Agile and cooperative aerial manipulation of a cable-suspended load

Quadrotors can carry slung loads to hard-to-reach locations at high speed. Given that a single quadrotor has limited payload capacities, using a team of quadrotors to collaboratively manipulate the full pose of a heavy object is a scalable and promising solution. However, existing control algorithms for multilifting systems only enable low-speed and low-acceleration operations because of the complex dynamic coupling between quadrotors and the load, limiting their use in time-critical missions such as search and rescue. In this work, we present a solution to substantially enhance the agility of cable-suspended multilifting systems. Unlike traditional cascaded solutions, we introduce a trajectory-based framework that solves the whole-body kinodynamic motion planning problem online, accounting for the dynamic coupling effects and constraints between the quadrotors and the load. The planned trajectory is provided to the quadrotors as a reference in a receding-horizon fashion and is tracked by an onboard controller that observes and compensates for the cable tension. Real-world experiments demonstrate that our framework can achieve at least eight times greater acceleration than state-of-the-art methods to follow agile trajectories. Our method can even perform complex maneuvers such as flying through narrow passages at high speed. In addition, it exhibits high robustness against load uncertainties and wind disturbances and does not require adding any sensors to the load, demonstrating strong practicality.

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Publication Details

Journal
Science Robotics
Published
2025-10-29
DOI
https://doi.org/10.1126/scirobotics.adu8015
Citations
8
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
9.72
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article

Agile and cooperative aerial manipulation of a cable-suspended load

Antonio Franchi, Sihao Sun, Xuerui Wang, Javier Alonso–Mora et al.
8 citations
Science Robotics
Adaptive Control of Nonlinear Systems
9.72
article

Agile and cooperative aerial manipulation of a cable-suspended load

Antonio Franchi, Sihao Sun, Xuerui Wang, Javier Alonso–Mora, Marco Tognon, Dario Sanalitro
article en
8 citations

Abstract

Quadrotors can carry slung loads to hard-to-reach locations at high speed. Given that a single quadrotor has limited payload capacities, using a team of quadrotors to collaboratively manipulate the full pose of a heavy object is a scalable and promising solution. However, existing control algorithms for multilifting systems only enable low-speed and low-acceleration operations because of the complex dynamic coupling between quadrotors and the load, limiting their use in time-critical missions such as search and rescue. In this work, we present a solution to substantially enhance the agility of cable-suspended multilifting systems. Unlike traditional cascaded solutions, we introduce a trajectory-based framework that solves the whole-body kinodynamic motion planning problem online, accounting for the dynamic coupling effects and constraints between the quadrotors and the load. The planned trajectory is provided to the quadrotors as a reference in a receding-horizon fashion and is tracked by an onboard controller that observes and compensates for the cable tension. Real-world experiments demonstrate that our framework can achieve at least eight times greater acceleration than state-of-the-art methods to follow agile trajectories. Our method can even perform complex maneuvers such as flying through narrow passages at high speed. In addition, it exhibits high robustness against load uncertainties and wind disturbances and does not require adding any sensors to the load, demonstrating strong practicality.

Science RoboticsVol. 10(107)
Centre National de la Recherche Scientifique (FR), Institut de Recherche en Informatique et Systèmes Aléatoires (FR), Sorbonne Université (FR), Institut Systèmes Intelligents et de Robotique (FR), Université de Rennes (FR), Sapienza University of Rome (IT), University of Twente (NL), Delft University of Technology (NL)
Openalex Percentile: Top 2%
Adaptive Control of Nonlinear Systems
9.72
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