Multi sensor fusion in robot assembly using particle filters

In this paper, we present a new method for sensor fusion in robot assembly. In our approach, model information can be derived automatically from CAD-data. We introduce Force Torque Maps, which are either computed automatically exploiting modern graphical processors or are measured by scanning forces and torques during contact motions. Subsequently, Force Torque Maps are applied as model information during execution of real assembly tasks. Also, computer vision is included by comparing relative poses of features in virtual images with their real relative poses given from measured images. For fusion of these two (or more) different sensors we suggest to use particle filters. Experiments with variations of peg in hole tasks in a real work cell demonstrate our new approach to be very useful for the whole process chain from planning to execution.