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Falconry-like palm landing by a flapping-wing drone based on the human gesture interaction and distance-aware flight planning

Kazuki Numazato, Keiichiro Kan, Masaki Kitagawa, Yunong Li, Johannes Kubel, Moju Zhao

TL;DR

The paper tackles safe and intuitive physical interaction between humans and flapping-wing drones by drawing inspiration from falconry, enabling a palm landing on a human hand. It introduces a simple human-gesture interface and a distance- and psychology-aware trajectory planner, underpinned by a dynamic flapping-wing drone model and a four-domain approach strategy. Real-world experiments using a motion-capture–drone testbed demonstrate feasible palm landing with measurable tracking accuracy ($\mathrm{RMSE}\approx0.17\mathrm{m}$), controlled timing, and maintained safety distances, while highlighting control delays and inertia as areas for improvement. The work advances human–drone interaction by combining biomimetic flight with explicit safety considerations and gesture-driven control, paving the way for more natural, contact-based drone applications in constrained environments.

Abstract

Flapping-wing drones have attracted significant attention due to their biomimetic flight. They are considered more human-friendly due to their characteristics such as low noise and flexible wings, making them suitable for human-drone interactions. However, few studies have explored the practical interaction between humans and flapping-wing drones. On establishing a physical interaction system with flapping-wing drones, we can acquire inspirations from falconers who guide birds of prey to land on their arms. This interaction interprets the human body as a dynamic landing platform, which can be utilized in various scenarios such as crowded or spatially constrained environments. Thus, in this study, we propose a falconry-like interaction system in which a flapping-wing drone performs a palm landing motion on a human hand. To achieve a safe approach toward humans, we design a trajectory planning method that considers both physical and psychological factors of the human safety such as the drone's velocity and distance from the user. We use a commercial flapping platform with our implemented motion planning and conduct experiments to evaluate the palm landing performance and safety. The results demonstrate that our approach enables safe and smooth hand landing interactions. To the best of our knowledge, it is the first time to achieve a contact-based interaction between flapping-wing drones and humans.

Falconry-like palm landing by a flapping-wing drone based on the human gesture interaction and distance-aware flight planning

TL;DR

The paper tackles safe and intuitive physical interaction between humans and flapping-wing drones by drawing inspiration from falconry, enabling a palm landing on a human hand. It introduces a simple human-gesture interface and a distance- and psychology-aware trajectory planner, underpinned by a dynamic flapping-wing drone model and a four-domain approach strategy. Real-world experiments using a motion-capture–drone testbed demonstrate feasible palm landing with measurable tracking accuracy (), controlled timing, and maintained safety distances, while highlighting control delays and inertia as areas for improvement. The work advances human–drone interaction by combining biomimetic flight with explicit safety considerations and gesture-driven control, paving the way for more natural, contact-based drone applications in constrained environments.

Abstract

Flapping-wing drones have attracted significant attention due to their biomimetic flight. They are considered more human-friendly due to their characteristics such as low noise and flexible wings, making them suitable for human-drone interactions. However, few studies have explored the practical interaction between humans and flapping-wing drones. On establishing a physical interaction system with flapping-wing drones, we can acquire inspirations from falconers who guide birds of prey to land on their arms. This interaction interprets the human body as a dynamic landing platform, which can be utilized in various scenarios such as crowded or spatially constrained environments. Thus, in this study, we propose a falconry-like interaction system in which a flapping-wing drone performs a palm landing motion on a human hand. To achieve a safe approach toward humans, we design a trajectory planning method that considers both physical and psychological factors of the human safety such as the drone's velocity and distance from the user. We use a commercial flapping platform with our implemented motion planning and conduct experiments to evaluate the palm landing performance and safety. The results demonstrate that our approach enables safe and smooth hand landing interactions. To the best of our knowledge, it is the first time to achieve a contact-based interaction between flapping-wing drones and humans.

Paper Structure

This paper contains 17 sections, 7 equations, 14 figures.

Figures (14)

  • Figure 1: Proposed falconry-like interaction system which takes human safety factors into account. The flapping-wing drone approaches a human body following a planned path and performs a landing motion on a human palm. The human gesture system detects the position of the palm and the chest, and enables the user to stop the drone by bending the arm.
  • Figure 2: The mechanical structure model of a tailless aerial robotic flapper. The upper part shows the drone in the from above, and the lower part shows the drone in the front view. It has motors for thrust (m1, m2), a motor for pitch control (m3), and a motor for yaw control (m4). The wings make flapping motion while m1 and m2 is rotating.
  • Figure 3: Human gestures for the falconry-like interaction system. (a) Bending the arm to stop the drone. (b) Stretching the arm to start the approaching motion.
  • Figure 6: Proposed motion planning for flapping drone approach. It has 4 domains which are separated by the distance from the user. Different strategies are applied to drone motion in different domains.
  • Figure 7: Overall system configuration.
  • ...and 9 more figures