AI helps drones find the perfect branch to perch on

A team led by Alex Dunnett at Imperial College London has published a paper demonstrating a vision-based system that enables drones to autonomously identify the best branch to perch on in a tree. Instead of simply targeting the nearest available branch, the system analyzes each branch's shape and structure using image processing, machine learning, image segmentation, and binary morphology. It assesses branch width, slope (angle to horizontal), and curvature to determine suitability for a tendon-driven grasping claw.

The method was validated on a dataset of over 10,000 urban tree images taken from February to October in subtropical and temperate monsoon climates. For feasible targets (branches thick enough and with sufficient perching space), the system successfully located a perch spot 76% of the time. The researchers note this is a preliminary result and plan to incorporate depth perception and attitude sensors to improve performance. The work could lead to drones that can recharge, survey, or monitor environments by perching in trees.