集群机器人无线网络时间同步与定位技术研究
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摘要
无线传感器网络和多移动机器人技术综合了无线通信、机械、计算机、电子等多个学科,是近年来比较受重视的两个研究领域。基于两者优势结合,集群机器人节点能够在未知环境下实现近距离和远距离的定位。
本文介绍了国内外无线传感器网络与移动机器人领域的相关研究成果和关键技术,对无线传感器网络和集群机器人相关技术进行了比较。通过对无线传感器网络典型时间同步算法的研究,提出了一种改进的时间同步算法,并对节点间同步误差进行估计。通过对两者定位技术的分析,提出了基于超声波测距和无线信号衰减的定位方式。节点之间的距离小于5m时,集群机器人节点可采用超声波测距来感知周围信息进行定位；远距离大于5m时,节点采用RSSI定位,将测得的距离信息进行融合,通过三边定位算法计算出所处二维位置坐标。
集群机器人无线传感器网络节点时间同步和定位系统研究包括集群机器人节点研究、时间同步算法研究和定位技术研究三个部分。集群机器人采用三轮微型车体结构,节点硬件设计主要包括无线通信模块、电机驱动模块、超声波传感器测距模块、串口通信模块和电源模块的设计。本文的时间同步算法综合双向同步和洪泛的思想,保证同步精度的前提下,减少信息的交换次数。节点定位采用基于测距技术的的定位机制,主要利用RSSI辅助以超声波渡越时间法对移动机器人节点在未知环境下进行定位。
基于无线传感器网络的集群机器人节点分别在室内和室外进行部署和定位试验,运行良好,能够很好的实现移动节点在二维平面内的定位,证实了节点设计和算法的合理性。通过无线传感器网络提高了集群机器人对周围环境的感知能力,同时改善了网络节点的动态性能,在移动目标跟踪等方面将会有广阔的应用前景。
In recent years, both Wireless Sensor Networks(WSN) and mobile multi-robot technology have been integrated into wireless communications, machinery, computers, electronics and other disciplines, and highly valued in research field. Based on the advantages, swarms of robotic nodes can achieve to the location of close and long-distance in an unknown environment.
The related research and key technologies at home and abroad in the field of WSN and mobile multi-robot had been introduced in this paper, and then the comparison had also been given out. After the research for typical time synchronization in WSN, an improved algorithm was proposed and the synchronization error between the nodes was estimated. Through the analysis of these two positioning technology, the way of positioning with ultrasonic and radio signal attenuation was also proposed. When the distance was less than 5 meters, swarms of robotic nodes could perceive of the surrounding information and complete their positioning by using ultrasonic, whereas, nodes would start Received Signal Strength Indication(RSSI) automatically for positioning. Depending on fusion of the distance information, nodes could calculate the position in two-dimensional coordinates with the triangular localization algorithms.
The research about time synchronization and positioning system of nodes was divided into three parts, that is swarm of robotic nodes, time synchronization algorithm and positioning technology. Swarms of robots could be designed in mini-car with three wheels for the structure. The nodes hardware design mainly includes:wireless communication module, motor drive module, ultrasonic sensors module for ranging, serial communication module and power module. Based on Two-way Synchronization and flooding, the proposed synchronization algorithm in this paper could reduce the number of exchange of information under the premise of synchronization precision. Localization for nodes uses ranging mechanism, by supporting RSSI and transit time of ultrasonic, all the nodes could achieve to positioning in an unknown environment.
Swarms of robotic nodes based on WSN had been deployed for positioning test in both indoor and outdoor and could run well. With the mobile nodes had achieved a good positioning in the two-dimensional area, it confirmed the rationality of node design and algorithm. WSN can improve the capability of apperceiving surrounding environment for swarm of robots, and at the same time, the dynamic performance of the network nodes could be increased. By combination of these two technologies, it will have broad application prospects in the tracking of mobile target and others.
本文介绍了国内外无线传感器网络与移动机器人领域的相关研究成果和关键技术,对无线传感器网络和集群机器人相关技术进行了比较。通过对无线传感器网络典型时间同步算法的研究,提出了一种改进的时间同步算法,并对节点间同步误差进行估计。通过对两者定位技术的分析,提出了基于超声波测距和无线信号衰减的定位方式。节点之间的距离小于5m时,集群机器人节点可采用超声波测距来感知周围信息进行定位；远距离大于5m时,节点采用RSSI定位,将测得的距离信息进行融合,通过三边定位算法计算出所处二维位置坐标。
集群机器人无线传感器网络节点时间同步和定位系统研究包括集群机器人节点研究、时间同步算法研究和定位技术研究三个部分。集群机器人采用三轮微型车体结构,节点硬件设计主要包括无线通信模块、电机驱动模块、超声波传感器测距模块、串口通信模块和电源模块的设计。本文的时间同步算法综合双向同步和洪泛的思想,保证同步精度的前提下,减少信息的交换次数。节点定位采用基于测距技术的的定位机制,主要利用RSSI辅助以超声波渡越时间法对移动机器人节点在未知环境下进行定位。
基于无线传感器网络的集群机器人节点分别在室内和室外进行部署和定位试验,运行良好,能够很好的实现移动节点在二维平面内的定位,证实了节点设计和算法的合理性。通过无线传感器网络提高了集群机器人对周围环境的感知能力,同时改善了网络节点的动态性能,在移动目标跟踪等方面将会有广阔的应用前景。
In recent years, both Wireless Sensor Networks(WSN) and mobile multi-robot technology have been integrated into wireless communications, machinery, computers, electronics and other disciplines, and highly valued in research field. Based on the advantages, swarms of robotic nodes can achieve to the location of close and long-distance in an unknown environment.
