Rolling Horizon Coverage Control with Collaborative Autonomous Agents
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866915233445969920 |
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| author | Papaioannou, Savvas Kolios, Panayiotis Theocharides, Theocharis Panayiotou, Christos G. Polycarpou, Marios M. |
| author_facet | Papaioannou, Savvas Kolios, Panayiotis Theocharides, Theocharis Panayiotou, Christos G. Polycarpou, Marios M. |
| contents | This work proposes a coverage controller that enables an aerial team of distributed autonomous agents to collaboratively generate non-myopic coverage plans over a rolling finite horizon, aiming to cover specific points on the surface area of a 3D object of interest. The collaborative coverage problem, formulated, as a distributed model predictive control problem, optimizes the agents' motion and camera control inputs, while considering inter-agent constraints aiming at reducing work redundancy. The proposed coverage controller integrates constraints based on light-path propagation techniques to predict the parts of the object's surface that are visible with regard to the agents' future anticipated states. This work also demonstrates how complex, non-linear visibility assessment constraints can be converted into logical expressions that are embedded as binary constraints into a mixed-integer optimization framework. The proposed approach has been demonstrated through simulations and practical applications for inspecting buildings with unmanned aerial vehicles (UAVs). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_05883 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Rolling Horizon Coverage Control with Collaborative Autonomous Agents Papaioannou, Savvas Kolios, Panayiotis Theocharides, Theocharis Panayiotou, Christos G. Polycarpou, Marios M. Robotics This work proposes a coverage controller that enables an aerial team of distributed autonomous agents to collaboratively generate non-myopic coverage plans over a rolling finite horizon, aiming to cover specific points on the surface area of a 3D object of interest. The collaborative coverage problem, formulated, as a distributed model predictive control problem, optimizes the agents' motion and camera control inputs, while considering inter-agent constraints aiming at reducing work redundancy. The proposed coverage controller integrates constraints based on light-path propagation techniques to predict the parts of the object's surface that are visible with regard to the agents' future anticipated states. This work also demonstrates how complex, non-linear visibility assessment constraints can be converted into logical expressions that are embedded as binary constraints into a mixed-integer optimization framework. The proposed approach has been demonstrated through simulations and practical applications for inspecting buildings with unmanned aerial vehicles (UAVs). |
| title | Rolling Horizon Coverage Control with Collaborative Autonomous Agents |
| topic | Robotics |
| url | https://arxiv.org/abs/2504.05883 |