  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 and 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 (6-DOF) pose
estimation but also providing dynamical characteristics of the flight platform
for external force perception or dynamics-aided estimation. The VID dataset
contains hardware synchronized imagery and inertial measurements, with accurate
ground truth trajectories for evaluating common visual-inertial estimators.
Moreover, the proposed dataset highlights rotor speed and motor current
measurements, control 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 in the real world for pose and external force evaluation.
The dataset: https://github.com/ZJU-FAST-Lab/VID-Dataset and related files:
https://github.com/ZJU-FAST-Lab/VID-Flight-Platform are open-sourced.
