Collision Avoidance and Geofencing for Fixed-wing Aircraft with Control Barrier Functions (2403.02508v2)
Abstract: Safety-critical failures often have fatal consequences in aerospace control. Control systems on aircraft, therefore, must ensure the strict satisfaction of safety constraints, preferably with formal guarantees of safe behavior. This paper establishes the safety-critical control of fixed-wing aircraft in collision avoidance and geofencing tasks. A control framework is developed wherein a run-time assurance (RTA) system modulates the nominal flight controller of the aircraft whenever necessary to prevent it from colliding with other aircraft or crossing a boundary (geofence) in space. The RTA is formulated as a safety filter using control barrier functions (CBFs) with formal guarantees of safe behavior. CBFs are constructed and compared for a nonlinear kinematic fixed-wing aircraft model. The proposed CBF-based controllers showcase the capability of safely executing simultaneous collision avoidance and geofencing, as demonstrated by simulations on the kinematic model and a high-fidelity dynamical model.
- K. L. Hobbs, M. L. Mote, M. C. Abate, S. D. Coogan, and E. M. Feron, “Runtime assurance for safety-critical systems: An introduction to safety filtering approaches for complex control systems,” IEEE Control Systems Magazine, vol. 43, no. 2, pp. 28–65, 2023.
- O. Khatib, “Real-time obstacle avoidance for manipulators and mobile robots,” in IEEE International Conference on Robotics and Automation, vol. 2, 1985, pp. 500–505.
- Y.-b. Chen, G.-c. Luo, Y.-s. Mei, J.-q. Yu, and X.-l. Su, “UAV path planning using artificial potential field method updated by optimal control theory,” International Journal of Systems Science, vol. 47, no. 6, pp. 1407–1420, 2016.
- P. Fiorini and Z. Shiller, “Motion planning in dynamic environments using velocity obstacles,” The International Journal of Robotics Research, vol. 17, no. 7, pp. 760–772, 1998.
- A. Haraldsen, M. S. Wiig, A. D. Ames, and K. Y. Pettersen, “Safety-critical control of nonholonomic vehicles in dynamic environments using velocity obstacles,” arXiv preprint, arXiv:2310.00713, 2023.
- A. D. Ames, X. Xu, J. W. Grizzle, and P. Tabuada, “Control barrier function based quadratic programs for safety critical systems,” IEEE Transactions on Automatic Control, vol. 62, no. 8, pp. 3861–3876, 2017.
- Y. Shoukry, P. Tabuada, S. Tsuei, M. B. Milam, J. W. Grizzle, and A. D. Ames, “Closed-form controlled invariant sets for pedestrian avoidance,” in American Control Conference, 2017, pp. 1622–1628.
- U. J. Ravaioli, J. Cunningham, J. McCarroll, V. Gangal, K. Dunlap, and K. L. Hobbs, “Safe reinforcement learning benchmark environments for aerospace control systems,” in IEEE Aerospace Conference, 2022, pp. 1–20.
- M. Tayal and S. Kolathaya, “Control barrier functions in dynamic UAVs for kinematic obstacle avoidance: A collision cone approach,” arXiv preprint, no. arXiv:2303.15871, 2023.
- A. Singletary, K. Klingebiel, J. R. Bourne, N. A. Browning, P. Tokumaru, and A. Ames, “Comparative analysis of control barrier functions and artificial potential fields for obstacle avoidance,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021, pp. 8129–8136.
- W. Luo and A. Kapoor, “Airborne collision avoidance systems with probabilistic safety barrier certificates,” in NeurIPS ’19 Workshop on Safety and Robustness in Decision-making, 2019.
- E. Scukins and P. Ögren, “Using reinforcement learning to create control barrier functions for explicit risk mitigation in adversarial environments,” in IEEE International Conference on Robotics and Automation, 2021, pp. 10 734–10 740.
- E. Squires, R. Konda, S. Coogan, and M. Egerstedt, “Model free barrier functions via implicit evading maneuvers,” arXiv preprint, no. arXiv:2107.12871, 2021.
- E. Squires, P. Pierpaoli, R. Konda, S. Coogan, and M. Egerstedt, “Composition of safety constraints for fixed-wing collision avoidance amidst limited communications,” Journal of Guidance, Control, and Dynamics, vol. 45, no. 4, pp. 714–725, 2022.
