Toward image based visual servoing for aerial grasping and perching

This paper addresses the dynamics, control, planning, and visual servoing for micro aerial vehicles to perform high-speed aerial grasping tasks. We draw inspiration from agile, fast-moving birds, such as raptors, that detect, locate, and execute high-speed swoop maneuvers to capture prey. Since these grasping maneuvers are predominantly in the sagittal plane, we consider the planar system and present mathematical models and algorithms for motion planning and control, required to incorporate similar capabilities in quadrotors equipped with a monocular camera. In particular, we develop a dynamical model directly in the image space, show that this is a differentially-flat system with the image features serving as flat outputs, outline a method for generating trajectories directly in the image feature space, develop a geometric visual controller that considers the second order dynamics (in contrast to most visual servoing controllers that assume first order dynamics), and present validation of our methods through both simulations and experiments.