Energy-aware Coverage Path Planning for Unmanned Aerial Vehicles
Resumo
Coverage Path Planning (CPP) problem is a motion planning subtopic in robotics, where it is necessary to build a path for a robot to explore every location in a given scenario. Unmanned Aerial Vehicles (UAV) have been employed in several applications related to the CPP problem. However, one of the significant limitations of UAVs is endurance, especially in multi-rotors. Minimizing energy consumption is pivotal to prolong and guarantee coverage. Thus, this work proposes energy-aware coverage path planning solutions for regular and irregular-shaped areas containing full and partial information. We consider aspects such as distance, time, turning maneuvers, and optimal speed in the UAV’s energy consumption. We propose an energy-aware spiral algorithm called E-Spiral to perform missions over regular-shaped areas. Next, we explore an energy-aware grid-based solution called EG-CPP for mapping missions over irregular-shaped areas containing no-fly zones. Finally, we present an energy-aware pheromone-based solution for patrolling missions called NC-Drone. The three novel approaches successfully address different coverage path planning scenarios, advancing the state-of-the-art in this area.
Palavras-chave:
Coverage Path Planning, Energy-aware, UAV
Referências
Acevedo, J.J., Arrue, B.C., Maza, I., Ollero, A.: Cooperative large area surveillance with a team of aerial mobile robots for long endurance missions. Journal of Intelligent & Robotic Systems 70(1-4), 329–345 (2013).
Adams, D.: Best drone 2019: the top drones for stunning 4k video, pin-sharp photos and aerial selfies. Available online: https://www.t3.com/features/best-drone (2019), (accessed on 19 June 2019).
Andersen, H.L.: Path Planning for Search and Rescue Mission using Multicopters. Master’s thesis, Norway (2014).
Araujo, J., Sujit, P., Sousa, J.B.: Multiple uav area decomposition and coverage. In: 2013 IEEE symposium on computational intelligence for security and defense applications (CISDA). pp. 30–37. IEEE, IEEE, Singapore (2013).
Artemenko, O., Dominic, O.J., Andryeyev, O., Mitschele-Thiel, A.: Energy-aware trajectory planning for the localization of mobile devices using an unmanned aerial vehicle. In: 2016 25th International Conference on Computer Communication and Networks (ICCCN). pp. 1–9. IEEE, IEEE, Waikoloa, HI, USA (2016).
Balampanis, F., Maza, I., Ollero, A.: Coastal areas division and coverage with multiple UAVs for remote sensing. Sensors 17(4), 808 (2017).
Barrientos, A., Colorado, J., del Cerro, J., Martinez, A., Rossi, C., Sanz, D., Valente, J.: Aerial remote sensing in agriculture: A practical approach to area coverage and path planning for fleets of mini aerial robots. J. Field Robot. 28(5), 667–689 (9 2011).
Choset, H.: Coverage for robotics–a survey of recent results. Annals of mathematics and artificial intelligence 31(1-4), 113–126 (2001).
Coombes, M., Chen, W.H., Liu, C.: Boustrophedon coverage path planning for uav aerial surveys in wind. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS). pp. 1563–1571. IEEE, IEEE, Miami, FL, USA (2017).
Coombes, M., Fletcher, T., Chen, W.H., Liu, C.: Optimal polygon decomposition for uav survey coverage path planning in wind. Sensors 18(7), 2132 (2018).
Di Franco, C., Buttazzo, G.: Coverage path planning for uavs photogrammetry with energy and resolution constraints. Journal of Intelligent & Robotic Systems pp. 1–18 (2016).
Koenig, S., Liu, Y.: Terrain coverage with ant robots: A simulation study. In: Proceedings of the Fifth International Conference on Autonomous Agents. pp. 600–607. ACM, Montreal, Quebec, Canada (2001).
Li, D., Wang, X., Sun, T.: Energy-optimal coverage path planning on topographic map for environment survey with unmanned aerial vehicles. Electronics Letters 52(9), 699–701 (2016).
