Optimal Robot Formations: Balancing Range-Based Observability and User-Defined Configurations
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866913786788577280 |
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| author | Ahmed, Syed Shabbir Shalaby, Mohammed Ayman Ny, Jerome Le Forbes, James Richard |
| author_facet | Ahmed, Syed Shabbir Shalaby, Mohammed Ayman Ny, Jerome Le Forbes, James Richard |
| contents | This paper introduces a set of customizable and novel cost functions that enable the user to easily specify desirable robot formations, such as a ``high-coverage'' infrastructure-inspection formation, while maintaining high relative pose estimation accuracy. The overall cost function balances the need for the robots to be close together for good ranging-based relative localization accuracy and the need for the robots to achieve specific tasks, such as minimizing the time taken to inspect a given area. The formations found by minimizing the aggregated cost function are evaluated in a coverage path planning task in simulation and experiment, where the robots localize themselves and unknown landmarks using a simultaneous localization and mapping algorithm based on the extended Kalman filter. Compared to an optimal formation that maximizes ranging-based relative localization accuracy, these formations significantly reduce the time to cover a given area with minimal impact on relative pose estimation accuracy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_00988 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimal Robot Formations: Balancing Range-Based Observability and User-Defined Configurations Ahmed, Syed Shabbir Shalaby, Mohammed Ayman Ny, Jerome Le Forbes, James Richard Robotics This paper introduces a set of customizable and novel cost functions that enable the user to easily specify desirable robot formations, such as a ``high-coverage'' infrastructure-inspection formation, while maintaining high relative pose estimation accuracy. The overall cost function balances the need for the robots to be close together for good ranging-based relative localization accuracy and the need for the robots to achieve specific tasks, such as minimizing the time taken to inspect a given area. The formations found by minimizing the aggregated cost function are evaluated in a coverage path planning task in simulation and experiment, where the robots localize themselves and unknown landmarks using a simultaneous localization and mapping algorithm based on the extended Kalman filter. Compared to an optimal formation that maximizes ranging-based relative localization accuracy, these formations significantly reduce the time to cover a given area with minimal impact on relative pose estimation accuracy. |
| title | Optimal Robot Formations: Balancing Range-Based Observability and User-Defined Configurations |
| topic | Robotics |
| url | https://arxiv.org/abs/2403.00988 |