A strategy for recognizing and locating three-dimensional objects in range data is presented. The strategy combines information derived from models of the objects and edges and surfaces detected in the data to efficiently match objects. Given a set of objects to be found, the set of object features are partitioned into subsets having similar intrinsic properties. An ordered tree of features to be considered is set up for each subset. These search trees are designed to maximize the use of the information as it is obtained and minimize the time required to recognize objects. A detailed example of this approach being used to recognize moderately complex castings in a jumble is presented.