Method and apparatus for processing information and a method and apparatus for executing a work instruction

A pattern recognition method, comprising:

• acquiring state information of an object;
• providing a first neural network to transform the state information into a first intermediate representation;
• providing a second neural network to transform input knowledge information of the object into a second intermediate representation;
• fusing said first intermediate representation and said second intermediate representation to produce a common intermediate representation of the object, and
• training said first and second neural networks by applying a teacher signal derived from said common intermediate representation;
• providing said trained first neural network to transform the state information of the object in to a third intermediate representation;
• providing said trained second neural network to transform the input knowledge information to be compared to said state information of the object into a fourth intermediate representation;
• and
• comparing said third intermediate representation with said fourth intermediate representation to determine whether a concept represented by said state information of the object and a concept represented by said knowledge information to be compared with said state information of said object are consistent with each other.

A method of executing a work instruction, comprising steps of:

• teaching a neural network to recognize an object, including the steps of:
• acquiring state information of the object via a detection unit;
• providing a first neural network to transform the state information of the object into a first intermediate representation,
• providing a second neural network to transform input knowledge information of the object into a second intermediate representation,
• fusing said first intermediate representation and said second intermediate representation to produce a common intermediate representation of the object, and
• training said first and second neural networks by applying a teacher signal derived from said common intermediate representation;
• inputting a work instruction;
• interpreting said input work instruction to identify separate units of information;
• retrieving knowledge information concerning a concept represented by at least one of the separate units of information;
• allowing said trained second neural network to transform said knowledge information into a fourth intermediate representation;
• allowing said trained first neural network to transform said state information of an object into a third intermediate representation;
• and comparing said third intermediate representation with said fourth intermediate representation to determine whether a concept represented by said state information of the object and a concept represented by said knowledge information are consistent with each other.

A pattern recognition apparatus, comprising:

• a first neural network, for transforming input state information into a first intermediate representation;
• a second neural network for transforming input knowledge information into a second intermediate representation;
• a fusing means for fusing said first intermediate representation and said second intermediate representation, applying said common intermediate representation as a teacher signal to said first and second neural networks, and thus training said first and second neural networks;
• and
• a comparing means for comparing a third intermediate representation which is transformed from state information of an object by said trained first neural network with a fourth intermediate representation which is transformed from knowledge information of an object to be detected by said trained second neural network, and determining whether or not the object and the object to be determined are consistent with each other.