MPC-based control of a cable-suspended load using multiple UAVs for dynamic motions

Full pose manipulation of a cable-suspended load using multiple UAVs is a promising technique for a huge variety of future industrial applications, such as heavy payload transportation and autonomous building constructions. The physical interactions between UAVs, load and cables render collaborative manipulation a challenging task from both a planning and control perspective. Existing solutions require either quasi-static assumptions that limit the dynamic behaviour of the system, which limits their operational speeds; or neglect safety-related constraints such as cable tautness and non-collisions between UAVs. Therefore, this project envisions developing the next generation of multi-UAV systems to achieve fast, safe, and robust manipulation of a cable-suspended load in the real world. 
In this project, the student will collaborate with researchers from the University of Twente and the University of Catania, to develop and experimentally validate a novel theory based on nonlinear model predictive control (NMPC) and adaptive control.

List of 5 bibliographical references:

1. Sun, S., & Franchi, A. (2023). Nonlinear MPC for full-pose manipulation of a cable-suspended load using multiple UAVs. arXiv preprint arXiv:2301.08545.
2. Sanalitro, D. (2022). Aerial Cooperative Manipulation: full pose manipulation in air and in interaction with the environment (Doctoral dissertation, INSA de Toulouse).
3. Smeur, E. J., Chu, Q., & De Croon, G. C. (2016). Adaptive incremental nonlinear dynamic inversion for attitude control of micro air vehicles. Journal of Guidance, Control, and Dynamics, 39(3), 450-461.
4. Hamandi, M., Tognon, M., & Franchi, A. (2020, May). Direct acceleration feedback control of quadrotor aerial vehicles. In 2020 IEEE International Conference on Robotics and Automation (ICRA) (pp. 5335-5341). IEEE.
5. Sanalitro, D., Savino, H. J., Tognon, M., Cortés, J., & Franchi, A. (2020). Full-pose manipulation control of a cable-suspended load with multiple UAVs under uncertainties. IEEE Robotics and Automation Letters, 5(2), 2185-2191.