Localization for Mobile Robots using Panoramic Vision, Local Features and Particle Filter
- 18 April 2005
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 3348-3353
- https://doi.org/10.1109/robot.2005.1570627
Abstract
In this paper we present a vision-based approach to self-localization that uses a novel scheme to integrate feature-based matching of panoramic images with Monte Carlo localization. A specially modified version of Lowe’s SIFT algorithm is used to match features extracted from local interest points in the image, rather than using global features calculated from the whole image. Experiments conducted in a large, populated indoor environment (up to 5 persons visible) over a period of several months demonstrate the robustness of the approach, including kidnapping and occlusion of up to 90% of the robot’s field of viewKeywords
This publication has 11 references indexed in Scilit:
- Omnivision-based probabilistic self-localization for a mobile shopping assistant continuedPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- Topological mobile robot localization using fast vision techniquesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Mobile robot localization using an incremental eigenspace modelPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Rover localization in natural environments by indexing panoramic imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Robust vision-based localization for mobile robots using an image retrieval system based on invariant featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Auxiliary particle filter robot localization from high-dimensional sensor observationsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Appearance-based place recognition for topological localizationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual LandmarksThe International Journal of Robotics Research, 2002
- Object recognition from local scale-invariant featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1999
- Active Markov localization for mobile robotsRobotics and Autonomous Systems, 1998