ALBERO: Agile Landing on Branches for Environmental Robotics Operations

Drones have been increasingly used in various domains, including ecological monitoring in forests. However, the endurance and noise of drones have limited their deployment to short flight missions above canopies. To address these limitations, we introduce ALBERO: a framework comprising a mechanical solution and an optimal planner to realise agile quadrotor perching on tree branches of steep incline. The gripper features an ultra-fast active mechanism inspired by birds' claws that enables quadrotors to perch swiftly on randomly-oriented tree branches. By perching, the drone can preserve energy for extended periods of time, while silently gathering forest data in the canopy. The intrinsic properties of the gripper allow for extra flexibility in size, surface roughness and shape imperfections of natural perches, such as those found in the wild. The gripper also has good scalability properties and can be easily matched to different drones' sizes. The biggest advantage of this novel design lays in its ability to close reactively and ultra-fast ( $\text{67}\,\text{ms}$ on the large gripper, $\text{42}\,\text{ms}$ on the small gripper), enabling the quadrotor to perform agile perching manoeuvres from different angles and at different approach speeds. ALBERO's software module comprises of a trajectory planning algorithm adapted for branch perching, ensuring that the drone can perch on inclined cylindrical targets from any starting location in the proximity of the branch. These requirements translate in stringent positioning and orientation accuracy, but they enable the drone to land dynamically from a variety of positions within the forest.