1 citations · 1 across the 5 of their papers we have counts for
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Cross domain Persistent Monitoring for Hybrid Aerial Underwater Vehicles
Ricardo B. Grando, Victor A. Kich, Alisson H. Kolling +3
Hybrid Unmanned Aerial Underwater Vehicles (HUAUVs) have emerged as platforms capable of operating in both aerial and underwater environments, enabling applications such as inspect…
Improving Generalization in Aerial and Terrestrial Mobile Robots Control Through Delayed Policy Learning
Ricardo B. Grando, Raul Steinmetz, Victor A. Kich +7
Deep Reinforcement Learning (DRL) has emerged as a promising approach to enhancing motion control and decision-making through a wide range of robotic applications. While prior rese…
DoCRL: Double Critic Deep Reinforcement Learning for Mapless Navigation of a Hybrid Aerial Underwater Vehicle with Medium Transition
Ricardo B. Grando, Junior C. de Jesus, Victor A. Kich +3
Deep Reinforcement Learning (Deep-RL) techniques for motion control have been continuously used to deal with decision-making problems for a wide variety of robots. Previous works s…
Mapless Navigation of a Hybrid Aerial Underwater Vehicle with Deep Reinforcement Learning Through Environmental Generalization
Ricardo B. Grando, Junior C. de Jesus, Victor A. Kich +3
Previous works showed that Deep-RL can be applied to perform mapless navigation, including the medium transition of Hybrid Unmanned Aerial Underwater Vehicles (HUAUVs). This paper…
Deterministic and Stochastic Analysis of Deep Reinforcement Learning for Low Dimensional Sensing-based Navigation of Mobile Robots
Ricardo B. Grando, Junior C. de Jesus, Victor A. Kich +3
Deterministic and Stochastic techniques in Deep Reinforcement Learning (Deep-RL) have become a promising solution to improve motion control and the decision-making tasks for a wide…