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We present a method for reconstructing 3D models of tree branch structure from laser range data. Our approach is probabilistic, and uses a generative model of a tree to guide an iterative reconstruction process. Our goal is to recover parameters such as branch locations, angles, radii, and lengths, as well as connectivity information between branches. These parameters can then be fed into functional-structural plant models to study the relationships between the structure of a plant, itsdoi:10.1109/robot.2009.5152684 dblp:conf/icra/BinneyS09 fatcat:rqgrazs6izddha3hapwlly23iy