Probabilistic Decision Making of Robot Behavior Based on Bayesian Network
نویسندگان
چکیده
This paper presents a technique for an intelligent software robot (sobot) Rity to behave in uncertain environment in an appropriate manner. The intelligence of a robot is necessary to infer an appropriate behavior when various sensor data (stimuli) exist simultaneously and a specific behavior can be decided by a behavior controller. There could be various methods to build a behavior controller. Here we make behavior scenarios to set priorities among behaviors and use sobot Rity and Bayesian network to model an intelligent behavior controller and to make a certainty factor of behavior candidates by probability computation. Simulation results show that Rity behaves well following behavior scenarios with the proposed architecture.
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