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Real-Time Decision Making of Autonomous Robot under Uncertainty of State Estimation by Using Particle Filter and Q-MDP Value Method

Ryuichi Ueda, Tamio Arai

Year
2007
Citations
2
Access
Open access

Abstract

We propose the real-time Q-MDP value method for decision making of a robot under uncertain state recognition. When the computation result of a control problem is known on the assumption that recognition is certain, the original Q-MDP value method decides an appropriate action based on uncertain recognition. The method is not suitable for real-time decision making due to the complexity of probability calculation. In the real-time Q-MDP value method, a particle filter that is utilized for state estimation is directly used for the probability calculation. The proposed method can make it possible to execute the Q-MDP value method in real-time. The proposed method is applied to total behavior of a goalkeeper for robot soccer competition. Experiments and actual games have suggested that this method can decide actions effectively according as uncertain result of state estimation.

Keywords

Particle filterRobotComputer scienceValue (mathematics)State (computer science)Filter (signal processing)ComputationArtificial intelligenceKalman filterControl (management)

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