A Two-View based Multilayer Feature Graph for Robot Navigation Conference Paper uri icon

abstract

  • To facilitate scene understanding and robot navigation in a 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 demonstrated to be very robust in identifying feature correspondence. 2012 IEEE.

name of conference

  • 2012 IEEE International Conference on Robotics and Automation

published proceedings

  • 2012 IEEE International Conference on Robotics and Automation

altmetric score

  • 3

author list (cited authors)

  • Li, H., Song, D., Lu, Y., & Liu, J.

citation count

  • 13

complete list of authors

  • Li, Haifeng||Song, Dezhen||Lu, Yan||Liu, Jingtai

publication date

  • May 2012