机器人化工程机械的超声波避障与惯性导航系统研究
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摘要
移动机器人作为机器人学科中一个比较活跃的研究分支,一直以来得到了学界的关注。移动机器人的避障,导航和定位是移动机器人研究领域内一个重要的研究方向,同时也是移动机器人研究的关键技术。随着信息技术,自动化技术,计算机技术和导航技术的不断发展,各个学科间不断地交叉融合。这也极大地推动了移动机器人在避障、导航和定位方面研究的发展。
本文以工作在部分未知或者完全未知环境下的移动机器人为研究对象,从工程应用和理论两个方面对移动机器人的超声波避障与惯性导航进行了研究,并且着重研究了系统的硬件设计。
通过综合国内外现有的技术文献,提出了一种融合超声波避障与惯性导航的综合导航平台系统方案。导航平台具有超声波避障探测、模拟信号采集、MEMS惯性导航模块和与GPS模块进行通信等功能。为了能够在满足系统性能要求的基础上尽可能地降低系统成本,该导航平台是以MSP430F135为核心。在完成其外围电路的基础上,采用T/R40作为超声波传感器,并对超声波的发送和接收电路进行了设计。该导航平台对模拟信号的采集可分为对高频模拟信号和低频模拟信号的采集。其中高频模拟信号采集是由AT89S52控制8位高速A/D-TLC5540INSR来实现的,而低频模拟信号采集是由MSP430F135控制其集成的12位ADC来实现。为了能够建立起主CPU和同样由MSP430F135作为主控CPU的MEMS惯性导航模块间的通信,文中采用同步SPI作为主从CPU通信方式。另外,为了能够扩展系统功能,文中采用RS232作为通信接口,实现主MSP430F135与GPS模块之间的通信。然后,在完成以上硬件设计的基础上进行了系统软件的仿真与调试。在实现各个模块的基本功能之后,初步进行了系统的综合调试。
为了提高惯性导航的导航精度,本文从理论上对惯性导航系统中的MEMS陀螺仪的漂移问题和卡尔曼滤波中的野值问题进行了理论分析,并研究了野值剔除方法和修正野值的卡尔曼滤波算法。
论文最后对全文进行了总结并对移动机器人在避障和惯性导航方向的研究进行了展望,阐明了移动机器人未来可能的研究方向。
As a correspondingly active research branch of robotics, the mobile robot has being drawn more attention in this field all the time. The obstacle avoidance and navigation of mobile robot was an important research field, as a key technique as well. As the development of information technique, automation technique, computer technique and navigation technique, each field has been continuously intercrossing and syncretizing with others. It impelled the researching development of mobile robot in obstacle avoidance and navigation
This thesis took the robot which worked under partly unknown or absolutely unknown environment as research object, and briefly focused on the design of hardware.
Comparing the existing literature both domestic and overseas, we designed a kind of mobile robot navigation system platform which integrated the ultrasonic obstacle avoidance and inertial navigation system. This navigation platform had the function such as ultrasonic obstacle avoidance detecting, analog signals acquisition, MEMS inertial navigation module and communicating with GPS module. In order to satisfy the system requirement and low the cost, we selected the MSP430F135 as the Signal Processor. Basing on completing the peripheral circuit designing, we selected the T/R40 as the ultrasonic sensor and designed the ultrasonic eradiating circuit and receiving circuit. The analog signals acquisition module was composed of high frequency and low frequency analog signals acquisition. Thereinto, the high frequency acquisition system was implemented by that AT89S52 controlled the high-speed 8-bit analog-to-digital converter, while the low frequency acquisition system was implemented by MSP430F135 which integrated a 12-bit ADC. In order to build the communication between the master and MEMS inertial navigation module, the synchronous SPI was used as the communication mode between the master and slavery. In addition, in order to extent the system function, the RS232 communication interface was used to implemented the communication between the master CPU and GPS module. And then, basing on the completed hardware design, we did some system software simulation and debugging to implement every module function. Finally, after finishing the every module function, we made some simple system synthetically debugging.
At the end, in order to enhance the navigation precision, we analyzed the random drift of the MEMS gyroscope in inertial system and the drift of Kalman filter,and did some research on how to eliminate the drift and a Kalman filter arithmetic which could properly compensate the drift.
