Rolling Horizon Coverage Control with Collaborative Autonomous Agents

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).

@article{papaioannou2025_2504.05883,
  title={ Rolling Horizon Coverage Control with Collaborative Autonomous Agents },
  author={ Savvas Papaioannou and Panayiotis Kolios and Theocharis Theocharides and Christos G. Panayiotou and Marios M. Polycarpou },
  journal={arXiv preprint arXiv:2504.05883},
  year={ 2025 }
}