In the field of aerial robotics, one of the key challenges is to enable aerial manipulators to exert substantial forces on the environment. Enabling this will allow the technology to perform meaningful tasks airborne, such as cleaning or grinding surfaces. While in contact and applying a large, continuous force, control of the UAV's attitude is a challenge. In this work, we show that a regular (PID-based) attitude controller is incapable of stabilizing aerial manipulators that apply physical contact forces on the environment that are comparable to the UAV's weight. We present a novel control algorithm that uses an LQR-optimized state feedback on the roll and yaw angle while in contact. Experiments on a UAV of 1.5 kg show that the proposed controller is capable of applying a contact force of over 15 N - equal to the UAV's weight - sustained for several minutes.

This paper proposes a semi-autonomous bilateral control architecture for unmanned aerial vehicles. During autonomous navigation, a human operator is allowed to assist the autonomous controller of the vehicle by actively changing its navigation parameters to assist it in critical situations, such as navigating through narrow paths. The overall goal of the controller is to combine the stability and precision of an autonomous control with the cognitive abilities of a human operator, only when strictly required for the accomplishment of a task. The control architecture has been validated through simulations and experiments.