Control de formación con evasión de colisiones en agentes de primer y segundo orden

Julio Castillo-Aparicio; Alondra Zutelly Vega-Arroyo; Jaime González-Sierra; Yair Lozano-Hernández

doi:10.29057/icbi.v11iEspecial4.11332

Julio Castillo-Aparicio Instituto Politécnico Nacional, UPIIH https://orcid.org/0009-0005-1147-8055
Alondra Zutelly Vega-Arroyo Instituto Politécnico Nacional, UPIIH https://orcid.org/0009-0002-9382-1416
Jaime González-Sierra Instituto Politécnico Nacional, UPIIH https://orcid.org/0000-0001-9141-0061
Yair Lozano-Hernández Instituto Politécnico Nacional, UPIIH https://orcid.org/0000-0001-8157-3510

DOI: https://doi.org/10.29057/icbi.v11iEspecial4.11332

Palabras clave: Control de formación, Evasión de colisiones, Agentes de primer y segundo orden

Resumen

Este artículo aborda el problema de control de formación con evasión de colisiones para un sistema multi-agente conformado por un agente de primer orden y un agente de segundo orden. La estrategia de control se basa en el enfoque de funciones saturadas para lograr la formación deseada y el enfoque de Campos Vectoriales Repulsivos (CVR) que permiten la evasión de colisiones. Debido a la naturaleza del agente de segundo orden, éste puede continuar su movimiento a pesar de haber alcanzado la formación deseada, por lo tanto, para evitar este inconveniente, se agrega un tercer agente como referencia con nula dinámica. Se demuestra que si existe un árbol de expansión dirigido con nodo raíz en el tercer agente, los errores de posición y velocidad convergen a cero. Además, se asume que las variables de posición, velocidad y aceleración se pueden medir. Se presentan simulaciones numéricas para evaluar el desempeño de los agentes utilizando diferentes gráficas de formación.

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Ajwad, S. A., Moulay, E., Defoort, M., Ménard, T., y Coirault, P. (2021). Collision-free formation tracking of multi-agent systems under communication constraints. IEEE Control Systems Letters, 5(4):1345–1350.

Aranda-Bricaire, E. y González-Sierra, J. (2023). Formation with non-collision control strategies for second-order multi-agent systems. Entropy, 25(6).

Dang, A. D., La, H. M., Nguyen, T., y Horn, J. (2019). Formation control for autonomous robots with collision and obstacle avoidance using a rotational and repulsive force–based approach. International Journal of Advanced Robotic Systems, 16(3).

Dou, L., Yu, X., Liu, L.,Wang, X., y Feng, G. (2021). Moving-target enclosing control for mobile agents with collision avoidance. IEEE Transactions on Control of Network Systems, 8(4):1669–1679.

Flores-Resendiz, J. F. y Aranda-Bricaire, E. (2020). A general solution to the formation control problem without collisions for first order multi-agent systems. Robotica, 38(6):1123–1137.

Flores-Resendiz, J. F., Aranda-Bricaire, E., González-Sierra, J., y Santiaguillo-Salinas, J. (2015). Finite-time formation control without collisions for multiagent systems with communication graphs composed of cyclic paths. Mathematical Problems in Engineering, pp. 1–17.

Flores-Resendiz, J. F., Avilés, D., y Aranda-Bricaire, E. (2023). Formation control for second-order multi-agent systems with collision avoidance. Machines, 11(2).

Gnanasekera, M. y Katupitiya, J. (2022). A time-efficient method to avoid collisions for collision cones: An implementation for uavs navigating in dynamic environments. Drones, 6(5).

Godsil, C. y Royle, G. (2001). Algebraic graph theory. Graduate Texts in Mathematics, Springer, New York, NY, USA, 207.

González-Sierra, J., Dzul, A., y Ríos, H. (2019). Robust sliding-mode formation control and collision avoidance via repulsive vector fields for a group of quad-rotors. International Journal of Systems Science, 50(7):1483–1500.

González-Sierra, J., Hernandez-Martinez, E., Ramírez-Neria, M., y Fernandez-Anaya, G. (2023). Smooth collision avoidance for the formation control of first order multi-agent systems. Robotics and Autonomous Systems, 165:104433.

Graham, A. (1981). Kronecker Products and Matrix Calculus With Applications. Halsted, New York.

Hernandez-Martinez, E. y Aranda-Bricaire, E. (2013). Collision avoidance in formation control using discontinuous vector fields. IFAC Proceedings Volumes, 46(23):797–802.

Hu, J., Zhang, H., Liu, L., Zhu, X., Zhao, C., y Pan, Q. (2020). Convergent multiagent formation control with collision avoidance. IEEE Transactions on Robotics, 36(6):1805–1818.

Huang, S., Teo, R. S. H., y Tan, K. K. (2019). Collision avoidance of multi unmanned aerial vehicles: A review. Annual Reviews in Control, 48:147–164.

Khatib, O. (1985). Real-time obstacle avoidance for manipulators and mobile robots. En Proceedings. 1985 IEEE International Conference on Robotics and Automation, volumen 2, pp. 500–505.

