Structure and Process: Learning of Visual Models and Construction Plans for Complex Objects

Abstract

Supervising robotic assembly of multi-functional objects by means of a computer vision system requires components to identify assembly operations and to recognize feasible assemblies of single objects. Thus, the structure of complex objects as well as their construction processes are of interest. If the results of both components should be consistent there have to be common models providing knowledge about the intended application. However, if the assembly system should handle not only exactly specified tasks it is rather impossible to model every possible assembly or action explicitly. The fusion of a flexible dynamic model for assemblies and a monitor for the construction process enables reliable and efficient learning and supervision. As an example, the construction of objects by aggregating wooden toy pieces is used. The system also integrates a natural speech dialog module, which provides the overall communication strategy and additionally supports decisions in the case of ambiguities and uncertainty.KeywordsBayesian NetworkObject RecognitionObject ClassComplex ObjectAssembly PlanThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.