There is a need for safe and reliable aerial load transport through complex environments. In developing countries road networks may not exist or may be inaccessible for significant parts of the year due to seasonal rain, flood, or snow. In dense urban areas, energy and time costs of transportation are rapidly increasing due to road congestion. Autonomous aerial vehicles have emerged as a fast, economical alternative to delivery using traditional ground-based infrastructure. This project will show how the cargo-carrying limitations of single aerial vehicles may be overcome using multiple vehicles to cooperatively transport cable-supported loads. Current control approaches impede progress in this domain by ignoring the tight dynamical coupling between multiple aerial robots and the shared cable-suspended load, the dynamics on manifolds, the unilateral cable tension constraints, the collision constraints, the multiple hybrid dynamical modes, and the physical system limits. This project will address these issues, and furthermore show how operational flexibility associated with redundant vehicles and the hybrid nature of cable support may be exploited to achieve greater maneuverability of the load-carrying formation.
The overarching goal of this work is to understand the science at the intersection of geometric control and convex optimization for achieving cooperative highly-dynamic aerial manipulation that explicitly addresses the hybrid dynamics of the system while providing formal guarantees of stability and safety. The transformative nature of this research stems from its ability to generate theoretical advances in feedback control on multiple levels, while also being firmly grounded in being demonstrated on a physical system with stringent performance requirements and safety constraints. This work is therefore guided by the following goals (1) Formulate constrained geometric control for systems evolving on manifolds to enforce input and state constraints; (2) Develop safety-critical geometric control for systems evolving on manifolds to enforce formal collision-free dynamic motion; and (3) Demonstrate highly dynamic multi-agent cooperative aerial manipulation and transportation that switches between multiple hybrid dynamical modes. As a result of these research goals, this work has the potential to enable the next generation of aerial load transportation using teams of small unmanned aerial robots.
