Spatial collision avoidance for Quadrotors

https://doi.org/10.58571/CNCA.AMCA.2024.005

Resumen: This article presents an algorithm for robust trajectory tracking and a three-dimensional collision avoidance strategy for perturbed quadrotors operating in the same airspace. When activated, the avoidance strategy forms a three-dimensional repulsive vector field around each vehicle. A control law, based on the direction of the vector field, ensures collision avoidance. The robust control law for trajectory tracking compensates for constant unknown disturbances. The trajectory tracking and collision avoidance strategies are then practically validated, demonstrating their real-world applicability.

¿Cómo citar?

Trujillo Flores, M., Martinez Ramirez, M., Romero, J.G. & Rodriguez Cortes, H. (2024). Spatial collision avoidance for Quadrotors. Memorias del Congreso Nacional de Control Automático 2024, pp. 24-29. https://doi.org/10.58571/CNCA.AMCA.2024.005

Palabras clave

Collision avoidance, Quadrotor, Soft real-time, Nonlinear control

• Aslan, M.F., Durdu, A., Sabanci, K., Ropelewska, E., and Gültekin, S.S. (2022). A comprehensive survey of the recent studies with UAV for precision agriculture in open fields and greenhouses. Applied Sciences, 12(3). doi:10.3390/app12031047. URL https://www.mdpi.com/2076-3417/12/3/1047.
• Astolfi, A., Karagiannis, D., and Ortega, R. (2008). Nonlinear and Adaptive Control with Applications, volume 187. Springer.
  Barnes, L., Fields, M., and Valavanis, K. (2007). Unmanned ground vehicle swarm formation control using potential fields. In 2007 Mediterranean Conference on Control Automation, 1–8. doi: 10.1109/MED.2007.4433724.
• Belge, E., Altan, A., and Hacıoglu, R. (2022). Metaheuristic optimization-based path planning and tracking of quadcopter for payload hold-release mission. Electronics, 11(8). doi:10.3390/electronics11081208. URL https://www.mdpi.com/2079-9292/11/8/1208.
• Concei¸cao, M.I., Concei¸cao, E., Grilo, A., Basiri, M., and Awbi, H. (2023). The application of uavs in the evaluation of thermal comfort levels in buildings equipped with internal greenhouses. Clean Technologies, 5(3), 1080–1114. doi:10.3390/cleantechnol5030055.
• DJI-Enterprise (2024). Mobile software development kit. URL https://developer.dji.com/mobile-sdk/. Last accesed 25-06-2024.
• Ehang (2024). Ehang aerial light show. URL https://www.ehang.com/formation/. Accesed 20-06-2024.
• Fiorini, P. and Shiller, Z. (1998). Motion planning in dynamic environments using velocity obstacles. The International Journal of Robotics Research, 17(7), 760–772. doi: 10.1177/027836499801700706. URL https://doi.org/10.1177/027836499801700706.
• González-Sierra, J., Hernandez-Martinez, E., Ramírez-Neria, M., and Fernandez-Anaya, G. (2023). Smooth collision avoidance for
  the formation control of first order multi-agent systems. Robotics and Autonomous Systems, 165, 104433. doi:https://doi.org/10.1016/j.robot.2023.104433. URL https://www.sciencedirect.com/science/article/pii/S0921889023000726.
  gRPC Authors (2024). Rpc framework. URL https://grpc.io/. Last accesed 25-06-2024.
• Habibi, H., Safaei, A., Voos, H., Darouach, M., and Sanchez-Lopez, J.L. (2023). Safe navigation of a quadrotor uav with uncertain dynamics and guaranteed collision avoidance using barrier Lyapunov function. Aerospace Science and Technology, 132, 108064. doi: https://doi.org/10.1016/j.ast.2022.108064. URL https://www.sciencedirect.com/science/article/pii/S1270963822007386.
