温室移动机器人复合栅格地图构建方法研究
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摘要
针对温室环境中机器人依靠自身携带的传感器无法获取全面的环境信息,从而常导致路径规划错误的问题,提出了一种结合外部传感器系统获取温室环境信息,构建复合栅格地图的方法。利用无线传感器网络定时采集对机器人通过性有影响的温度、湿度环境信息,并发送给机器人;当温度或湿度数据的变化率达到设定阈值时,机器人利用阈值分割和插值法分别建立温度和湿度栅格地图;将温度栅格地图、湿度栅格地图与室内障碍物栅格地图相结合,构建动态更新的复合栅格地图。经测试,采用常规A*算法规划路径时,基于环境数据变化率阈值设定为±10%的复合栅格地图的成功率和完成时间,分别是基于普通栅格地图成功率的2. 5倍和1. 05倍。结果表明,复合栅格地图能提高路径规划的成功率,并且不会由于动态更新复合栅格地图,导致机器人响应时间明显增加,实时性能满足系统的实际需求。
A mobile robot based on a normal grid map could not obtain the comprehensive environmental information in a greenhouse because of the less number and limited location of carried sensors. An incorrect planning path may arise. The system adopted a way to build a composite grid map based on the comprehensive environmental information in greenhouse. Firstly,wireless sensor network regularly collected data of temperature and humidity and sent them to the robot. These data had heavy impacts on mobile robot's passing through in greenhouse. Secondly,when the rate of change of temperature or humidity data reached the threshold,the system used the method of threshold segmentation and interpolation to establish the grid maps for temperature and humidity respectively. Finally,the system combined the grid map for temperature,the grid map for humidity and the grid map for interior material barrier in a greenhouse to build a dynamically updated composite grid map. After testing,when the system adopted the A*algorithm,the rate of success to avoid area of high temperature and high humidity based on the composite grid map at threshold of ± 10% was 2. 5 times to normal grid map. The time of completion was 1. 05 times to normal grid map. The results show that the composite grid map can improve the success rate of the path planning and the robot does not meet the problem of slow response of the robot due to the dynamic updating of the composite grid map. The real-time performance satisfies the actual requirements of the system.
A mobile robot based on a normal grid map could not obtain the comprehensive environmental information in a greenhouse because of the less number and limited location of carried sensors. An incorrect planning path may arise. The system adopted a way to build a composite grid map based on the comprehensive environmental information in greenhouse. Firstly,wireless sensor network regularly collected data of temperature and humidity and sent them to the robot. These data had heavy impacts on mobile robot's passing through in greenhouse. Secondly,when the rate of change of temperature or humidity data reached the threshold,the system used the method of threshold segmentation and interpolation to establish the grid maps for temperature and humidity respectively. Finally,the system combined the grid map for temperature,the grid map for humidity and the grid map for interior material barrier in a greenhouse to build a dynamically updated composite grid map. After testing,when the system adopted the A*algorithm,the rate of success to avoid area of high temperature and high humidity based on the composite grid map at threshold of ± 10% was 2. 5 times to normal grid map. The time of completion was 1. 05 times to normal grid map. The results show that the composite grid map can improve the success rate of the path planning and the robot does not meet the problem of slow response of the robot due to the dynamic updating of the composite grid map. The real-time performance satisfies the actual requirements of the system.
引文
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[17]李进燕,朱征宇,刘琳,等.基于行程时间多步预测的实时路径导航算法[J].计算机应用研究,2013,30(2):346-349,353.(LiJinyan,Zhu Zhengyu,Liu Lin,et al. Real-time navigation algorithmbased on multi-step travel time prediction[J]. Application Researchof Computers,2013,30(2):346-349,353.)
[18]赵德安,贾伟宽,张云,等.农业机器人自主导航改进自适应滤波控制器研究[J].农业机械学报,2015,46(5):1-6.(Zhao Dean,Jia Weikuan,Zhang Yun,et al. Design of agricultural robot autono-mous navigation control based on improved self-adaptive filter[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(5):1-6.)
[2]胡静涛,高雷,白晓平,等.农业机械自动导航技术研究进展[J].农业工程学报,2015,31(10):1-10.(Hu Jingtao,Gao Lei,Bai Xiao-ping,et al. Review of research on automatic guidance of agricultural ve-hicles[J]. Transactions of the Chinese Society of Agricultural En-gineering,2015,31(10):1-10.)
[3]高国琴,李明.基于K-means算法的温室移动机器人导航路径识别[J].农业工程学报,2014,30(7):25-33.(Gao Guoqin,LiMing. Navigating path recognition for greenhouse mobile robot basedon K-means algorithm[J]. Transactions of the Chinese Society ofAgricultural Engineering,2014,30(7):25-33.)
