ICRA 2011 Paper Abstract


Paper TuP204.6

Truax, Robert (MIT), Platt, Robert (MIT), Leonard, John (MIT)

Using Prioritized Relaxations to Locate Objects in Points Clouds for Manipulation

Scheduled for presentation during the Regular Sessions "Recognition I" (TuP204), Tuesday, May 10, 2011, 16:40−16:55, Room 3E

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 March 30, 2020

Keywords Recognition, Range Sensing


This paper considers the problem of identifying objects of interest in laser range point clouds for the purposes of manipulation. One of the characteristics of perception for manipulation is that while it is unnecessary to label all objects in the scene, it may be very important to maximize the likelihood of correctly locating a desired object. This paper leverages this and proposes an approach for locating the most likely object configurations given an object parameterization and a point cloud. While many other approaches to object localization need to explicitly associate points with hypothesized objects, our proposed method avoids this by optimizing relaxations of the likelihood function rather than the exact likelihood. The result is a simple, efficient, and robust method for locating objects that makes few assumptions beyond the desired object parameterization and with few parameters that require tuning.



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