AirBender: Adaptive Transportation of Bendable Objects Using Dual UAVs
Jiawei Xu, Longsen Gao, Rafael Fierro, David Saldaña
AI summary
Problem
Transporting bendable objects in midair with aerial robots is challenging due to unknown elastic forces, nonlinear deformations, and the risk of instability or crashes, especially when explicit physical models are unavailable.
Approach
The authors develop an adaptive trajectory-tracking controller that uses recursive least-squares approximation to estimate the unknown bending force from vehicle states and continuously compensates for it without requiring an explicit elasticity model.
Key results
- Proven asymptotic stability via Lyapunov analysis
- Real-time force estimation using continuous recursive least-squares
- Successful hardware experiments with dual quadrotors transporting a carbon-fiber strip
- Adaptation to unknown mass, density, and Young’s modulus
Why it matters
Enables aerial robots to safely manipulate deformable payloads, expanding their utility in agriculture, construction, and search-and-rescue where rigid-object assumptions fail.
Abstract
The interaction of robots with bendable objects in midair presents significant challenges in control, often resulting in performance degradation and potential crashes, especially for aerial robots due to their limited actuation capabilities and constant need to remain airborne. This letter presents an adaptive controller thatenablestwoaerialvehiclestocollaborativelyfollowatrajectory while transporting a bendable object without relying on explicit elasticity models. Our method allows on-the-fly adaptation to the object’s unknown deformable properties, ensuring stability and performance in trajectory-tracking tasks. We use Lyapunov anal- ysis to demonstrate that our adaptive controller is asymptotically stable. Our method is evaluated through hardware experiments in various scenarios, demonstrating the capabilities of using multiro- tor aerial vehicles to handle bendable objects. IndexTerms—Aerialsystems:Mechanicsandcontrol,robust/ad- aptive control, aerial systems: Applications.