# Nonlinear MPC for Full-Pose Manipulation of a Cable-Suspended Load using Multiple UAVs

arXiv: https://arxiv.org/abs/2301.08545 · HTML: https://mlsanity.com/paper/2301.08545/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Jan 2023.

## Built on by (most cited first, 3 of 3)

- [DiffCoord: Differentiable Coordination for Distributed Multi-Agent Trajectory Optimization](https://mlsanity.com/paper/2509.01630/) (2025)
- [Wiggle and Go! System Identification for Zero-Shot Dynamic Rope Manipulation](https://mlsanity.com/paper/2604.22102/) (2026)
- [Safe and Scalable Multi-Drone Payload Transport via CBF-based Reinforcement Learning with Zero-Shot Sim-to-Real Transfer](https://mlsanity.com/paper/2607.20665/) (2026)

## Abstract (arXiv)

In this work, we propose a centralized control method based on nonlinear model predictive control to let multiple UAVs manipulate the full pose of an object via cables. At the best of the authors knowledge this is the first method that takes into account the full nonlinear model of the load-UAV system, and ensures all the feasibility constraints concerning the UAV maximumum and minimum thrusts, the collision avoidance between the UAVs, cables and load, and the tautness and maximum tension of the cables. By taking into account the above factors, the proposed control algorithm can fully exploit the performance of UAVs and facilitate the speed of operation. Simulations are conducted to validate the algorithm to achieve fast and safe manipulation of the pose of a rigid-body payload using multiple UAVs. We demonstrate that the computational time of the proposed method is sufficiently small (<100 ms) for UAV teams composed by up to 10 units, which makes it suitable for a huge variety of future industrial applications, such as autonomous building construction and heavy-load transportation.