The related research and key technologies at home and abroad in the field of WSN and mobile multi-robot had been introduced in this paper, and then the comparison had also been given out. After the research for typical time synchronization in WSN, an improved algorithm was proposed and the synchronization error between the nodes was estimated. Through the analysis of these two positioning technology, the way of positioning with ultrasonic and radio signal attenuation was also proposed. When the distance was less than 5 meters, swarms of robotic nodes could perceive of the surrounding information and complete their positioning by using ultrasonic, whereas, nodes would start Received Signal Strength Indication(RSSI) automatically for positioning. Depending on fusion of the distance information, nodes could calculate the position in two-dimensional coordinates with the triangular localization algorithms.
The research about time synchronization and positioning system of nodes was divided into three parts, that is swarm of robotic nodes, time synchronization algorithm and positioning technology. Swarms of robots could be designed in mini-car with three wheels for the structure. The nodes hardware design mainly includes:wireless communication module, motor drive module, ultrasonic sensors module for ranging, serial communication module and power module. Based on Two-way Synchronization and flooding, the proposed synchronization algorithm in this paper could reduce the number of exchange of information under the premise of synchronization precision. Localization for nodes uses ranging mechanism, by supporting RSSI and transit time of ultrasonic, all the nodes could achieve to positioning in an unknown environment.
Swarms of robotic nodes based on WSN had been deployed for positioning test in both indoor and outdoor and could run well. With the mobile nodes had achieved a good positioning in the two-dimensional area, it confirmed the rationality of node design and algorithm. WSN can improve the capability of apperceiving surrounding environment for swarm of robots, and at the same time, the dynamic performance of the network nodes could be increased. By combination of these two technologies, it will have broad application prospects in the tracking of mobile target and others.
引文
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[27]Takemura Y, Sato M, Ishii K. Toward Realization of Swarm Intelligence Mobile Robots[J]. International Congress Series 1291.2006:273-276 P
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[29]李文锋.无线传感器网络与移动机器人控制[M].北京：科学出版社.2009,1：8-10页
[30]沈建华,杨艳琴,崔骁曙.MSP430系列16位超低功耗单片机原理与应用[M].北京：清华大学出版社.2006,12(5)：21-22页
[31]魏小龙.MSP430系列单片机接口技术及系统设计实例[M].北京：北京航空航天大学出版社.2002：14-16页
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[2]DeHannis A, Wise K. A Wireless Microsystem for the Remote Sensing of Pressure, Temperature and Relative Humidity[J]. IEEE Micro-electric mechanical Systems.2005,(14):12-15 P
[3]Ishii K, Miki T. Mobile Robot Platforms for Artificial and Swarm Intelligence Researches[C]. International Congress Series.2007:39-42 P
[4]Prencipe G. On the Feasibility of Gathering by Autonomous Mobile Robots [C]. Proceedings of 12th International Conference on Structural Information and Communication Complexity.2005:246-261 P
[5]Holger K, Willig A. Protocols and Architectures for Wireless Sensor Networks[J]. John Wiley and Sons.2005:26-28 P
[6]孙利民,李建中,陈渝等.无线传感器网络[M].北京：清华大学出版社.2005.5：4-5页,59-60页,157页
[7]王殊,阎毓杰,胡富平等.无线传感器网络的理论及应用[M].北京：北京航空航天大学出版社.2007,1：2-3页,173-174页,147-148页
[8]Chang J H, Tassiulas L. Routing for Maximum System Lifetime in Wireless Ad-hoc Networks[C]. Proceedings of the 37th Annual Allerton Conference on Communications.1999,(9):22-31 P
[9]Jia X Y, Wang C. The Security Routing Research for WSN in the Application of Intelligent Transport System[C]. Proceedings of the 2006 IEEE International Conference on Mechatronics and Automation.2006: 45-46 P
