Downwash-aware Control Allocation for Over-actuated UAV Platforms
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Abstract (arXiv)
Tracking position and orientation independently affords more agile maneuver for over-actuated multirotor Unmanned Aerial Vehicles (UAVs) while introducing undesired downwash effects; downwash flows generated by thrust generators may counteract others due to close proximity, which significantly threatens the stability of the platform. The complexity of modeling aerodynamic airflow challenges control algorithms from properly compensating for such a side effect. Leveraging the input redundancies in over-actuated UAVs, we tackle this issue with a novel control allocation framework that considers downwash effects and explores the entire allocation space for an optimal solution. This optimal solution avoids downwash effects while providing high thrust efficiency within the hardware constraints. To the best of our knowledge, ours is the first formal derivation to investigate the downwash effects on over-actuated UAVs. We verify our framework on different hardware configurations in both simulation and experiment.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Jul 2022.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 0; 2026: 1.
3 papers.
- 2023OmniDrones: An Efficient and Flexible Platform for Reinforcement Learning in Drone Controlcited by 33
- 2024ProxFly: Robust Control for Close Proximity Quadcopter Flight via Residual Reinforcement Learningcited by 4
- 2026Drag-Aware Aerodynamic Manipulability for Torque-Limited Redundant Multirotors: Aerodynamic Promptness based on the Symmetric Acceleration Capacitycited by 0
- 2026Drag-Aware Aerodynamic Manipulability for Torque-Limited Redundant Multirotors: Aerodynamic Promptness based on the Symmetric Acceleration Capacity9 Mar 2026
- 2024ProxFly: Robust Control for Close Proximity Quadcopter Flight via Residual Reinforcement Learning20 Sep 2024
- 2023OmniDrones: An Efficient and Flexible Platform for Reinforcement Learning in Drone Control22 Sep 2023