期刊文献+

一种基于SLAM的多功能探索机器人设计 被引量:9

Design of Multifunctional Exploration Robot Based on SLAM
下载PDF
导出
摘要 针对机器人在未知环境下导航和捕获目标问题,设计了一种基于SLAM技术的探索机器人,并提出一种融合机器视觉与SLAM算法的导航方法。机器人由主控模块、底层驱动模块、摄像头、激光雷达和机械臂构成。通过在安装有开源机器人操作系统(ROS)的机器人上进行实验。实验结果表明,通过上述方法能够构建可靠有效的地图并规划出合理的移动路线,完成目标物体的定位和捕获。 Aiming at the problem that the robot navigates and captures the target in an unknown environment,a robot based on SLAM technology was designed and a navigation method combining machine vision and SLAM algorithm was proposed.The robot consists of a main control module,an underlying drive module,a camera,a laser radar and a robotic arm.Experiments were performed on a robot with an open source robotic operating system(ROS)installed.The experimental results show that:Through the above method,a reliable and effective map can be constructed and a reasonable moving route can be planned to complete the positioning and capturing of the target object.
作者 王嵘 万永菁 WANG Rong;WAN Yongjing(School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China)
出处 《机械与电子》 2019年第9期51-53,58,共4页 Machinery & Electronics
基金 国家自然科学基金资助项目(61872143) 2018年教育部产学合作协同育人项目(201801315013) 2018年华东理工大学本科实验实践教学改革与建设项目(2018)
关键词 即时定位和地图构建 图像识别 路径规划 SLAM image recognition path planning
  • 相关文献

参考文献7

二级参考文献42

  • 1周武,赵春霞.一种改进的边缘粒子滤波SLAM方法[J].华中科技大学学报(自然科学版),2008,36(S1):181-185. 被引量:4
  • 2王璐,蔡自兴.未知环境中移动机器人并发建图与定位(CML)的研究进展[J].机器人,2004,26(4):380-384. 被引量:45
  • 3Daum F. Nonlinear filters: Beyond the Kalman filter [J]. IEEE A and E Systems Magazine, 2005, 20(8) : 177-183.
  • 4Bailey T J,Neito J G. Consistency of the EKF-SLAM algorithm[C]//Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems. Beijing: IEEE,2006: 3562-3568.
  • 5Banani S A, Masnadi-Shirazi M A. A new version of unscented Kalman filter[C] // Proceedings of World Academy of Science, Engineering and Technology. Amsterdam: WASET, 2007:192-197.
  • 6Gordon N J, Salmond D J, Smith A F M. Novel approach to nonlinear/non-gaussian bayesian state estimation[J]. IEE Proceedings: F, 1993, 140(2): 107- 113.
  • 7Smith R, Cheeseman P. On the representation and estimation of spatiail uncertainty[J]. The lntenational Journal of Robotics Reseach, 1986, 5(4): 56-58.
  • 8Montemerlo M, Thrun S, Koller D, et al. FastSLAM 2.0: an improved particle filtering algorithm for simultaneous localization and mapping that provably converges[C]//Proceedings of the International Conference on Artificial Intelligence. Acapulco:AAAI, 2003: 1151-1156.
  • 9Montemerlo M, Thrun S, Koller D, et al. FastSLA M, a factored solution to the simultaneous localization and mapping problem[C]//Proceedings of the National Conference on Artificial Intelligence. Cambridge~AAAI, 2002:593-598.
  • 10Lee, J. , Kao, H. A. , and Yang, S. , Service Innovation and Smart Analytics for Industry 4. 0 and Big Data Environment [ J ]. Procedia Cirp, vol. 16, 2014, pp. 3-8.

共引文献70

同被引文献54

引证文献9

二级引证文献27

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