A constraint-satisfaction approach for 3D vision/touch-based object recognition

We present a technique for recognizing polyhedral objects by integrating visual and tactile data. The problem is formulated as a constraint-satisfaction problem (CSP) to provide a unified framework for integrating different types of sensory data. To make use of the scene perceptual structures early in the recognition process, we enforce local consistency of the CSP. The process of local-consistency enforcing (LCE) reduces the correspondence uncertainty between scene and model features, which can lead to significant reductions in the computational load on subsequent recognition modules. LCE can also eliminate many erroneous model objects efficiently, without explicitly generating or verifying any object/pose hypotheses