[1]孙凤池,宋萌,刘光.一种无线传感器信号衰减自适应测距模型[J].智能系统学报,2012,7(3):214-219.
SUN Fengchi,SONG Meng,LIU Guang.An adaptive ranging model based on energy distance loss of wireless sensors[J].CAAI Transactions on Intelligent Systems,2012,7(3):214-219.
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SUN Fengchi,SONG Meng,LIU Guang.An adaptive ranging model based on energy distance loss of wireless sensors[J].CAAI Transactions on Intelligent Systems,2012,7(3):214-219.
一种无线传感器信号衰减自适应测距模型
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
7
期数:
2012年第3期
页码:
214-219
栏目:
学术论文—机器感知与模式识别
出版日期:
2012-06-25
- Title:
- An adaptive ranging model based on energy distance loss of wireless sensors
- 文章编号:
- 1673-4785(2012)03-0214-06
- Keywords:
- robot; wireless sensors; energy distance loss; adaptive ranging model
- 分类号:
- TP24
- 文献标志码:
- A
- 摘要:
- 使用无线传感器作为路标实现机器人定位具有许多优势，但无线传感器与机器人之间的距离测量存在易受环境干扰的缺点.为了解决这一难题，在对无线传感器射频信号衰减原理分析的基础上，基于在线学习的方法为无线传感器路标建立自适应的信号衰减测距模型.由于模型学习过程是在线进行的，环境因素对无线信号传播衰减的影响被包含在模型中，故此测距模型提高了对无线信号传播环境的适应能力.此外，把路标的身份作为测距模型的输入，从而区分了传感器个体的差异，实验结果证明了这种建模方法在提高无线传感器测距精度方面的有效性.
- Abstract:
- Using wireless sensors as landmarks for mobile robot localization has many advantages, but the process of measuring the distance between the robot and wireless sensor is susceptible to environmental disturbance. To solve this difficult problem, the radio frequency signal decay theory was analyzed, and an adaptive signal decay range model was established for wireless landmarks based on the online learning method. The model learning was completed online, so the effect of the environmental factors on the decay of wireless signal transmission was included in the online modeling process; correspondingly, the adaptive ability of the model was improved. In addition, the identity numbers of different wireless landmarks were also input into the artificial neural network model so that differences among certain sensors were considered. Experiments show that the proposed modeling method is effective for improving wireless sensor ranging precision.
- 参考文献/References:
-
［1］陈卫东，张飞．移动机器人的同步自定位与地图创建研究进展［J］．控制理论与应用, 2005, 22(3): 455460.
CHEN Weidong, ZHANG Fei. Review on the achievements in simultaneous localization and map building for mobile robot［J］. Control Theory and Applications, 2005, 22(3): 455460.
［2］魏芳，董再励，孙茂相，等．用于移动机器人的视觉全局定位系统研究［J］．机器人, 2001, 23(5): 400403, 420.
?WEI Fang, DONG Zaili, SUN Maoxiang, et al. A vision global location system technique for mobile robots［J］. Robot, 2001, 23(5): 400403, 420.
［3］蔡自兴，王勇，王璐．基于角点聚类的移动机器人自然路标检测与识别［J］．智能系统学报, 2006, 1(1): 5256.
CAI Zixing, WANG Yong, WANG Lu. Corner cluster based detection and recognition of natural landmark for mobile robots［J］. CAAI Transactions on Intelligent Systems, 2006, 1(1): 5256.
［4］LOPEZ D G, SJO K, PAUL C, et al. Hybrid laser and vision based object search and localization［C］//IEEE International Conference on Robotics and Automation. Pasadena, USA, 2008: 26362643.
［5］陆军，孙凌丽，穆海军，等．基于全景视觉的机器人相互定位的研究［J］．哈尔滨工程大学学报, 2010, 31(4): 457464.
LU Jun, SUN Lingli, MU Haijun， et al. Mutual localization of mobile robots using an omnivision system［J］. Journal of Harbin Engineering University, 2010, 31(4): 457464.
［6］HAHNEL D, BURGARD W, FOX D, et al. Mapping and localization with RFID technology［C］//IEEE International Conference on Robotics and Automation. New Orleans, USA, 2004: 10151020.
［7］CHO K, KANG M S, PARK S, et al. Development of indoor localization system using ultrasonic sensors［C］//International Symposium on Robotics (ISR). Seoul, Korea, 2008: 211215.
［8］孙凤池，苑晶．一种用于未知环境探索的可动态配置路标系统［J］．机器人, 2010, 32(1): 7782.
SUN Fengchi, YUAN Jing. A dynamically configurable landmark system for unknown environment exploration［J］. Robot, 2010, 32(1): 7782.
［9］PRIYANTHA N B, CHAKRABORTY A, BALAKRISHNAN H. The cricket locationsupport system［C］//Sixth Annual International Conference on Mobile Computing and Networking. New York, USA, 2000: 3243.
［10］石鹏，徐凤燕，王宗欣．基于传播损耗模型的最大似然估计室内定位算法［J］．信号处理, 2005, 21(5): 502504.
SHI Peng, XU Fengyan, WANG Zongxin. A maximumlikelihood indoor location algorithm based on indoor propagation loss model［J］. Signal Processing, 2005, 21(5): 502504.
［11］VORST P, ZELL A. Semiautonomous learning of an RFID sensor model for mobile robot selflocation［C］//European Robotics Symposium. Prague, Czech Republic, 2008: 273282.
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备注/Memo
收稿日期： 2011-08-08.网络出版日期：2012-05-08.
基金项目：国家自然科学基金资助项目（61175083, 61175085）；天津市自然科学基金资助项目(10JCYBJC07600).
通信作者：孙凤池．E-mail: fengchisun@nankai.edu.cn.
作者简介：
孙凤池，男，1973年生，副教授,博士.主要研究方向为智能机器人、嵌入式系统.
宋萌，女，1986年生，硕士研究生，主要研究方向为智能机器人、模式识别.
刘光，男，1984年生，硕士研究生，主要研究方向为智能机器人.
更新日期/Last Update:
2012-09-05