本文以工作在部分未知或者完全未知环境下的移动机器人为研究对象,从工程应用和理论两个方面对移动机器人的超声波避障与惯性导航进行了研究,并且着重研究了系统的硬件设计。
通过综合国内外现有的技术文献,提出了一种融合超声波避障与惯性导航的综合导航平台系统方案。导航平台具有超声波避障探测、模拟信号采集、MEMS惯性导航模块和与GPS模块进行通信等功能。为了能够在满足系统性能要求的基础上尽可能地降低系统成本,该导航平台是以MSP430F135为核心。在完成其外围电路的基础上,采用T/R40作为超声波传感器,并对超声波的发送和接收电路进行了设计。该导航平台对模拟信号的采集可分为对高频模拟信号和低频模拟信号的采集。其中高频模拟信号采集是由AT89S52控制8位高速A/D-TLC5540INSR来实现的,而低频模拟信号采集是由MSP430F135控制其集成的12位ADC来实现。为了能够建立起主CPU和同样由MSP430F135作为主控CPU的MEMS惯性导航模块间的通信,文中采用同步SPI作为主从CPU通信方式。另外,为了能够扩展系统功能,文中采用RS232作为通信接口,实现主MSP430F135与GPS模块之间的通信。然后,在完成以上硬件设计的基础上进行了系统软件的仿真与调试。在实现各个模块的基本功能之后,初步进行了系统的综合调试。
为了提高惯性导航的导航精度,本文从理论上对惯性导航系统中的MEMS陀螺仪的漂移问题和卡尔曼滤波中的野值问题进行了理论分析,并研究了野值剔除方法和修正野值的卡尔曼滤波算法。
论文最后对全文进行了总结并对移动机器人在避障和惯性导航方向的研究进行了展望,阐明了移动机器人未来可能的研究方向。
As a correspondingly active research branch of robotics, the mobile robot has being drawn more attention in this field all the time. The obstacle avoidance and navigation of mobile robot was an important research field, as a key technique as well. As the development of information technique, automation technique, computer technique and navigation technique, each field has been continuously intercrossing and syncretizing with others. It impelled the researching development of mobile robot in obstacle avoidance and navigation
This thesis took the robot which worked under partly unknown or absolutely unknown environment as research object, and briefly focused on the design of hardware.
Comparing the existing literature both domestic and overseas, we designed a kind of mobile robot navigation system platform which integrated the ultrasonic obstacle avoidance and inertial navigation system. This navigation platform had the function such as ultrasonic obstacle avoidance detecting, analog signals acquisition, MEMS inertial navigation module and communicating with GPS module. In order to satisfy the system requirement and low the cost, we selected the MSP430F135 as the Signal Processor. Basing on completing the peripheral circuit designing, we selected the T/R40 as the ultrasonic sensor and designed the ultrasonic eradiating circuit and receiving circuit. The analog signals acquisition module was composed of high frequency and low frequency analog signals acquisition. Thereinto, the high frequency acquisition system was implemented by that AT89S52 controlled the high-speed 8-bit analog-to-digital converter, while the low frequency acquisition system was implemented by MSP430F135 which integrated a 12-bit ADC. In order to build the communication between the master and MEMS inertial navigation module, the synchronous SPI was used as the communication mode between the master and slavery. In addition, in order to extent the system function, the RS232 communication interface was used to implemented the communication between the master CPU and GPS module. And then, basing on the completed hardware design, we did some system software simulation and debugging to implement every module function. Finally, after finishing the every module function, we made some simple system synthetically debugging.
At the end, in order to enhance the navigation precision, we analyzed the random drift of the MEMS gyroscope in inertial system and the drift of Kalman filter,and did some research on how to eliminate the drift and a Kalman filter arithmetic which could properly compensate the drift.
引文
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[7]高国富谢少荣罗均,机器人传感器机器应用[M].化学工业出版社. 2005: 88-89
[8] http://robocup.sjtu.edu.cn/chinese/project/proje2.htm
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[17]吴镜开,黄远灿,王世兴.基于势场法的移动机器人避障路径规划[J].机器人技术,2007,23(2-2):228-230
[18]郑敏捷,蔡自兴,于金霞.一种动态环境下的移动机器人避障策略[J].高技术通讯,2006,16(8):813-817
[19]丁文娟.捷联惯性/里程切伪卫星车载组合导航系统研究[D].西安:西北工业大学,2006.2
[20]徐健.基于DSP的惯性导航系统设计与实现[D].大连:大连理工大学, 2006.16
[21]黄德鸣,程禄.惯性导航系统[M].北京:国防工业出版社,1986.
