Yan-zeng Gao

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The paper presents an intelligent underwater positioning system for remotely operated vehicle (ROV). We used multi-agents reinforcement learning algorithms based on particle swarm optimization fusing signals from Ultra-Short Baseline (USBL) position sonar and pose sensors, so that the USBL can be accelerated and be in-phase with pose sensors. We proposed(More)
The principal contribution of this paper is designed a general framework for an intelligent control system used in course angle control of remotely operated vehicle (ROV). A control scheme based on reinforcement learning (RL) agent combined with radial basis function (RBF) neural network control algorithm is applied. The effectiveness of the controller is(More)
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