Kufoalor, D. K. M., Johansen, T. A., Brekke, E. F., Hepsø, A., y Trnka, K. (2019). Autonomous maritime collision avoidance: Field verification of autonomous surface vehicle behavior in challenging scenarios. Journal of Field Robotics, 37(3):387–403.

Li, S. yWang, X. (2013). Finite-time consensus and collision avoidance control algorithms for multiple auvs. Automatica, 49(11):3359–3367.

Liu, J., Zhao, M., y Qiao, L. (2022a). Adaptive barrier lyapunov function-based obstacle avoidance control for an autonomous underwater vehicle with multiple static and moving obstacles. Ocean Engineering, 243:110303.

Liu, X., Li, C., y Li, D. (2022b). Collision-avoiding formation for multiple euler–lagrange systems against external disturbances and actuator faults. Journal of the Franklin Institute, 359(12):6336–6360.

Mao, R. y Dai, H. (2021). Distributed non-convex model predictive control for non-cooperative collision avoidance of networked differential drive mobile robots. IEEE Access, pp. 1–9.

Meyer, E., Robinson, H., Rasheed, A., y San, O. (2020). Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning. IEEE Access, 8:41466–41481.

Na, S., Niu, H., Lennox, B., y Arvin, F. (2022). Bio-inspired collision avoidance in swarm systems via deep reinforcement learning. IEEE Transactions on Vehicular Technology, 71(3):2511–2526.

Panagou, D. (2014). Motion planning and collision avoidance using navigation vector fields. 2014 IEEE International Conference on Robotics and Automation (ICRA), p. 2513–2518.

Park, B. S. y Yoo, S. J. (2021). Connectivity-maintaining and collision-avoiding performance function approach for robust leader–follower formation control of multiple uncertain underactuated surface vessels. Automatica, 127(C).

Polvara, R., Sharma, S., Wan, J., Manning, A., y Sutton, R. (2018). Obstacle avoidance approaches for autonomous navigation of unmanned surface vehicles. The Journal of Navigation, 71(1):241–256.

Raj, J., Raghuwaiya, K., y Vanualailai, J. (2020). Collision avoidance of 3d rectangular planes by multiple cooperating autonomous agents. Journal of Advanced Transportation, 2020(6):1–13.

Ren, W. y Beard, R. W. (2008). Distributed consensus in multi-vehicle cooperative control:theory and applications. Communications and Control Engineering Series, Springer, London, UK.

Sakai, D., Fukushima, H., y Matsuno, F. (2018). Leader-follower navigation in obstacle environments while preserving connectivity without data transmission. IEEE Transactions on Control Systems Technology, 26(4):1233–1248.

Santiaguillo-Salinas, J. y Aranda-Bricaire, E. (2017). Motion coordination problems with collision avoidance for multiagent systems. In (Ed.), Multi-agent Systems. IntechOpen, pp. 17–41.

Seung-Mok, L. y Hyun, M. (2015). Receding horizon particle swarm optimisation-based formation control with collision avoidance for nonholonomic mobile robots. IET Control Theory & Applications, 9(14):2075–2083.

Smith, N., Cobb, R., Pierce, S., y Raska, V. (2014). Optimal collision avoidance trajectories via direct orthogonal collocation for unmanned/remotely piloted aircraft sense and avoid operations. AIAA Guidance, Navigation, and Control Conference, pp. 1–25.

Sui, Z., Pu, Z., Yi, J., yWu, S. (2021). Formation control with collision avoidance through deep reinforcement learning using model-guided demonstration. IEEE Transactions on Neural Networks and Learning Systems, 32(6):2358–

Teel, A. R. (1992). Global stabilization and restricted tracking for multiple integrators with bounded controls. Systems & Control Letters, 18:165–171.

Vargas, S., Becerra, H. M., y Hayet, J.-B. (2022). Mpc-based distributed formation control of multiple quadcopters with obstacle avoidance and connectivity maintenance. Control Engineering Practice, 121:105054.

Woo, J. y Kim, N. (2020). Collision avoidance for an unmanned surface vehicle using deep reinforcement learning. Ocean Engineering, 199:107001.

Yang, S., Weiwei, B., Li, T., Shi, Q., Yang, Y., Yue, W., y Chen, C. (2021). Neural-network-based formation control with collision, obstacle avoidance and connectivity maintenance for a class of second-order nonlinear multiagent systems. Neurocomputing, 439.

Yasin, J. N., Mohamed, S. A. S., Haghbayan, M.-H., Heikkonen, J., Tenhunen, H., y Plosila, J. (2020). Unmanned aerial vehicles (uavs): Collision avoidance systems and approaches. IEEE Access, 8:105139–105155.

Yoo, S. J. y Kim, T.-H. (2015). Distributed formation tracking of networked mobile robots under unknown slippage effects. Automatica, 54:100–106.

Yoo, S. J. y Park, B. S. (2019). Connectivity preservation and collision avoidance in networked nonholonomic multi-robot formation systems: Unified error transformation strategy. Automatica, 103:274–281.