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Dynamic Maps for Long-Term Operation of Mobile Service Robots
Open accessAbstract
This paper introduces a dynamic map for mobile robots that adapts continuously over time. It resolves the stabilityplasticity dilemma (the trade-off between adaptation to new patterns and preservation of old patterns) by representing the environment over multiple timescales simultaneously (5 in our experiments). A sample-based representation is proposed, where older memories fade at different rates depending on the timescale.Robust statistics are used to interpret the samples.It is shown that this approach can track both stationary and non-stationary elements of the environment, covering the full spectrum of variations from moving objects to structural changes.The method was evaluated in a five week experiment in a real dynamic environment.Experimental results show that the resulting map is stable, improves its quality over time and adapts to changes.
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Cites
Globally Consistent Range Scan Alignment for Environment Mapping
Lu, F., & Milios, E. (1997) · Autonomous Robots · doi:10.1023/a:1008854305733 · Cited by 1,304
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Paull, L., Saeedi, S., Seto, M., & Li, H. (2014) · IEEE Journal of Oceanic Engineering · doi:10.1109/joe.2013.2278891 · Cited by 1,536
iSAM2: Incremental smoothing and mapping using the Bayes tree
Kaess, M., Johannsson, H., Roberts, R., Ila, V., Leonard, J. J., & Dellaert, F. (2012) · The International Journal of Robotics Research · doi:10.1177/0278364911430419 · Cited by 1,362
A Tutorial on Graph-Based SLAM
Grisetti, G., Kummerle, R., Stachniss, C., & Burgard, W. (2010) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2010.939925 · Cited by 1,345
Visual Place Recognition: A Survey
Lowry, S., Sünderhauf, N., Newman, P., Leonard, J. J., Cox, D., Corke, P., & Milford, M. J. (2016) · IEEE Transactions on Robotics · doi:10.1109/tro.2015.2496823 · Cited by 1,079
iSAM: Incremental Smoothing and Mapping
Kaess, M., Ranganathan, A., & Dellaert, F. (2008) · IEEE Transactions on Robotics · doi:10.1109/tro.2008.2006706 · Cited by 1,076
Metadata
- Authors
- Biber, P., & Duckett, T.
- Venue
- Robotics: Science and Systems I
- Published
- 2005-06-08
- Volume
- 01
- Pages
- 17-24
- OpenAlex
- W3143919370
- Cited by
- 334
- References
- 1
- FWCI
- 47.28
- Type
- conference paper
- Language
- en
- Open access
- gold
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- Biber, P., & Duckett, T. (2005). Dynamic Maps for Long-Term Operation of Mobile Service Robots. Robotics: Science and Systems I. https://doi.org/10.15607/rss.2005.i.003
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
