Visual odometry has made tremendous progress since Mars Exploration Rovers was exploited, but studies focus less on the platform itself. In order to make the state estimation better applied, we focus on details about dynamical modelling of quadrotor, and propose to make the most of all kinds of sensory data to acquire all states of any quadrotor platform. In the series of work, the identification of quadrotor dynamical system is prime, which is between Newton-Euler dynamics and rotor rpm and motor current. Then, an all-states estimator is designed to fuse different kinds of sensor, which leads to more accurate pose estimation and addictive generalized external force estimation without losing real-time and robustness.
VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation, Ziming Ding, Tiankai Yang, Kunyi Zhang, Chao Xu, Fei Gao, submitted to the International Conference on Robotics and Automation (ICRA 2021). [preprint]