Factor Graph Modeling of Rigid‐body Dynamics for Localization, Mapping, and Parameter Estimation of a Spinning Object in Space

This paper presents a new approach for solving the simultaneous localization and mapping problem for inspecting an unknown and uncooperative object that is spinning about an arbitrary axis in space. This approach probabilistically models the six degree-of-freedom rigid-body dynamics in a factor graph formulation. Using the incremental smoothing and mapping system, this method estimates a feature-based map of the target object, as well as this object's position, orientation, linear velocity, angular velocity, center of mass, principal axes, and ratios of inertia. This solves an important problem for spacecraft proximity operations. Additionally, it provides a generic framework for incorporating rigid-body dynamics that may be applied to a number of other terrestrial-based applications. To evaluate this approach, the Synchronized Position Hold Engage Reorient Experimental Satellites SPHERES were used as a testbed within the microgravity environment of the International Space Station. The SPHERES satellites, using body-mounted stereo cameras, captured a dataset of a target object that was spinning at ten rotations per minute about its unstable, intermediate axis. This dataset was used to experimentally evaluate the approach described in this paper, and it showed that it was able to estimate a geometric map and the position, orientation, linear and angular velocities, center of mass, and ratios of inertia of the target object.