Abstract In this paper, we present a framework for studying folding problems from a motion planning perspective. In particular, all folding objects are modeled as tree-like multilink articulated `robots', where fold positions correspond to joints and areas that cannot fold correspond to links. This formulation allows us to apply recent techniques developed in the robotics motion planning community for articulated objects with many degrees of freedom (many links) to folding problems. An important benefit of this approach is that it not only allows us to study foldability questions, such as, can one object be folded (or unfolded) into another object, but also enables us to study the dynamic folding process itself. The framework proposed here has application in traditional motion planning areas such as automation, teaching through demonstration, animation, and most importantly, presents a different approach to the most profound problem in computational biology: protein struction prediction. Indeed, our preliminary experimental results with traditional paper crafts (e.g., box folding) and a relatively small protein are quite promising
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