  Autonomous Micro Aerial Vehicles (MAVs) have the potential to be employed for
surveillance and monitoring tasks. By perching and staring on one or multiple
locations aerial robots can save energy while concurrently increasing their
overall mission time without actively flying. In this paper, we address the
estimation, planning, and control problems for autonomous perching on inclined
surfaces with small quadrotors using visual and inertial sensing. We focus on
planning and executing of dynamically feasible trajectories to navigate and
perch to a desired target location with on board sensing and computation. Our
planner also supports certain classes of nonlinear global constraints by
leveraging an efficient algorithm that we have mathematically verified. The on
board cameras and IMU are concurrently used for state estimation and to infer
the relative robot/target localization. The proposed solution runs in real-time
on board a limited computational unit. Experimental results validate the
proposed approach by tackling aggressive perching maneuvers with flight
envelopes that include large excursions from the hover position on inclined
surfaces up to 90$^\circ$, angular rates up to 600~deg/s, and accelerations up
to 10m/s^2.
