In nature, landing is far more than simply touching the ground. Many animals can land and remain attached to surfaces that would be extremely difficult for conventional aircraft to use. Flies can attach themselves to ceilings, geckos can stabilize themselves when landing on tree trunks, and bats can settle onto cave ceilings. These abilities allow animals to move, rest and survive in environments filled with irregular surfaces. Flying robots, however, face a very different challenge. Most drones are designed to land on relatively flat, horizontal surfaces. Landing on a vertical wall requires precise control of speed, pitch angle, forces and timing. A small error during the maneuver can cause the robot to fall or become damaged. A new machine-learning-based approach developed by Shen and colleagues aims to change this. The researchers have developed a framework that can predict whether a flying robot equipped with spines will successfully perch on a vertical wall . More importantly, the...