GeoSafe: A Unified Unconstrained Multi-DOF Optimization Framework for Multi-UAV Cooperative Hoisting and Obstacle Avoidance
Xingyu Li, Hongyu Nie, Haoxuan Xu, Xingrui Liu, Zhaotong Tan, Chunyu Jiang, Yang Feng, Sen Mei
Abstract
In warehouse logistics and post-disaster rescue, multi-UAV payload transport must navigate tight spaces, such as 1.2m × 0.8m aisles and collapsed pipelines as narrow as 0.6m. Traditional four-DOF (translation and scaling) trajectory planning struggles under such constraints. To overcome this, we propose an optimization-based framework that introduces rotational degrees of freedom, expanding the solution space to five dimensions. Using the MINCO transformation, we reformulate constrained formation adjustment into an unconstrained optimization problem via smooth mappings and penalty functions, enabling simultaneous obstacle avoidance and formation control. The GeoSafe algorithm further enhances safe passage by integrating iterative region expansion and semi-definite programming to maximize obstacle-free space. Extensive simulations and real-world experiments show our method’s superiority over sampling-based and IF-based approaches in narrow passage traversal, computational efficiency, and formation scalability.
BibTeX
@inproceedings{iros2025_geosafeaunifiedu,
title = {GeoSafe: A Unified Unconstrained Multi-DOF Optimization Framework for Multi-UAV Cooperative Hoisting and Obstacle Avoidance},
author = {Xingyu Li and Hongyu Nie and Haoxuan Xu and Xingrui Liu and Zhaotong Tan and Chunyu Jiang and Yang Feng and Sen Mei},
booktitle = {IROS 2025},
year = {2025}
}