A Planning-and-Control Framework for Aerial Manipulation of Articulated Objects

Abstract

While the variety of applications for Aerial Manipulators (AMs) has increased over the last years, they are mostly limited to push-and-slide tasks. More complex manipulations of dynamic environments are poorly addressed and still require handcrafted designs of hardware, control, and trajectory planning. In this letter we focus on the active manipulation of articulated objects with AMs. We present a novel planning and control approach that allows the AM to execute complex interaction maneuvers with as little as possible priors given by the operator. Our framework combines sampling-based predictive control to generate pose trajectories with an impedance controller for compliant behaviours, applied to a fully-actuated flying platform. The framework leverages a physics engine to simulate the dynamics of the platform and the environment in order to find optimal motions to execute manipulation tasks. Experiments on two selected examples of pulling open a door and of turning a valve show the feasibility of the proposed approach.