ICRA 2012 Paper Abstract

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Paper WeD110.4

Li, Haifeng (Nankai University), Song, Dezhen (Texas A&M University), Lu, Yan (Texas A&M University), Liu, Jingtai (Nankai University)

A Two-View Based Multilayer Feature Graph for Robot Navigation

Scheduled for presentation during the Interactive Session "Interactive Session WeD-1" (WeD110), Wednesday, May 16, 2012, 16:30−17:00, Ballroom D

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 18, 2017

Keywords Visual Navigation

Abstract

To facilitate scene understanding and robot navigation in modern urban area, we design a multilayer feature graph (MFG) based on two views from an on-board camera. The nodes of an MFG are features such as scale invariant feature transformation (SIFT) feature points, line segments, lines, and planes while edges of the MFG represent different geometric relationships such as adjacency, parallelism, collinearity, and coplanarity. MFG also connects the features in two views and the corresponding 3D coordinate system. Building on SIFT feature points and line segments, MFG is constructed using feature fusion which incrementally, iteratively, and extensively verifies the aforementioned geometric relationships using random sample consensus (RANSAC) framework. Physical experiments show that MFG can be successfully constructed in urban area and the construction method is proved to be very robust in identifying feature correspondence.

 

 

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