Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks
University of British Columbia
Abstract
A key component of a mobile robot system is the ability to localize itself accurately and, simultaneously, to build a map of the environment. Most of the existing algorithms are based on laser range finders, sonar sensors or artificial landmarks. In this paper, we describe a vision-based mobile robot localization and mapping algorithm, which uses scale-invariant image features as natural landmarks in unmodified environments. The invariance of these features to image translation, scaling and rotation makes them suitable landmarks for mobile robot localization and map building. With our Triclops stereo vision system, these landmarks are localized and robot ego-motion is estimated by least-squares minimization of…
Citation impact
- FWCI
- 537.40
- Percentile
- 100%
- References
- 38
Authors
3Topics & keywords
- Landmark
- Computer vision
- Artificial intelligence
- Mobile robot
- Computer science
- Scale-invariant feature transform
- Robot
- Invariant (physics)
- Sustainable cities and communities