Li, Y., Chen, H., Er, M.J., Wang, X.: Coverage path planning for uavs based on enhanced exact cellular decomposition method. Mechatronics 21(5), 876 – 885 (2011), special Issue on Development of Autonomous Unmanned Aerial Vehicles.
Maza, I., Ollero, A.: Multiples uav cooperative searching operation using polygon area decomposition and efficient coverage algorithms. In: Distributed Autonomous Robotic Systems 6. pp. 221–230. Springer Japan (2007).
Nattero, C., Recchiuto, C., Sgorbissa, A., Wanderlingh, F.: Coverage algorithms for search and rescue with uav drones. In: Workshop of the XIII AIIA Symposium on Artificial Intelligence. Italian Association for Artificial Intelligence, Pisa, Italy (2014).
Paradzik, M., İnce, G.: Multi-agent search strategy based on digital pheromones for uavs. In: 2016 24th Signal Processing and Communication Application Conference (SIU). pp. 233–236. IEEE, IEEE, Zonguldak, Turkey (2016).
Rosalie, M., Danoy, G., Chaumette, S., Bouvry, P.: From random process to chaotic behavior in swarms of uavs. In: Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications. pp. 9–15. ACM, ACM, Malta, Malta (2016).
Sadat, S.A., Wawerla, J., Vaughan, R.: Fractal trajectories for online non-uniform aerial coverage. In: 2015 IEEE International Conference on Robotics and Automation (ICRA). pp. 2971–2976. IEEE, IEEE, Seattle, WA, USA (2015).
Santamaria, E., Segor, F., Tchouchenkov, I.: Rapid aerial mapping with multiple heterogeneous unmanned vehicles. In: Proc. of the 10th International Conference on Information Systems for Crisis Response and Management. Citeseer, ISCRAM, Baden-Baden, Germany (2013).
Torres, M., Pelta, D.A., Verdegay, J.L., Torres, J.C.: Coverage path planning with unmanned aerial vehicles for 3d terrain reconstruction. Expert Systems with Applications 55, 441 – 451 (2016).
Valente, J., Del Cerro, J., Barrientos, A., Sanz, D.: Aerial coverage optimization in precision agriculture management: A musical harmony inspired approach. Computers and electronics in agriculture 99, 153–159 (2013).
Valente, J., Sanz, D., Del Cerro, J., Barrientos, A., de Frutos, M.Á.: Near-optimal coverage trajectories for image mosaicing using a mini quad-rotor over irregularshaped fields. Precision Agriculture 14(1), 115–132 (2013).
Adams, D.: Best drone 2019: the top drones for stunning 4k video, pin-sharp photos and aerial selfies. Available online: https://www.t3.com/features/best-drone (2019), (accessed on 19 June 2019).
Andersen, H.L.: Path Planning for Search and Rescue Mission using Multicopters. Master’s thesis, Norway (2014).
Araujo, J., Sujit, P., Sousa, J.B.: Multiple uav area decomposition and coverage. In: 2013 IEEE symposium on computational intelligence for security and defense applications (CISDA). pp. 30–37. IEEE, IEEE, Singapore (2013).
Artemenko, O., Dominic, O.J., Andryeyev, O., Mitschele-Thiel, A.: Energy-aware trajectory planning for the localization of mobile devices using an unmanned aerial vehicle. In: 2016 25th International Conference on Computer Communication and Networks (ICCCN). pp. 1–9. IEEE, IEEE, Waikoloa, HI, USA (2016).
Balampanis, F., Maza, I., Ollero, A.: Coastal areas division and coverage with multiple UAVs for remote sensing. Sensors 17(4), 808 (2017).
Barrientos, A., Colorado, J., del Cerro, J., Martinez, A., Rossi, C., Sanz, D., Valente, J.: Aerial remote sensing in agriculture: A practical approach to area coverage and path planning for fleets of mini aerial robots. J. Field Robot. 28(5), 667–689 (9 2011).
Choset, H.: Coverage for robotics–a survey of recent results. Annals of mathematics and artificial intelligence 31(1-4), 113–126 (2001).
Coombes, M., Chen, W.H., Liu, C.: Boustrophedon coverage path planning for uav aerial surveys in wind. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS). pp. 1563–1571. IEEE, IEEE, Miami, FL, USA (2017).
