Robust outdoor visual localization using a three-dimensional-edge map


Autoria(s): Nuske, Stephen; Roberts, Jonathan M.; Wyeth, Gordon
Data(s)

2009

Resumo

Visual localization systems that are practical for autonomous vehicles in outdoor industrial applications must perform reliably in a wide range of conditions. Changing outdoor conditions cause difficulty by drastically altering the information available in the camera images. To confront the problem, we have developed a visual localization system that uses a surveyed three-dimensional (3D)-edge map of permanent structures in the environment. The map has the invariant properties necessary to achieve long-term robust operation. Previous 3D-edge map localization systems usually maintain a single pose hypothesis, making it difficult to initialize without an accurate prior pose estimate and also making them susceptible to misalignment with unmapped edges detected in the camera image. A multihypothesis particle filter is employed here to perform the initialization procedure with significant uncertainty in the vehicle's initial pose. A novel observation function for the particle filter is developed and evaluated against two existing functions. The new function is shown to further improve the abilities of the particle filter to converge given a very coarse estimate of the vehicle's initial pose. An intelligent exposure control algorithm is also developed that improves the quality of the pertinent information in the image. Results gathered over an entire sunny day and also during rainy weather illustrate that the localization system can operate in a wide range of outdoor conditions. The conclusion is that an invariant map, a robust multihypothesis localization algorithm, and an intelligent exposure control algorithm all combine to enable reliable visual localization through challenging outdoor conditions.

Identificador

http://eprints.qut.edu.au/32810/

Publicador

John Wiley & Sons

Relação

DOI:10.1002/rob.20306

Nuske, Stephen, Roberts, Jonathan M., & Wyeth, Gordon (2009) Robust outdoor visual localization using a three-dimensional-edge map. Journal of Field Robotics, 26(9), pp. 728-756.

Fonte

School of Electrical Engineering & Computer Science; Institute for Future Environments; Science & Engineering Faculty

Palavras-Chave #080101 Adaptive Agents and Intelligent Robotics #Robots #Computer Vision
Tipo

Journal Article