2026-04-03T23:42:01Zhttps://recercat.cat/oai/request

oai:recercat.cat:10256/21622024-05-22T09:46:06Zcom_2072_452955com_2072_2054col_2072_452957

00925njm 22002777a 4500 dc Carreras Pérez, Marc author Batlle i Grabulosa, Joan author Ridao Rodríguez, Pere author 2001 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 http://hdl.handle.net/10256/2162 Robots mòbils Robots submarins Vehicles submergibles Mobile robots Submersibles Underwater robots Hybrid coordination of reinforcement learning-based behaviors for AUV control