Autonomous Perching Drones: Design, Perception and Control
G.M. Strunck (TU Delft - Mechanical Engineering)
S. Hamaza – Graduation committee member (TU Delft - Control & Simulation)
Javier Alonso-Mora – Graduation committee member (TU Delft - Learning & Autonomous Control)
M. Popovic – Graduation committee member (TU Delft - Control & Simulation)
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Abstract
Autonomous perching enables micro aerial vehicles (MAVs) to act as quiet, non-intrusive sensing nodes for ecological monitoring and habitat assessment. We present a 1.2[kg] quadrotor designed for selective branch perching in natural environments, aiming to extend operational endurance and enable elevated observation in dense vegetation.
We achieve autonomous quadrotor perching by addressing challenges in perception, planning, mechanical design and control.
Our system, equipped with a stereo vision pipeline and a lightweight top-mounted actuated gripper arm, demonstrates fully autonomous perching across a wide range of branch and stem orientations - from horizontal to vertical - even in cluttered, near-natural forest scenes. In controlled laboratory trials, the MAV performs a 360° scan to identify candidate perches, verifies them with depth-based checks, executes a bottom-up, orthogonal approach, and supports repeated take-off and re-perching at different branches.
This is the first time the complete pipeline of design, perception, planning, and control is addressed for perching drones. With that, our work lays the foundation for future deployment in ecological monitoring and restoration missions, where minimally invasive aerial observation could benefit remote or sensitive ecosystems.