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[23]胡盛斌,罗均,龚振帮.用于移动机器人避障的超声测距系统[J].机电一体化, 2003(1):37-40
[24]黄庆成,洪炳铭,Javaid I}hurshid,高庆吉,朱莹,阮玉峰全自主足球机器人的超声波定位避障系统[J]. Vol.35 No.9 Sep.,2003
[25]MSP430X13X MIXED SIGNAL MICROCONTROLLER. TEXAS INSTRUMENTS.2001
[26]沈建华,杨艳琴.MSP430系列16位超低功耗单片机原理与应用[M].清华大学出版社.2003.2
[27]超声波特性http://szbaiyi18a.dz-z.com/Files.html
[28]孙传友,孙晓彬,汉泽西等.测控系统原理与设计[M].北京航空航天大学出版社。2006.1
[29]OP27GP Data Sheet[M]. ADI.2001
[30]THS3001CD Data sheet[M]. TEXAS INSTRUMENTS.1999
[31]TLC5540A, 8-BIT HIGH-SPEEDANALOG-TO-DIGITAL CONVERTERS. www.ti.com
[32]TLC5540/TLC5510/TLC5510A Evaluation Module User’s Guide. www.ti.com
[33]TPS7350QP Data Sheet[M]. TEXAS INSTRUMENTS.1999
[34]LM1117 Data Sheet[M].National Semiconductor.1999
[35]TPS60403DBV Data Sheet[M]. TEXAS INSTRUMENTS.2001
[36]CY731021CV33-12ZC Data Sheet[M].Cypress
[37]ADXL202E Data Sheet[M].Analog Device
[38]ADXRS612 Data Sheet[M].Analog Device
[39]MSP430 IAR Embedded Workbench? IDE User Guide. http://www.msp430.com
[40]秦龙.MSP430单片机常用模块与综合系统实例精讲[M].电子工业出版社,2007.7
[41]高亚楠,陈家斌.惯性导航系统中的Kalman滤波技术[J].2005,30(1):1-4
[42]郭秀中.惯导系统陀螺仪理论[M].国防工业出版社,1996
[43]黄德鸣,程禄.惯性导航系统[M].国防工业出版社,1986
[44]徐建.基于DSP的惯性导航系统设计与实现[D].大连:大连理工大学,2006,12
[45]张春惠.高精度捷联式惯性导航系统算法研究[D].哈尔滨:哈尔滨工程大学,2005.3
[46]樊荣.捷联惯性导航系统初始对准方法研究及其仿真[D].南京:南京理工大学,2006.6
[47]丁文娟.捷联惯性/里程仪/伪卫星车载组合导航系统研究[D].西安:西北工业大学,2006.2
[48]张帆,卢峥.自适应抗野值kalman滤波[J].电机与控制学科,2007,11(2):188-191
[49]周跃庆,高宁,刘鲁源等.抗野值自适应kalman滤波及其在陀螺信号处理中的应用[J].天津大学学报. 2004, 37(9):815-817
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[2]王火亮,孙守迁.基于超声波传感器测距的家用自主式移动吸尘器路径规划算法[J].计算机应用研究.2002, 19(8):57-58,61.
[3]欧青立,何克忠.室外智能移动机器人的发展及其关键技术研究[J].机器人.2000 22(6):519-526.
[4]张竺英,王棣棠,刘大路.自治式水卜机器人回收系统的研究与设计[J].机器人.1995, 17(6):348-351.
[5] Nilsson N J. A mobile automation: an application of artificial intelligence techniques. In Proceedings the 1st International Joint Conference on Artificial Intelligence. 1969,.509-520.
[6]邹细勇.自主移动机器人的智能导航研究[D].杭州:浙江大学,2004.5
[7]高国富谢少荣罗均,机器人传感器机器应用[M].化学工业出版社. 2005: 88-89
[8] http://robocup.sjtu.edu.cn/chinese/project/proje2.htm
[9]郑向阳.自主式移动机器人路径规划研究[D].杭州:浙江大学,2004.2
[10]王斌明.基于多传感器信息融合的移动机器人避障研究[D].南京:南京理工大学,2006.6
[11]王军,苏剑波,席裕庚.多传感器集成与融合概述.机器人.2001.2(23):183-186
[12]朴松昊,洪炳熔.一种动态环境下移动机器人的路径规划方法.机器人,2003 25(1):18-21.
