Precise Assembly of 3D Truss Structures Using EKF-Based Error Prediction and Correction

We describe a method to construct precise truss structures from non-precise commodity parts. Trusses with precision in the order of micrometers, such as the truss of a space telescope, can be accomplished with precisely machined truss connection systems. This approach is expensive, heavy, and prone to failure, e.g., when a single element is lost. In the past, we have proposed a novel concept in which non-precise commodity parts can be aligned using precise jigging robots and then welded in place. Even when using highly precise sensors and actuators, this approach can still lead to errors due to thermal expansion and structural deformation. In this paper, we describe and experimentally evaluate an EKF-based SLAM approach that allows a team of intelligent precision jigging robots (IPJR) to maintain a common estimate of the structure’s pose, improve this estimate during loop closures in the construction process, and uses this estimate to correct for errors during construction. We also show that attaching a new node to the assembly site with the lowest uncertainty significantly increases accuracy.