Coombes, M., Fletcher, T., Chen, W.H., Liu, C.: Optimal polygon decomposition for uav survey coverage path planning in wind. Sensors 18(7), 2132 (2018).
Di Franco, C., Buttazzo, G.: Coverage path planning for uavs photogrammetry with energy and resolution constraints. Journal of Intelligent & Robotic Systems pp. 1–18 (2016).
Koenig, S., Liu, Y.: Terrain coverage with ant robots: A simulation study. In: Proceedings of the Fifth International Conference on Autonomous Agents. pp. 600–607. ACM, Montreal, Quebec, Canada (2001).
Li, D., Wang, X., Sun, T.: Energy-optimal coverage path planning on topographic map for environment survey with unmanned aerial vehicles. Electronics Letters 52(9), 699–701 (2016).
Li, Y., Chen, H., Er, M.J., Wang, X.: Coverage path planning for uavs based on enhanced exact cellular decomposition method. Mechatronics 21(5), 876 – 885 (2011), special Issue on Development of Autonomous Unmanned Aerial Vehicles.
Maza, I., Ollero, A.: Multiples uav cooperative searching operation using polygon area decomposition and efficient coverage algorithms. In: Distributed Autonomous Robotic Systems 6. pp. 221–230. Springer Japan (2007).
Nattero, C., Recchiuto, C., Sgorbissa, A., Wanderlingh, F.: Coverage algorithms for search and rescue with uav drones. In: Workshop of the XIII AIIA Symposium on Artificial Intelligence. Italian Association for Artificial Intelligence, Pisa, Italy (2014).
Paradzik, M., İnce, G.: Multi-agent search strategy based on digital pheromones for uavs. In: 2016 24th Signal Processing and Communication Application Conference (SIU). pp. 233–236. IEEE, IEEE, Zonguldak, Turkey (2016).
Rosalie, M., Danoy, G., Chaumette, S., Bouvry, P.: From random process to chaotic behavior in swarms of uavs. In: Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications. pp. 9–15. ACM, ACM, Malta, Malta (2016).
Sadat, S.A., Wawerla, J., Vaughan, R.: Fractal trajectories for online non-uniform aerial coverage. In: 2015 IEEE International Conference on Robotics and Automation (ICRA). pp. 2971–2976. IEEE, IEEE, Seattle, WA, USA (2015).
Santamaria, E., Segor, F., Tchouchenkov, I.: Rapid aerial mapping with multiple heterogeneous unmanned vehicles. In: Proc. of the 10th International Conference on Information Systems for Crisis Response and Management. Citeseer, ISCRAM, Baden-Baden, Germany (2013).
Torres, M., Pelta, D.A., Verdegay, J.L., Torres, J.C.: Coverage path planning with unmanned aerial vehicles for 3d terrain reconstruction. Expert Systems with Applications 55, 441 – 451 (2016).
Valente, J., Del Cerro, J., Barrientos, A., Sanz, D.: Aerial coverage optimization in precision agriculture management: A musical harmony inspired approach. Computers and electronics in agriculture 99, 153–159 (2013).
Valente, J., Sanz, D., Del Cerro, J., Barrientos, A., de Frutos, M.Á.: Near-optimal coverage trajectories for image mosaicing using a mini quad-rotor over irregularshaped fields. Precision Agriculture 14(1), 115–132 (2013).
Publicado
11/11/2020
Como Citar
CABREIRA, Tauã Milech; BRISOLARA, Lisane B.; FERREIRA JR., Paulo R..
Energy-aware Coverage Path Planning for Unmanned Aerial Vehicles. In: CONCURSO DE TESES E DISSERTAÇÕES EM ROBÓTICA - CTDR (DOUTORADO) - SIMPÓSIO BRASILEIRO DE ROBÓTICA E SIMPÓSIO LATINO-AMERICANO DE ROBÓTICA (SBR/LARS), 8. , 2020, Natal.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 109-120.
DOI: https://doi.org/10.5753/wtdr_ctdr.2020.14959.