- H. Zhou, Z. Zheng, Z. Guan, and Y. Ma, “Control barrier function based nonlinear controller for automatic carrier landing,” in 16th International Conference on Control, Automation, Robotics and Vision, 2020, pp. 584–589.
- Y. Xu, R. Zhou, Z. Yu, F. Chen, and Y. Zhang, “Barrier Lyapunov function-based finite-time reliable trajectory tracking control of fixed-wing UAV with error constraints,” IFAC-PapersOnLine, vol. 55, no. 6, pp. 597–602, 2022.
- Z. Zheng, J. Li, Z. Guan, and Z. Zuo, “Constrained moving path following control for UAV with robust control barrier function,” IEEE/CAA Journal of Automatica Sinica, vol. 10, no. 7, pp. 1557–1570, 2023.
- A. Ghaffari, “Analytical design and experimental verification of geofencing control for aerial applications,” IEEE/ASME Transactions on Mechatronics, vol. 26, no. 2, pp. 1106–1117, 2021.
- A. Singletary, A. Swann, Y. Chen, and A. D. Ames, “Onboard safety guarantees for racing drones: High-speed geofencing with control barrier functions,” IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 2897–2904, 2022.
- I. Lugo-Cárdenas, G. Flores, S. Salazar, and R. Lozano, “Dubins path generation for a fixed wing UAV,” in International Conference on Unmanned Aircraft Systems, 2014, pp. 339–346.
- M. Owen, R. W. Beard, and T. W. McLain, “Implementing Dubins airplane paths on fixed-wing UAVs,” in Handbook of Unmanned Aerial Vehicles, K. P. Valavanis and G. J. Vachtsevanos, Eds. Dordrecht: Springer Netherlands, 2015, pp. 1677–1701.
- A. Ames, J. Grizzle, and P. Tabuada, “Control barrier function based quadratic programs with application to adaptive cruise control,” in 53rd IEEE Conference on Decision and Control, 2014, pp. 6271–6278.
- M. H. Cohen, P. Ong, G. Bahati, and A. D. Ames, “Characterizing smooth safety filters via the implicit function theorem,” IEEE Control Systems Letters, vol. 7, pp. 3890–3895, 2023.
- T. G. Molnar and A. D. Ames, “Composing control barrier functions for complex safety specifications,” IEEE Control Systems Letters, vol. 7, pp. 3615–3620, 2023.
- L. Lindemann and D. V. Dimarogonas, “Control barrier functions for signal temporal logic tasks,” IEEE Control Systems Letters, vol. 3, no. 1, pp. 96–101, 2019.
- Q. Nguyen and K. Sreenath, “Exponential Control Barrier Functions for enforcing high relative-degree safety-critical constraints,” in American Control Conference, 2016, pp. 322–328.
- W. Xiao and C. Belta, “Control barrier functions for systems with high relative degree,” in 58th IEEE Conference on Decision and Control, 2019, pp. 474–479.
- W. Xiao, C. G. Cassandras, C. A. Belta, and D. Rus, “Control barrier functions for systems with multiple control inputs,” in American Control Conference, 2022, pp. 2221–2226.
- A. J. Taylor, P. Ong, T. G. Molnar, and A. D. Ames, “Safe backstepping with control barrier functions,” in 61st IEEE Conference on Decision and Control, 2022, pp. 5775–5782.
- T. G. Molnar, R. K. Cosner, A. W. Singletary, W. Ubellacker, and A. D. Ames, “Model-free safety-critical control for robotic systems,” IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 944–951, 2022.
- S. Kolathaya and A. D. Ames, “Input-to-state safety with control barrier functions,” IEEE Control Systems Letters, vol. 3, no. 1, pp. 108–113, 2019.
- A. Alan, A. J. Taylor, C. R. He, G. Orosz, and A. D. Ames, “Safe controller synthesis with tunable input-to-state safe control barrier functions,” IEEE Control Systems Letters, vol. 6, pp. 908–913, 2022.
- “DOD artificial intelligence agents successfully pilot fighter jet,” www.afrl.af.mil/News/Article-Display/Article/3297364/dod-artificial-intelligence-agents-successfully-pilot-fighter-jet, accessed: 2024/02/26.
- R. A. Freeman and P. V. Kokotović, “Backstepping design of robust controllers for a class of nonlinear systems,” IFAC Proceedings Volumes, vol. 25, no. 13, pp. 431–436, 1992.