Sensory integration in a neural network‐based robot safety system

Abstract

Abstract This article presents an architecture for a real‐time robot safety system for advanced manufacturing environments. The system is based on neural network technology, and contains the neural network detection unit and the neural network decision unit implemented at the intermediate and high level of processing, respectively. A new, computationally efficient methodology for sensory fusion at the intermediate level in the dynamic robot cell environment is also proposed. In particular, the neural network detection unit is used to combine basic probability mass functions encoded in certainty grids (local maps) into one final map of the robot environment containing potential collision zones with the human operator. The map produced by the neural network detection unit along with other information will be utilized by the neural network decision unit to produce appropriate robot safety decisions. The results of initial computer simulation indicate that the proposed approach can be very useful for design of robot safety in advanced manufacturing environments. @ 1995 John Wiley & Sons, Inc.