  Designing a robot or structure that can fold itself into a target shape is a
process that involves challenges originated from multiple sources. For example,
the designer of rigid self-folding robots must consider foldability from
geometric and kinematic aspects to avoid self-intersection and undesired
deformations. Recent works have shown success in estimating foldability of a
design using robot motion planners. However, many foldable structures are
actuated using physically coupled reactions (i.e., folding originated from
thermal, chemical, or electromagnetic loads). Therefore, a reliable foldability
analysis must consider additional constraints that resulted from these critical
phenomena. This work investigates the idea of efficiently incorporating
computationally expensive physics simulation within the folding motion planner
to provide a better estimation of the foldability. In this paper, we will use
laser forming origami as an example to demonstrate the benefits of considering
the properties beyond geometry. We show that the design produced by the
proposed method can be folded more efficiently.
