Contact state recognition and planning of robotic assembly

To deal with the contact state recognizing and planning of robotic assembly, a fuzzy Petri-net based reasoning model is presented in this paper. First, multiple types of sensor signals are converted to the same form of real values using fuzzification method. Second, weight factors and priorities of sensor signals are introduced to solve the contradictions between the number, high degree of truth and important degree of input conditions. Third, dynamic information of assembly is deeply studied to strengthen the ability of the model to converge. Finally, a planar peg-in-the-hole example is given to illustrate the reasonability and feasibility of the model