Pose and Motion Estimation of Free-Flying Objects: Aerodynamics, Constrained Filtering, and Graph-Based Feature Tracking

In this article, we investigate the problem of dynamically estimating the instantaneous position, orientation, velocity, and angular velocity of an arbitrarily shaped object during its free flight based on image frames taken simultaneously by two high-speed cameras. Aerodynamic effects, including drag, lift, and Magnus forces, are modeled to describe the object's flight. Observables are derived from combining dynamics with a camera projection model assuming two-view geometry, via the use of multiple quaternions. The state of the composed system can then be estimated via constrained Kalman filtering, to which a solution is presented for the case of multiple quadratic constraints. To keep track of appearing and disappearing visual features during flight, the estimation algorithm employs a graph matching-based technique to maintain a set of evolving hypotheses through evaluation, pruning, and addition. Experiments conducted over various objects have either provided validation against motions independently estimated using multiple accelerometers, or formed verification by matching flight images against projections based on the state estimates.