Object Mapping, Recognition, and Localization from Tactile Geometry
We present a method for performing object recognition using multiple images acquired from a tactile sensor. The method relies on using the tactile sensor as an imaging device, and builds an object representation based on mosaics of tactile measurements. We then describe an algorithm that is able to recognize an object using a small number of tactile sensor readings. Our approach makes extensive use of sequential state estimation techniques from the mobile robotics literature, whereby we view the object recognition problem as one of estimating a consistent location within a set of object maps. We examine and test approaches based on both traditional particle filtering and histogram filtering. We demonstrate both the mapping and recognition / localization techniques on a set of raised letter shapes using real tactile sensor data.
Zachary Pezzementi Caitlin Reyda Gregory D. Hager
Dept. of Computer Science,Johns Hopkins University,Baltimore,MD 21218,USA Department of Mechanical Engineering,Massachussetts Institute of Technology,Cambridge,MA 02139,USA
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
5942-5948
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）