Abstract
Natural and human-made disasters require effective victim assistance and last-mile relief supply operations with teams of ground vehicles. In these applications, digital elevation models (DEM) can provide accurate knowledge for safe vehicle motion planning but grid representation results in very large search graphs. Furthermore, travel time, which becomes a crucial cost optimization criterion, may be affected by inclination and other challenging terrain characteristics. In this paper, our goal is to evaluate a search heuristic function based on anisotropic vehicle velocity restrictions for building the cost matrix required for multi-vehicle routing on natural terrain and disaster sites. The heuristic is applied to compute the fastest travel times between every pair of matrix elements by means of a path planning algorithm. The analysis is based on a case study on the ortophotographic DEM of natural terrain with different target points, where the proposed heuristic is compared against an exhaustive search solution.
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References
Bae, J., Chung, W.: Heuristics for two depot heterogeneous unmanned vehicle path planning to minimize maximum travel cost. Sensors 19(11) (2019). https://doi.org/10.3390/s19112461
Bruni, M.E., Beraldi, P., Khodaparasti, S.: A fast heuristic for routing in post-disaster humanitarian relief logistics. Transp. Res. Procedia 30, 304–313 (2018). https://doi.org/10.1016/j.trpro.2018.09.033
Choi, Y., Chen, M., Choi, Y., Briceno, S., Mavris, D.: Multi-UAV trajectory optimization utilizing a NURBS-based terrain model for an aerial imaging mission. J. Intell. Robot. Syst.: Theory Appl. (2019). https://doi.org/10.1007/s10846-019-01027-9
Conesa-Muñoz, J., Pajares, G., Ribeiro, A.: Mix-opt: a new route operator for optimal coverage path planning for a fleet in an agricultural environment. Expert Syst. Appl. 54, 364–378 (2016). https://doi.org/10.1016/j.eswa.2015.12.047
Faied, M., Mostafa, A., Girard, A.: Vehicle routing problem instances: application to multi-UAV mission planning. In: AIAA Guidance, Navigation, and Control Conference (2010). https://doi.org/10.2514/6.2010-8435
Fernández-Lozano, J.J., Mandow, A., Martín-Guzman, M., Martín-Avila, J., Serón, J., Martínez, J.L., Gomez-Ruiz, J.A., Socarrás-Bertiz, C., Miranda-Paez, J., García-Cerezo, A.: Integration of a canine agent in a wireless sensor network for information gathering in search and rescue missions. In: IEEE International Conference on Intelligent Robots and Systems, pp. 5685–5690 (2018). https://doi.org/10.1109/IROS.2018.8593849
Garrido, S., Moreno, L., Martín, F., Álvarez, D.: Fast marching subjected to a vector field-path planning method for Mars rovers. Expert Syst. Appl. 78, 334–346 (2017). https://doi.org/10.1016/j.eswa.2017.02.019
Műhlbacher, C., Gspandl, S., Reip, M., Steinbauer, G.: Adapting edge weights for optimal paths in a navigation graph. Mech. Mach. Sci. 49, 372–380 (2018). https://doi.org/10.1007/978-3-319-61276-8_41
Muñoz, P., R-Moreno, M.D., Castaño, B.: 3Dana: a path planning algorithm for surface robotics. Eng. Appl. Artif. Intell. 60, 175–192 (2017). https://doi.org/10.1016/j.engappai.2017.02.010
Muñoz-Morera, J., Alarcon, F., Maza, I., Ollero, A.: Combining a hierarchical task network planner with a constraint satisfaction solver for assembly operations involving routing problems in a multi-robot context. Int. J. Adv. Robot. Syst. 15(3) (2018). https://doi.org/10.1177/1729881418782088
Ropero, F., Muñoz, P., R-Moreno, M.: TERRA: a path planning algorithm for cooperative UGV-UAV exploration. Eng. Appl. Artif. Intell. 78, 260–272 (2019). https://doi.org/10.1016/j.engappai.2018.11.008
San Juan, V., Santos, M., Andújar, J.: Intelligent UAV map generation and discrete path planning for search and rescue operations. Complexity 2018 (2018). https://doi.org/10.1155/2018/6879419
Gonzalez-de Soto, M., Emmi, L., Garcia, I., Gonzalez-de Santos, P.: Reducing fuel consumption in weed and pest control using robotic tractors. Comput. Electron. Agric. 114, 96–113 (2015). https://doi.org/10.1016/j.compag.2015.04.003
Wang, H., Zhang, H., Wang, K., Zhang, C., Yin, C., Kang, X.: Off-road path planning based on improved ant colony algorithm. Wirel. Pers. Commun. 102(2), 1705–1721 (2018). https://doi.org/10.1007/s11277-017-5229-5
Acknowledgments
This work has received funding from the national project RTI2018-093421-B-I00 (Spanish Government), Universidad de Málaga (Andalucía Tech) and the grant BES-2016-077022 of the European Social Fund.
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Toscano-Moreno, M., Mandow, A., Martínez, M.A., García-Cerezo, A. (2020). Velocity-Based Heuristic Evaluation for Path Planning and Vehicle Routing for Victim Assistance in Disaster Scenarios. In: Silva, M., Luís Lima, J., Reis, L., Sanfeliu, A., Tardioli, D. (eds) Robot 2019: Fourth Iberian Robotics Conference. ROBOT 2019. Advances in Intelligent Systems and Computing, vol 1093. Springer, Cham. https://doi.org/10.1007/978-3-030-36150-1_10
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