A decision method for object identification in robotics

摘要

In this paper we propose a method for generating a deterministic classification tree in the Sequential Pattern Recognition problem. At first, features are partitioned and structured in a set of decision rules. Then this set is translated in an optimal decision tree which satisfies a constraint on the maximum probability of misclassification.