  This paper describes an approach to building a cost-effective and research
grade visual-inertial odometry aided vertical taking-off and landing (VTOL)
platform. We utilize an off-the-shelf visual-inertial sensor, an onboard
computer, and a quadrotor platform that are factory-calibrated and
mass-produced, thereby sharing similar hardware and sensor specifications
(e.g., mass, dimensions, intrinsic and extrinsic of camera-IMU systems, and
signal-to-noise ratio). We then perform a system calibration and identification
enabling the use of our visual-inertial odometry, multi-sensor fusion, and
model predictive control frameworks with the off-the-shelf products. This
implies that we can partially avoid tedious parameter tuning procedures for
building a full system. The complete system is extensively evaluated both
indoors using a motion capture system and outdoors using a laser tracker while
performing hover and step responses, and trajectory following tasks in the
presence of external wind disturbances. We achieve root-mean-square (RMS) pose
errors between a reference and actual trajectories of 0.036m, while performing
hover. We also conduct relatively long distance flight (~180m) experiments on a
farm site and achieve 0.82% drift error of the total distance flight. This
paper conveys the insights we acquired about the platform and sensor module and
returns to the community as open-source code with tutorial documentation.
