Omnidirectional visual odometry for a planetary rover
Open accessAbstract
Position estimation for planetary rovers has been typically limited to odometry based on proprioceptive measurements such as the integration of distance traveled and measurement of heading change. Here we present and compare two methods of online visual odometry suited for planetary rovers. Both methods use omnidirectional imagery to estimate motion of the rover. One method is based on robust estimation of optical flow and subsequent integration of the flow. The second method is a full structure-from-motion solution. To make the comparison meaningful we use the same set of raw corresponding visual features for each method. The dataset is an sequence of 2000 images taken during a field experiment in the Atacama desert, for which high resolution GPS ground truth is available.
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Scaramuzza, D., & Fraundorfer, F. (2011) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2011.943233 · Cited by 1,550 · see citing works
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Maimone, M., Cheng, Y., & Matthies, L. (2007) · Journal of Field Robotics · doi:10.1002/rob.20184 · Cited by 655 · see citing works
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Pillai, S., & Leonard, J. J. (2017) · 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2017.8206441 · Cited by 42 · see citing works
- Authors
- Corke, P., Strelow, D., & Singh, S.
- Affiliations
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Carnegie Mellon University (US)
- Venue
- 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566)
- Publisher
- IEEE
- Published
- 2005-04-12
- Volume
- 4
- Pages
- 4007-4012
- ISSN
- 2153-0858 (ISSN-L)
- OpenAlex
- W1559224780
- Cited by
- 162
- References
- 0
- Citations by year
- 2024: 2 · 2023: 2 · 2022: 5 · 2021: 5 · 2020: 5 · 2019: 8 · 2018: 7 · 2017: 7 · 2016: 9 · 2015: 7 · 2014: 8 · 2013: 11 · 2012: 11
- FWCI
- 27.40
- Type
- conference paper
- Language
- en
- Open access
- green
- figshare.com
- Licence
- cc-by
- Locations
- IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (publishedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- KiltHub Repository (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Faculty of Built Environment and Engineering
- KiltHub Repository
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
- Keywords
- visual odometry, planetary rovers, optical flow, structure from motion, positioning, feature matching, GPS ground truth
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