paper-with-me

Papers

Docking Multirotors in Close Proximity using Learnt Downwash Models

2023-11-23 · Ajay Shankar, Heedo Woo, Amanda Prorok

Unmodeled aerodynamic disturbances pose a key challenge for multirotor flight when multiple vehicles are in close proximity to each other. However, certain missions \textit{require} two multirotors to approach each other within 1-2 body-lengths of each other and hold formation -- we consider one such practical instance: vertically docking two multirotors in the air. In this leader-follower setting, the follower experiences significant downwash interference from the leader in its final docking stages. To compensate for this, we employ a learnt downwash model online within an optimal feedback controller to accurately track a docking maneuver and then hold formation. Through real-world flights with different maneuvers, we demonstrate that this compensation is crucial for reducing the large vertical separation otherwise required by conventional/naive approaches. Our evaluations show a tracking error of less than 0.06m for the follower (a 3-4x reduction) when approaching vertically within two body-lengths of the leader. Finally, we deploy the complete system to effect a successful physical docking between two airborne multirotors in a single smooth planned trajectory.

📄 PDF Abstract BibTeX arXiv:2311.13988

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

SO(2)-Equivariant Downwash Models for Close Proximity Flight

2023-05-30 · H. Smith, A. Shankar, J. Gielis, J. Blumenkamp 외

Multirotors flying in close proximity induce aerodynamic wake effects on each other through propeller downwash. Conventional methods have fallen short of providing adequate 3D force-based models that can be incorporated …

Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions

2020-03-06 · Guanya Shi, Wolfgang Hönig, Yisong Yue, Soon-Jo Chung

In this paper, we present Neural-Swarm, a nonlinear decentralized stable controller for close-proximity flight of multirotor swarms. Close-proximity control is challenging due to the complex aerodynamic interaction effec…

Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms using Learned Interactions

2020-12-10 · Guanya Shi, Wolfgang Hönig, Xichen Shi, Yisong Yue 외

We present Neural-Swarm2, a learning-based method for motion planning and control that allows heterogeneous multirotors in a swarm to safely fly in close proximity. Such operation for drones is challenging due to complex…

Motion Planning

Influence of Static and Dynamic Downwash Interactions on Multi-Quadrotor Systems

2025-07-13 · Anoop Kiran, Nora Ayanian, Kenneth Breuer arxiv

Flying multiple quadrotors in close proximity presents a significant challenge due to complex aerodynamic interactions, particularly downwash effects that are known to destabilize vehicles and degrade performance. Tradit…

Collision Avoidance

FLOAT Drone for Physical Interaction: Lateral Airflow Reduction, Wrench Modeling, and Adaptive Control

2026-07-05 · Junxiao Lin, Kehan Zhou, Shuhang Ji, Yimin Peng 외 arxiv

Aerial physical interaction represents a promising direction for next-generation unmanned aerial vehicles (UAVs), but it requires an aerial platform that can exert contact forces while maintaining stable flight. For clos…