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

Aggressive Visual Perching with Quadrotors on Inclined Surfaces