Rule-Based Control and Communication of Humanoid Robots Using High-Level Petri Nets

Abstract

Rule-based Control of Humanoid Robots using Image Realization Algorithms Petri nets are used to graphically model various sequences of actions which can be representative of real-world situations. Different variations of Petri nets have been developed. Implementing fuzzy logic creates a Fuzzy Petri net and implementing time into transitions creates a Timed Petri net. Both types of Petri nets allow more robust models to be developed. Using the NAO humanoid robots the tasks of stabilization and communication are being established. Algorithms are being developed to accomplish each of these tasks using real-time image processing and recognition. Petri nets models were used to simulate the tasks which could be implemented using the NAO robot.