Autonomous Collaborative Transport of a Beam-Type Payload by a Pair of Multi-rotor Helicopters

Horyna, Jiri; Báča, Tomáš; Saska, Martin

doi:10.1109/icuas51884.2021.9476789

Cited by 4 publications

(1 citation statement)

References 21 publications

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“…Research in UAV swarm cooperative networks provides robust theoretical underpinnings for the extensive deployment of UAV systems, thereby enhancing their functionality across various fields [10,11]. These networks bolster system redundancy and robustness, ensuring stability and reliability even in the event of individual UAV failures [12].…”

Section: Introductionmentioning

confidence: 99%

Distributed Computing Optimization in Unmanned Aerial Vehicle Swarm Cooperative Networks

Luo,

Zhang,

Shi

et al. 2024

CIT. J. comput. inf. technol

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The Unmanned Aerial Vehicle (UAV) swarm cooperative networks across diverse domains present significant challenges in management and control to maximize collaborative efficiency, particularly in applications for large-scale and dynamic environments where real-time coordination is essential. This challenge has led to the development of a UAV swarm cooperative network flow prediction model, facilitating the strategic anticipation of network dynamics. A novel algorithm for distributed, finite-time cooperative control is introduced, grounded in this model. This algorithm optimizes the operational efficiency and control precision of UAV systems, while simultaneously augmenting the collaborative efficiency and stability of the UAV swarms. It marks a significant advancement in distributed computing strategies, offering a viable solution for the real-time coordination challenges in extensive UAV swarm cooperative networks. The proposed approach leverages multi-agent technology, integrating spatial-temporal constraints, location limitations, and path selection in cooperative behavior for dynamic and effective network management. This study not only enhances the understanding of UAV swarm dynamics but also contributes to the practical application of UAV swarms in areas requiring precise coordination and robust network stability.

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Section: Introductionmentioning

confidence: 99%

Distributed Computing Optimization in Unmanned Aerial Vehicle Swarm Cooperative Networks

Luo,

Zhang,

Shi

et al. 2024

CIT. J. comput. inf. technol

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Cooperative Load Transportation With Two Quadrotors Using Adaptive Control

et al. 2021

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The problem of carrying a bar-shaped payload suspended by flexible cables attached to two quadrotors is analyzed in this work. The aerial vehicles and the load are dealt with as a single system, whose kinematics is described as a multi-robot formation using the virtual structure approach. The dynamic effects caused by the tethered load over the quadrotors, as well as those caused by each quadrotor over the other, are treated by an adaptive dynamic compensator. To validate the proposal, experiments were run testing the system in adverse conditions: transportation far from quasi-static motion, high payload-to-quadrotor weight ratio, 20% of error in the robot model parameters, transportation under wind disturbances, and payload weight changes during flight. The good performance of the proposed control system in all these tests allows concluding that the proposed system is able to accomplish payload positioning, orientation, and trajectory tracking under adverse conditions, with accelerations up to 1.6 m/s 2 .

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Collaborative Object Manipulation on the Water Surface by a UAV-USV Team Using Tethers

Novák,

Báča,

Saska

2024

2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Autonomous Collaborative Transport of a Beam-Type Payload by a Pair of Multi-rotor Helicopters

Cited by 4 publications

References 21 publications

Distributed Computing Optimization in Unmanned Aerial Vehicle Swarm Cooperative Networks

Distributed Computing Optimization in Unmanned Aerial Vehicle Swarm Cooperative Networks

Cooperative Load Transportation With Two Quadrotors Using Adaptive Control

Collaborative Object Manipulation on the Water Surface by a UAV-USV Team Using Tethers

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