ICRA 2011 Paper Abstract

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Paper ThP205.3

Shroff, Nitesh (University of Maryland, College Park), Taguchi, Yuichi (Mitsubishi Electric Research Laboratories), Tuzel, Oncel (MERL), Veeraraghavan, Ashok (Mitsubishi Electric Research Labs), Ramalingam, Srikumar (Mitsubishi Electric Research Lab), Okuda, Haruhisa (Mitsubishi Electric Corporation)

Finding a Needle in a Specular Haystack

Scheduled for presentation during the Regular Sessions "Vision for Object Recognition" (ThP205), Thursday, May 12, 2011, 15:55−16:10, Room 3G

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on May 22, 2019

Keywords Computer Vision for Robotics and Automation

Abstract

Progress in machine vision algorithms has led to widespread adoption of these techniques to automate several industrial assembly tasks. Nevertheless, shiny or specular objects which are common in industrial environments still present a great challenge for vision systems. In this paper, we take a step towards this problem under the context of vision-aided robotic assembly. We show that when the illumination source moves, the specular highlights remain in a region whose radius is inversely proportional to the surface curvature. This allows us to extract regions of the object that have high surface curvature. These points of high curvature can be used as features for specular objects. Further, an inexpensive multi-flash camera (MFC) design can be used to reliably extract these features. We show that one can use multiple views of the object using the MFC in order to triangulate and obtain the 3D location and pose of the shiny objects. Finally, we show a system consisting of a robot arm with an MFC that can perform automated detection and pose estimation of shiny screws within a cluttered bin, achieving position and orientation errors less than 0.5 mm and 0.8 degrees respectively.

 

 

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