• Hernández-Martínez, E.G. and Aranda-Bricaire, E. (2009). Multiagent formation control with collision avoidance based on discontinuous vector fields. In 2009 35th Annual Conference of IEEE Industrial Electronics, 2283–2288. doi:10.1109/IECON.2009.5415217.
• Javaid, M., Khan, I., Singh, R., Rab, S., and Suman, R. (2022). Exploring contributions of drones towards industry 4.0. Industrial Robot, 49(3), 476–490. doi:https://doi.org/10.1108/IR-09-2021-0203.
• Kaplan, K. (2016). 500 drones light night sky to set record. URL https://www.new-techeurope.com/2016/11/06/intel-drone-technology-breaking-new-ground/. Accesed 20-06-2024.
• Loizou, S.G. (2017). The navigation transformation. IEEE Transactions on Robotics, 33(6), 1516–1523.
  Malang, C., Charoenkwan, P., and Wudhikarn, R. (2023). Implementation and critical factors of unmanned aerial vehicle (uav) in warehouse management: A systematic literature review. Drones, 7(2). doi:10.3390/drones7020080. URL https://www.mdpi.com/2504-446X/7/2/80.
• Mendoza-Soto, J.L., Alvarez-Icaza, L., and Rodríguez-Cortés, H. (2018). Constrained generalized predictive control for obstacle avoidance in a quadcopter. Robotica, 36(9), 1363–1385. doi: 10.1017/S026357471800036X.
• Morelli, E.A. and Klein, V. (2016). Aircraft system identification: theory and practice, volume 2. Sunflyte Enterprises Williamsburg, VA.
  Olivares, V., Cordova, F., Sepúlveda, J.M., and Derpich, I. (2015). Modeling internal logistics by using drones on the stage of assembly of products. Procedia Computer Science, 55, 1240–1249. doi:https://doi.org/10.1016/j.procs.2015.07.132. URL https://www.sciencedirect.com/science/article/pii/S1877050915016075. 3rd International Conference on Information Technology and Quantitative Management, ITQM 2015.
• OptiTrack (2024). Motive, optical motion capture software. URL https://optitrack.com/software/motive/. Last accesed 25-06-2024.
• Pan, Z., Zhang, C., Xia, Y., Xiong, H., and Shao, X. (2022). An improved artificial potential field method for path planning and formation control of the multi-uav systems. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(3), 1129–1133. doi:10.1109/TCSII.2021.3112787.
• Ramírez-Rodríguez, J.M., Tlatelpa-Osorio, Y.E., and RodríguezCortés, H. (2021). Low level controller for quadrotors. In 2021 International Conference on Unmanned Aircraft Systems (ICUAS), 1155–1161. doi:10.1109/ICUAS51884.2021.9476683.
• Restrepo, E., Sarras, I., Loria, A., and Marzat, J. (2019). 3d uav navigation with moving-obstacle avoidance using barrier Lyapunov functions. IFAC-PapersOnLine, 52(12), 49–54. doi: https://doi.org/10.1016/j.ifacol.2019.11.068. URL https://www.sciencedirect.com/science/article/pii/S2405896319310031. 21st IFAC Symposium on Automatic Control in Aerospace ACA 2019.
• Rodríguez-Cortés, H. and Velasco-Villa, M. (2022). A new geometric trajectory tracking controller for the unicycle mobile robot. Systems Control Letters, 168, 105360. doi:https://doi.org/10.1016/j.sysconle.2022.105360. URL https://www.sciencedirect.com/science/article/pii/S0167691122001414.
• Romero, J.G., Navarro, D., Nuno, E., and Que, H. (2022). A globally convergent adaptive velocity observer for nonholonomic mobile robots affected by unknown disturbances. IEEE Control Systems Letters, 7, 85–90.
• Romero, J.G., Nuno, E., and Aldana, C.I. (2024). Global consensus-based formation control of perturbed nonholonomic mobile robots with time varying delays. Journal of the Franklin Institute, 361(2), 557–571.
• Waibel, M., Keays, B., and Augugliaro, F. (2017). Drone shows: Creative potential and best practices. Technical report, ETH Zürich. URL https://doi.org/10.3929/ethz-a-010831954.