[10]Alzaid H, Foo E, Nieto J G. Secure Data Aggregation in Wireless Sensor Network:a survey[C]. Proceedings of the 6th Australasian Information Security Conference.2008:113-118 P
[11]张仕斌,谭三,易勇等编著.网络安全技术[M].北京：清华大学出版社.2004,8:35-36 P
[12]Savarese C, Rabaey J M, Beutel J. Locationing in Distributed Ad-Hoc Wireless Sensor Network[C]. Proceedings of IEEE International Conference on Acoustics, Speech and Signal, Salt Lake, USA:IEEE Computer Society. 2001(4):2037-2040 P
[13]Tian H, Chengdu H, Brian M B, etal. Range-free Localization Schemes in Large Scale Sensor Networks[C]. Proceedings of 9th annual international conference on Mobile computing and networking.2003:81-95 P
[14]Warneke B, Last M, Liebowitz B, etal. Smart Dust:Communicating with a Cubic-millimeter Computer[J]. IEEE Computer Magazine,2001,34(1): 44-51 P
[15]Arampatzis T H, Lygeros J, Manesis S. A Suvey of Applications of Wireless Sensors and Wireless Sensor Networks[C]. Proceedings of the 13th Mediterranean Conference on Control and Automation.2005:719-720 P
[16]Mohan A, Malshe A P, Aravamudhan S, etal. MEMS Pressure Sensor and Packaging for Harsh Oceanic Environment[C]. Proceeding of 54th IEEE Electronic Components and Technology Conference.2004, (1):948-950 P
[17]Wark T, Crossman C, Hu W, etal. The Design and Evaluation of a Mobile Sensor Actuator Network for Autonomous Anminal Control[C]. Proceedings of the 6th International Conference on Information proceeding in Sensor Networks.2007,4:12-14 P
[18]Seok Y K, Joonho G, Jinbong K, etal. A Miniaturized Low-power Wireless Remote Environmental Monitoring System based on Electro-chemical Analysis[J]. Sensors and Actuators.2004, (102):27-34 P
[19]Stankovic J A, Cao Q, Doan T, etal. Wireless Sensor Networks for in-home Healthcare:Potential and Challenges[J].In Proceedings of Workshop on High Confidence Medical Devices Software and Systems.2005:12 P
[20]Mainwaring A, Polastre J, Szewczyk R, etal. Wireless Sensor Networks for Habitat Monitoring[J]. Proceedings of the ACM International Workshop on Wireless Sensor Networks and Applications.2002:141-145 P
[21]李善仓,张克旺.无线传感器网络原理与应用[M].北京：机械工业出版社.2008,3：18-19页,16页
[22]于宏毅,李鸥,张效义.无线传感器网络理论,技术与实现[M].北京：国防工业出版社.2008,9：7-8页,85-88页,112页
[23]Izumi T, Katayama Y, Inuzuka N, etal.Gathering Autonomous Mobile Robots with Dynamic Compasses:An optimal result, In:Proceeding of 21st System.Distribute Computing.2007:15-18 P
[24]张毅,罗元,郑太雄.移动机器人技术及其应用[M].北京：电子工业出版社.2007,9：141-142页,317页,8-12页
[25]Chaimovicz L, Campos M F, Kumar V. Dynamic Role Assignment for Cooperative Robots[C]. Proceedings of the 2002 IEEE International Conference on Robotics and Automation.2002,5:293-298 P
[26]谭民,王硕,曹志强.多机器人系统[M].北京：清华大学出版社.2005,4：6-7页,2-4页
[27]Takemura Y, Sato M, Ishii K. Toward Realization of Swarm Intelligence Mobile Robots[J]. International Congress Series 1291.2006:273-276 P
[28]Efrima A, David P D. Distributed Algorithms for Partitioning a Swarm of Autonomous Mobile Robots[J]. Theoretical Computer Science 410. 2009:1355-1368 P
[29]李文锋.无线传感器网络与移动机器人控制[M].北京：科学出版社.2009,1：8-10页
[30]沈建华,杨艳琴,崔骁曙.MSP430系列16位超低功耗单片机原理与应用[M].北京：清华大学出版社.2006,12(5)：21-22页
[31]魏小龙.MSP430系列单片机接口技术及系统设计实例[M].北京：北京航空航天大学出版社.2002：14-16页
[32]艾春丽,张凤登,刘荣鹏.基于CC2500的无线楼宇跟踪系统软硬件设计[J].现代电子技术.2007,(19)：138页,139-140页
[33]CC2500数据设计手册.www.ti.com.cn. TI:1-5页,13-15页,26-28页
[34]Rivard F E, Bisson J, Michaud F O, Letourneau D. Ultrasonic Relative Positioning for Multi-robot Systems[C]. IEEE International Conference on Robotics and Automation.2008,(5):19-23 P
[35]超声波测距. www.ti.com.cnTI：5-10页
[36]王亚磊.无线传感器网络中的时间同步技术的研究[D].南京邮电大学硕士论文.2008：14页
[37]李晓维,徐勇军,任丰原.无线传感器网络技术[M].北京：北京理工大学出版社.2007,8：241-242页,265页
[38]Ganeriwal S, Kumar R, Srivastava M B. Timing-sync Protocol for Sensor Network[C]. In:Proceeding of the 1st International Conference on Embedded Networked Sensor System,2003:138-149 P
[39]Thomas Y H, Shi Y. On Node Lifetime Problem for Energy Constrained Wireless Sensor Networks[J]. Mobile Networks and Applications.2005,(10): 865-878 P
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