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Paper TuD09.4

Choi, Changhyun (Georgia Institute of Technology), Taguchi, Yuichi (Mitsubishi Electric Research Laboratories), Tuzel, Oncel (MERL), Liu, Ming-Yu (University of Maryland College Park), Ramalingam, Srikumar (Mitsubishi Electric Research Lab)

Voting-Based Pose Estimation for Robotic Assembly Using a 3D Sensor

Scheduled for presentation during the Regular Session "Sensing for manipulation" (TuD09), Tuesday, May 15, 2012, 17:15−17:30, Meeting Room 9 (Sa)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on November 14, 2018

Keywords Range Sensing, Industrial Robots, Grasping

Abstract

We propose a voting-based pose estimation algorithm applicable to 3D sensors, which are fast replacing their 2D counterparts in many robotics, computer vision, and gaming applications. It was recently shown that a pair of oriented 3D points, which are points on the object surface with normals, in a voting framework enables fast and robust pose estimation. Although oriented surface points are discriminative for objects with sufficient curvature changes, they are not compact and discriminative enough for many industrial and real-world objects that are mostly planar. As edges play the key role in 2D registration, depth discontinuities are crucial in 3D. In this paper, we investigate and develop a family of pose estimation algorithms that better exploit this boundary information. In addition to oriented surface points, we use two other primitives: boundary points with directions and boundary line segments. Our experiments show that these carefully chosen primitives encode more information compactly and thereby provide higher accuracy for a wide class of industrial parts and enable faster computation. We demonstrate a practical robotic bin-picking system using the proposed algorithm and a 3D sensor.

 

 

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