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Hybrid coordination of reinforcement learning-based behaviors for AUV control
Carreras Pérez, Marc; Batlle i Grabulosa, Joan; Ridao Rodríguez, Pere
This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors
17-05-2010
Robots mòbils
Robots submarins
Vehicles submergibles
Mobile robots
Submersibles
Underwater robots
Tots els drets reservats
Article
IEEE
         

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