期刊文献+

基于激光雷达空气净化导航机器人的研究与设计 被引量:2

Research and design of navigation robot for air purification based on lidar
下载PDF
导出
摘要 基于二维激光雷达设计了一种适用于室内空气净化的自主导航移动机器人。针对目前RBPF算法因容易出现粒子退化而导致定位精度差、建图速度慢等问题,采用了一种改进的RBPF算法进行地图的构建,提高定位精度和建图速率的同时实现对机器人的自主导航。机器人在移动时会实时检测当前环境信息,当出现数据异常便自动开启空气净化装置,并将数据实时传输到云端服务器供用户监控。经实验验证,本系统可以更加快速地构建未知室内环境地图,并有效地完成多点室内空气净化任务。 Based on two-dimensional laser radar,this paper proposes a robot suitable for indoor air purification and autonomous navigation.For the problems that the RBPF algorithm is prone to particle degradation,which leads to poor positioning accuracy and slow mapping speed.An improved RBPF algorithm is used to construct the map,to im-prove the positioning accuracy and the mapping rate,and to realize the autonomous navigation of the robot.When the robot moves,it will detect the current environmental information in time.When the data is abnormal,the air purification device will be automatically turned on,and the data will be transmitted to the cloud server in time for monitoring by the user.The experiment proves that the system can construct the unknown indoor environment map more quickly and ef-fectively complete the multi-point indoor air purification task.
作者 马静 朴金宁 徐军 杨帆 MA Jing;PIAO Jinning;XU Jun;YANG Fan(School of Automation,Harbin University of Science and Technology,Harbin 150080,China)
出处 《激光杂志》 北大核心 2019年第11期150-153,共4页 Laser Journal
关键词 激光雷达 地图构建 改进RBPF算法 空气净化 数据可视化 lidar map construction improved RBPF algorithm air purification data visualization
  • 相关文献

参考文献9

二级参考文献93

  • 1庄严,王伟,王珂,徐晓东.移动机器人基于激光测距和单目视觉的室内同时定位和地图构建[J].自动化学报,2005,31(6):925-933. 被引量:55
  • 2何运兵,纪红兵,王乐夫.室内甲醛催化氧化脱除的研究进展[J].化工进展,2007,26(8):1104-1109. 被引量:36
  • 3张妍,李振海.室内空气净化器性能指标的探讨[J].环境与健康杂志,2007,24(6):453-455. 被引量:16
  • 4Durrant-Whyte H,Bailey T.Simultaneous localization and map- ping:part I[J].IEEE Trans,on Robotics and Automation Ma- gazine,2006,13(2):99-110.
  • 5Bailey T,Durrant-Whyte H.Simultaneous localization and map- ping:part II[J].IEEE Trans,on Robotics and Automation Magazine,2006,13(3):108-117.
  • 6Holmes S,Klein G,Murray D W.An O(N2)square root un- scented Kalman filter for visual simultaneous localization and mapping[J],IEEE Trans,on Pattern Analysis and Machine In- telligence,2009,31(7):1251-1263.
  • 7Hwang S Y,Song J B.Monocular vision-based SLAM in indoor environment using comer,lamp,and door features from up- ward-looking camera[J].IEEE Trans.on Industrial Electro- flics,2011,58(10):4804-4812.
  • 8MontemerIo M.FastSLAM:a factored solution to the simulta- neous localization and mapping problem with unknown data asso- ciation[D].Pennsylvania:Carnegie Mellon University,2003.
  • 9Thrun S,Montemerlo M,Koller D,et al.FastSLAM:an effi- cient solution to the simultaneous localization and mapping pro- blem with unknown data association[J].Machine Learning,2004,4(3):380-407.
  • 10Kim C,Sakthivel R,Chung W K.Unscented FastSLAM:a ro- bust and efficient solution to the SLAM problem[J].IEEE Trans,on Robotics,2008,24(4):808-820.

共引文献86

同被引文献29

引证文献2

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部