[4]王新忠,韩旭,毛罕平,等.基于最小二乘法的温室番茄垄间视觉导航路径检测[J].农业机械报,2012,43(6):161-166.(WangXinzhong,Han Xu,Mao Hanping,et al. Navigation line detection of to-mato ridges in greenhouse based on least square method[J]. Tran-sactions of the Chinese Society for Agricultural Machinery,2012,43(6):161-166.)
[5]贾士伟,李军民,邱权,等.基于激光测距仪的温室机器人道路边缘检测与路径导航[J].农业工程学报,2015,31(13):39-45.(Jia Shiwei,Li Junmin,Qiu Quan,et al. New corridor edge detectionand navigation for greenhouse mobile robots based on laser scanner[J]. Transactions of the Chinese Society of Agricultural Engi-neering,2015,31(13):39-45.)
[6]曹鹏飞,赵振.无线传感器网络关键技术研究综述[J].微计算机信息,2012,28(9):389-391,406.(Cao Pengfei,Zhao Zhen. Re-search of key technologies in wireless sensor network[J]. Control&Automation,2012,28(9):389-391,406.)
[7] Harun A,Ndzi D,Ramli M F,et al. Signal propagation in aquacultureenvironment for wireless sensor network applications[J]. Progress inElectromagnetics Research-Pier,2012,131(4):477-494.
[8] Tuna G,Gungor V C,Gulez K. An autonomous wireless sensor networkdeployment system using mobile robots for human existence detectionin case of disasters[J]. Ad hoc Network,2014,13(2):54-68.
[9] Li Xu,Lille I,Falcon R,et al. Servicing wireless sensor networks bymobile robots[J]. IEEE Communication Magazine,2012,50(7):147-154.
[10]Lee W Y,Hur K,Hwang K I,et al. Mobile robot navigation usingwireless sensor networks without localization procedure[J]. WirelessPersonal Communication,2012,62(2):257-275.
[11]张文,刘勇,张超凡,等.基于方向A*算法的温室机器人实时路径规划[J].农业机械学报,2017,48(7):22-28.(Zhang Wen,LiuYong,Zhang Chaofan,et al. Real-time path planning of greenhouserobot based on directional A*algorithm[J]. Transactions of theChinese Society for Agricultural Machinery,2017,48(7):22-28.)
[12]王红卫,马勇,谢勇,等.基于平滑A*算法的移动机器人路径规划[J].同济大学学报:自然科学版,2010,38(11):1647-1650,1655.(Wang Hongwei,Ma Yong,Xie Yong,et al. Mobile robot optimal pathplanning based on smoothing A*algorithm[J]. Journal of Tongji Uni-versity:Natural Science Edition,2010,38(11):1647-1650,1655.)
[13]马飞,杨皞屾,顾青,等.基于改进A*算法的地下无人铲运机导航路径规划[J].农业机械学报,2015,46(7):303-309.(Ma Fei,Yang Haoshen,Gu Qing,et al. Navigation path planning of unmannedunderground LHD based on improved A*algorithm[J]. Transactionsof the Chinese Society for Agricultural Machinery,2015,46(7):303-309.)
[14]简毅,张月.移动机器人全局覆盖路径规划算法研究进展与展望[J].计算机应用,2014,23(10):2844-2849.(Jian Yi,ZhangYue. Complete coverage path planning algorithm for mobile robot:pro-gress and prospect[J]. Journal of Computer Applications,2014,23(10):2844-2849.)
[15] Vakilian K A,Massah J. A farmer-assistant robot for nitrogen fertili-zing management of greenhouse crops[J]. Computer Electronic Ag-riculture,2017,139(12):153-163.
[16]李逃昌,胡静涛,高雷.基于级联式控制策略的农业机械鲁棒自适应路径跟踪控制[J].机器人,2014,36(2):241-249.(LiTaochang,Hu Jingtao,Gao Lei. Robust adaptive path tracking controlof agricultural machines based on cascaded control strategy[J]. Ro-bot,2014,36(2):241-249.)
[17]李进燕,朱征宇,刘琳,等.基于行程时间多步预测的实时路径导航算法[J].计算机应用研究,2013,30(2):346-349,353.(LiJinyan,Zhu Zhengyu,Liu Lin,et al. Real-time navigation algorithmbased on multi-step travel time prediction[J]. Application Researchof Computers,2013,30(2):346-349,353.)
[18]赵德安,贾伟宽,张云,等.农业机器人自主导航改进自适应滤波控制器研究[J].农业机械学报,2015,46(5):1-6.(Zhao Dean,Jia Weikuan,Zhang Yun,et al. Design of agricultural robot autono-mous navigation control based on improved self-adaptive filter[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(5):1-6.)
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