期刊文献+

基于双目视觉的服务机器人仿人机械臂控制 被引量:10

Binocular Vision-Based Humanoid Manipulator Control for Service Robot
下载PDF
导出
摘要 机械臂逆运动学、目标识别与定位是服务机器人手臂控制中的关键技术.为了更好地与复杂多变的非结构化环境进行交互,提出一种应用于服务机器人平台的基于双目视觉的仿人机械臂控制方法.给出一种针对6自由度手臂的逆解算法,并采用基于双目视觉与颜色分割的目标识别方法.然后,根据识别出的目标三维坐标信息控制机械臂完成特定任务.本方法在家庭服务机器人上得到了验证. Inverse kinematics, object localization and manipulation are essential for service robots with manipulators to achieve various human-like tasks. Binocular vision is employed to interact with the environment in which the service robot works. This paper presents an approach for binocular based humanoid manipulation in a service robot system. An inverse kinematic solver is proposed to find all joint angles for a given position of the effectors on the manipulator. The target object is recognized according to segmented colors, and the 3D position computed using the stereo vision system. Having obtained the target position, the manipulator performs a blind grasp. Experimental results show effectiveness of the proposed methods.
出处 《上海大学学报(自然科学版)》 CAS CSCD 北大核心 2012年第5期506-512,共7页 Journal of Shanghai University:Natural Science Edition
关键词 仿人机械臂 逆运动学 双目视觉 HSV 服务机器人 humanoid manipulator inverse kinematics binocular vision hue-saturation-value (HSV) service robot
  • 相关文献

参考文献11

  • 1SAKAGAMI Y, WATANABE R, AOYAMA C, et al. The intelligent ASIMO: System overview and integration [ C ]//Proceeding of the 2002 IEEE/RSJ International Conference on Intecligent Robots and Systems. Saitama: Honda R&D Co. Ltd., 2002:2478-2483.
  • 2HARA I, ASANO F, ASOH H, et al. Robust speech interface based on audio and video information fusion for humanoid HRP-2 [ J ]. Intelligent Robots and Systems, 2004 : 2404-2410.
  • 3KAWAMURA K, PETERS II R A, WILKES D M, et al. ISAC : Foundations in human-humanoid interaction [ J ]. IEEE Intelligent System, 2000,15 ( 4 ) :38-45.
  • 4PRATS M, SANZ P J, DEL POBIL A P. Model-based tracking and hybrid force/vision control for the UJI librarian robot [ C ] ff Intelligent Robots and Systems, IEEE/RSJ International Conference on Digital ObjectIdentifier. 2005.
  • 5KEMP C C, EDSINGER A, TORRES-JARA E. Challenges for robot manipulation in human environments : Developing robots that perform useful work in everyday settings [ J ]. IEEE Robotics and Automation Society, 2007 : 20-29.
  • 6ASHUTOSH S, JUSTIN D, JUSTIN K, et al. Robotic grasping of novel objects using vision [ J ]. International Journal of Robotics Research, 2008 : 157-173.
  • 7HILLENBRAND U, BRUNNER B, BORST C, et al. The robutler: A vision-controlled hand-arm system for manipulating bottles and glasses [ C ] //ISR 2004 35th International Symposium on Robotics, Paris-Nord Villepinte Exhibition Centre. 2004.
  • 8NIKU S B. Introduction to robotics analysis, systems, applications [ M ]. Beijing: Publishing House of Electronics Industry, 2004:28-85.
  • 9JAN P. Vision based mobile manipulation [D]. Regensburg: Regensburg University of Applied Sciences, 2008.
  • 10LEE H J, LEE M C. Technique for localization and visual servoing of mobile manipulators [ J ]. IEEE International Symposium on Industrial Electronics, 2009.

同被引文献66

  • 1吴剑波,李明鸣,赵宏,谭玉山.立体视觉三维测量系统中的数据获取技术[J].仪器仪表学报,2001,22(z1):216-217. 被引量:5
  • 2王浩,马振书,穆希辉,夏辉,兰箭.危险品弹药遥操作搬运机器人的研究与开发[J].科学技术与工程,2007,7(3):393-395. 被引量:5
  • 3谢伟东,王磊,佘翊妮,游红武.条烟自动分拣的异步法及其装置[J].工程设计学报,2007,14(2):112-116. 被引量:7
  • 4于仕琪,刘瑞祯.学习OpenCV[M].北京:清华大学出版社,2009.
  • 5BAY H,ESS A,TUYTELAARS T.SURF:Speeded Up Robust Features[J].Computer Vision and Image Understanding(CVIU),2008,110(3):346-359.
  • 6DARID G.Lowe,Distinctive Image Features from Scale-invariant Keypoints[J].International Journal of Computer Vision,2004,60(2):91-110.
  • 7Sakagami Y, Watanabe R, Aoyama C, et al. The intelligent ASIMO: system overview andintegration [C]// Proceeding of the 2002 IEEE/RSJ International Conference on IntelligentRobots and Systems. 2002; 2478-2483.
  • 8Stuckler J, Steffens R, Holz D, et al. Efficient 3D object perception and grasp planningfor mobile manipulation in domestic environments [J]. Robotics & Autonomous Systems, 2012,61(10): 1106-1115.
  • 9Huang Z Y, Huang J T, Hsu C M. A case study of object identification using a Kinectsensor [C]// 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC).2013: 1743-1747.
  • 10Parker M, Daniel H C, Echtler F, et al. Hacking the Kinect [M]. New York: Apress, 2012:10-25.

引证文献10

二级引证文献45

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