44 Greg Welch, Gary Bishop. An Introduction to the Kalman Filter. Department of Computer Science University of North Carolina at Chapel Hill. 2004,5(8):234-240
45吴勃英.数值分析原理.科学出版社. 2003:135-144
46邓正隆.惯性导航原理.哈尔滨工业大学出版社. 1994:210-256
47徐丽娜,谢青.捷联系统航姿算法分析.自动化技术与应用. 2000,5:6-9
48薛祖瑞.关于捷联惯导系统圆锥误差的论释.中国惯性技术学报. 2000,8(4):46-69
49李士勇.模糊控制、神经控制和智能控制论.哈尔滨工业大学出版社. 1996:156-245