The efficiency of path-planning in robot navigation is crucial in tasks such as search-and-rescue and disaster surveying, but this is emphasized even more when considering multi-rotor aerial robots due to the limited battery and flight time. Reasoning over priors extracted from the environment enables more intelligent planning than exhaustive search, as tasks can be localized and addressed appropriately.
In this spirit, the work in [1] proposes an efficient, hierarchical planner to achieve comprehensive visual coverage of large-scale outdoor scenarios for small drones. Following an initial reconnaissance flight, a coarse map of the scene gets built in real-time. Then, regions of the map that were not appropriately observed are identified and grouped by a novel perception-aware clustering process that enables the generation of continuous trajectories ( sweeps ) to cover them efficiently. Thanks to this partitioning of the map into a set of tasks, we can generalize the planning to an arbitrary number of drones and perform a well-balanced workload distribution among them.
References
[1] D. Morilla-Cabello, L. Bartolomei, L. Teixeira, E. Montijano and M. Chli, "Sweep-Your-Map: Efficient Coverage Planning for Aerial Teams in Large-Scale Environments," in IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 10810-10817, Oct. 2022. Available online at: https://ieeexplore.ieee.org/document/9844235