Robust Partitioned Visual Servoing for Aerial Manipulation Utilizing Controllable-space Image Planning and Adaptive Image Representation

In the pursuit of object retrieval using an aerial manipulator, developing robust visual servoing techniques in the presence of projection and motion model uncertainties is paramount. This paper proposes a novel approach to conducting image-space planning within the controllable-space of the aerial manipulator. Our new strategy resolves the inherent challenge of adhering to a piecewise linear camera trajectory which is infeasible for an aerial manipulator due to the platform’s underactuation and presence of secondary tasks for visual servoing. Through this approach, we introduce center of gravity alignment and camera orientation potential fields without relying on specific degrees of freedom from the arm. Moreover, we introduce a new approach that utilizes an image-resolution scaling technique involving an adaptive virtual camera focal length, leading to a numerically well-conditioned image Jacobian. Our proposed framework maintains robustness to the uncertainty in the intrinsic parameters of the camera. We substantiate the efficacy of our methodology through experiments conducted in a realistic physics-based simulation environment.