Tactile analysis and modeling of dextrous robotic hand

被引:0
作者
State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China [1 ]
机构
[1] State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University
来源
Jiqiren | 2013年 / 4卷 / 394-401期
关键词
Bag of model; Dextrous robotic hand; Fine operation; Linear dynamic system; Tactile;
D O I
10.3724/SP.J.1218.2013.00394
中图分类号
学科分类号
摘要
In order to achieve fine operation of dextrous robotic hand, the features of tactile data time-series of dextrous hand are analyzed, and a bag of models based on piecewise linear dynamic systems is proposed. Furthermore, corresponding relation between tactile data time-series and family of models describing different types of objects is established in lowdimensional feature space via solving parametric matrixes of dynamic system models. Some experiments are conducted on a dextrous hand with tactile array sensor, and the results show that the proposed method can give not only a precise description of the dynamic process corresponding to a same type of objects, but also a comprehensive description corresponding to different types of objects, which will lay the foundation for multi-modal information fusion in feature space.
引用
收藏
页码:394 / 401
页数:7
相关论文
共 13 条
[1]  
Siciliano B., Khatib O., Springer Handbook of Robotics, (2008)
[2]  
Liu S.Q., Huang W.Y., Wang A.M., Et al., Overview and prospect of research and development on robot tactile sensory technology, Robot, 24, 4, (2002)
[3]  
Bekiroglu Y., Huebner K., Kragic D., Integrating grasp planning with online stability assessment using tactile sensing, IEEE International Conference on Robotics and Automation, pp. 4750-4755, (2011)
[4]  
Xi X.G., Luo Z.Z., A tele-manipulator with tactile tele-presence and myoelectric bionic control, Robot, 31, 3, pp. 270-275, (2009)
[5]  
Bekiroglu Y., Laaksonen J., Jorgensen J.A., Et al., Assessing grasp stability based on learning and haptic data, IEEE Transactions on Robotics, 27, 3, pp. 616-629, (2011)
[6]  
Steffen J., Haschke R., Ritter H., Experience-based and tactiledriven dynamic grasp control, IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2938-2943, (2007)
[7]  
Bekiroglu Y., Detry R., Kragic D., Learning tactile characterizations of object- and pose-specific grasps, IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1554-1560, (2011)
[8]  
Schneider A., Sturm J., Stachniss C., Et al., Object identification with tactile sensors using bag-of-features, IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 243-248, (2009)
[9]  
Gorges N., Navarro S.E., Goger D., Et al., Haptic object recognition using passive joints and haptic key features, IEEE International Conference on Robotics and Automation, pp. 2349-2355, (2010)
[10]  
Del P.A.P., Prats M., Sanz P.J., Interaction in robotics with a combination of vision, tactile and force sensing, Fifth International Conference on Sensing Technology, pp. 21-26, (2011)