Relative-pose optimisation for robust and nonlinear control of unmanned aerial manipulators

Abstract

Recently, the complexity of control systems for autonomous Aerial Manipulators (AMs), i.e. Unmanned Aerial Vehicle (UAV) + Robot Manipulator (RM), is growing faster as per our demand of being able to perform more and more complex tasks. In the present work, we go a step forward adding an optimiser to the actual (nonlinear) control strategy, in order to comply with high-level control demands related to safety, accuracy and efficiency of the operational task. The actual strategy combined robust controllers with separate references- for both aerial vehicle and robot manipulator-optimising their shared priorities. Here, we demand the controller to meet an additional feed-forward action, so that the a priori free degree of freedom of the UAV relative-pose reference is optimised in real time according to the aforementioned requirements. In particular, the influence of the UAV relative-pose reference on the capabilities of the AM has been thoroughly analysed, demonstrating among others the benefits of a correct configuration to meet such high-level requirements, while reducing the End-Effector (EE) error, preventing unstability of hazardous situations and increasing the energetic efficiency of the whole system. A complete analysis of realistic simulations on a benchmark AM is reported.