Improving Dynamics of an Aerial Manipulator with Elastic Suspension Using Nonlinear Model Predictive Control

Abstract

Aerial manipulation increases significantly the workspace size of robotic manipulators. However, aerial manipulation suffers from a lack of autonomy due to limited embedded energy. The Aerial Manipulator with Elastic Suspension (AMES) is designed to cope with this issue. It is an omnidirectional aerial vehicle equipped with a gripper and suspended under a robotic carrier by a spring for gravity compensation. In this paper, the AMES is controlled with a nonlinear model predictive controller (NMPC). To eliminate the steady-state errors, an observer based on a model of the AMES augmented with constant disturbances is implemented in conjunction with the NMPC controller. Experiments illustrate the efficiency of the NMPC by comparing it to a computed torque controller.