[13]李羚翔.智能割草机器人路径识别、跟踪与障碍探测技术的研究[D].南京:南京理工大学,2005.6
[14]张守信,董绪荣.GPS/INS组合导航定位与应用.国防大学出版社,1998
[15]樊明轩.全区域覆盖移动机器人避障策略及多传感器系统的设计研究[D].南京:南京理工大学,2003.3
[16]孟伟,洪炳榕,韩学东.基于场景匹配的移动机器人避障[J].控制与决策,vol.19 No.8 Aug.2004:890-892
[17]吴镜开,黄远灿,王世兴.基于势场法的移动机器人避障路径规划[J].机器人技术,2007,23(2-2):228-230
[18]郑敏捷,蔡自兴,于金霞.一种动态环境下的移动机器人避障策略[J].高技术通讯,2006,16(8):813-817
[19]丁文娟.捷联惯性/里程切伪卫星车载组合导航系统研究[D].西安:西北工业大学,2006.2
[20]徐健.基于DSP的惯性导航系统设计与实现[D].大连:大连理工大学, 2006.16
[21]黄德鸣,程禄.惯性导航系统[M].北京:国防工业出版社,1986.
[22]蒋庆仙,关于MEMS惯性传感器的发展及在组合导航中的应用前景[J], (2006) 09-05-04
[23]胡盛斌,罗均,龚振帮.用于移动机器人避障的超声测距系统[J].机电一体化, 2003(1):37-40
[24]黄庆成,洪炳铭,Javaid I}hurshid,高庆吉,朱莹,阮玉峰全自主足球机器人的超声波定位避障系统[J]. Vol.35 No.9 Sep.,2003
[25]MSP430X13X MIXED SIGNAL MICROCONTROLLER. TEXAS INSTRUMENTS.2001
[26]沈建华,杨艳琴.MSP430系列16位超低功耗单片机原理与应用[M].清华大学出版社.2003.2
[27]超声波特性http://szbaiyi18a.dz-z.com/Files.html
[28]孙传友,孙晓彬,汉泽西等.测控系统原理与设计[M].北京航空航天大学出版社。2006.1
[29]OP27GP Data Sheet[M]. ADI.2001
[30]THS3001CD Data sheet[M]. TEXAS INSTRUMENTS.1999
[31]TLC5540A, 8-BIT HIGH-SPEEDANALOG-TO-DIGITAL CONVERTERS. www.ti.com
[32]TLC5540/TLC5510/TLC5510A Evaluation Module User’s Guide. www.ti.com
[33]TPS7350QP Data Sheet[M]. TEXAS INSTRUMENTS.1999
[34]LM1117 Data Sheet[M].National Semiconductor.1999
[35]TPS60403DBV Data Sheet[M]. TEXAS INSTRUMENTS.2001
[36]CY731021CV33-12ZC Data Sheet[M].Cypress
[37]ADXL202E Data Sheet[M].Analog Device
[38]ADXRS612 Data Sheet[M].Analog Device
[39]MSP430 IAR Embedded Workbench? IDE User Guide. http://www.msp430.com
[40]秦龙.MSP430单片机常用模块与综合系统实例精讲[M].电子工业出版社,2007.7
[41]高亚楠,陈家斌.惯性导航系统中的Kalman滤波技术[J].2005,30(1):1-4
[42]郭秀中.惯导系统陀螺仪理论[M].国防工业出版社,1996
[43]黄德鸣,程禄.惯性导航系统[M].国防工业出版社,1986
[44]徐建.基于DSP的惯性导航系统设计与实现[D].大连:大连理工大学,2006,12
[45]张春惠.高精度捷联式惯性导航系统算法研究[D].哈尔滨:哈尔滨工程大学,2005.3
[46]樊荣.捷联惯性导航系统初始对准方法研究及其仿真[D].南京:南京理工大学,2006.6
[47]丁文娟.捷联惯性/里程仪/伪卫星车载组合导航系统研究[D].西安:西北工业大学,2006.2
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