Data-Driven Modeling of Ground Effect For UAV Landing on a Vertical Oscillating Platform

Binglin He, Heng Zhang, Baisheng Lai, Song Liu, Yang Wang

Abstract: Landing on a vertically oscillating platform poses a significant challenge for multi-rotor unmanned aerial vehicle (UAVs) due to the time-varying ground effect (GE). In this work, we formulated a data-driven GE dynamic model that accurately describes the complex interactions between UAVs and both stationary and oscillating platforms. Integrating this model with a feedforward controller effectively compensates for GE, resulting in improved landing performance. The proposed GE model elucidates the relationship between GE and factors such as UAVs’ velocity, throttle magnitude, and the motion of the landing platform. It highlights that the GE experienced during the landing process of UAVs is not only contingent on the current state but also related to past states. The resulting GE model is parsimonious and suitable for onboard computers with limited computational power, and its accuracy has been confirmed through a series of flight experiments. To demonstrate the effectiveness of the developed UAVs landing scheme, we compared our approach with robust control and internal model control methods. Experimental results indicate that the proposed landing strategy achieves faster and smoother landings, with at least a 22% improvement in smoothness and a 25% reduction in landing time.

External IDs:dblp:conf/iros/HeZL0024