Generating visual sensing strategies in assembly tasks

Abstract

It is generally very difficult, if not impossible, for a robot to perform fine manipulation tasks without the benefit of some form of sensory feedback during actual task execution. As a result, sensing planning is an important component in assembly task planning. This paper describes a method of generating visual sensing strategies based on knowledge of the task to be performed. The generation of the appropriate visual sensing strategy entails knowing what information to extract and where to get it. This is facilitated by the knowledge of the task, which describes how objects are assembled. This knowledge, coupled with known sensor modeling, results in an abstract template of sensing strategy called the sensing task model. By instantiating the appropriate sensing task model at planning time, the sensing strategy is efficiently generated. Our method has been implemented using a laser range finder as the sensor. Experimental results involving typical assembly tasks show the feasibility of the method.