  Recently, the community has witnessed numerous datasets built for developing
and testing state estimators. However, for some applications such as aerial
transportation or search-and-rescue, the contact force or other disturbance
must be perceived for robust planning robust control, which is beyond the
capacity of these datasets. This paper introduces a
Visual-Inertial-Dynamical(VID) dataset, not only focusing on traditional six
degrees of freedom (6DOF) pose estimation but also providing dynamical
characteristics of the flight platform for external force perception or
dynamics-aided estimation. The VID dataset contains hard synchronized imagery
and inertial measurements, with accurate ground truth trajectories for
evaluating common visual-inertial estimators. Moreover, the proposed dataset
highlights the measurements of rotor speed and motor current, dynamical inputs,
and ground truth 6-axis force data to evaluate external force estimation. To
the best of our knowledge, the proposed VID dataset is the first public dataset
containing visual-inertial and complete dynamical information for pose and
external force evaluation. The dataset and related open source files are
available at \url{https://github.com/ZJU-FAST-Lab/VID-Dataset}.
