Summary
Path planning is a problem much studied in the context of artificial intelligence, with many applications in robotics, intelligent transport systems, and computer games. In this paper, we introduce the term constructive path planning to describe the use of path planning to create geometric models. The basic algorithm involves finding least-cost paths through a randomly weighted regular lattice. The resulting paths have characteristics in common with plants and other natural phenomena; visible structure is imposed on the randomness by the optimization process. This paper explores different arrangements of graph weights and shows the effectiveness of the technique in two detailed examples of procedural models, one for elm trees and one for lightning.
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Xu, L., Mould, D. (2009). Constructive Path Planning for Natural Phenomena Modeling. In: Plemenos, D., Miaoulis, G. (eds) Artificial Intelligence Techniques for Computer Graphics. Studies in Computational Intelligence, vol 159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85128-8_6
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DOI: https://doi.org/10.1007/978-3-540-85128-8_6
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