Justin Cano, Corentin Chauffaut, Eric Chaumette, Gaël Pagès and Jérôme Le Ny
Paper (2022)
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| Department: | Department of Electrical Engineering |
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| Research Center: | GERAD - Research Group in Decision Analysis |
| PolyPublie URL: | https://publications.polymtl.ca/52440/ |
| Conference Title: | IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022) |
| Conference Location: | Kyoto, Japan |
| Conference Date(s): | 2022-10-23 - 2022-10-27 |
| Publisher: | IEEE |
| DOI: | 10.1109/iros47612.2022.9981427 |
| Official URL: | https://doi.org/10.1109/iros47612.2022.9981427 |
| Date Deposited: | 18 Apr 2023 14:58 |
| Last Modified: | 05 Apr 2024 11:57 |
| Cite in APA 7: | Cano, J., Chauffaut, C., Chaumette, E., Pagès, G., & Le Ny, J. (2022, October). Maintaining Robot Localizability with Bayesian Cramer-Rao Lower Bounds [Paper]. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022), Kyoto, Japan. https://doi.org/10.1109/iros47612.2022.9981427 |
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