1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
Depth-CUPRL: Depth-Imaged Contrastive Unsupervised Prioritized Representations in Reinforcement Learning for Mapless Navigation of Unmanned Aerial Vehicles
Junior Costa de Jesus, Victor Augusto Kich, Alisson Henrique Kolling +3
Reinforcement Learning (RL) has presented an impressive performance in video games through raw pixel imaging and continuous control tasks. However, RL performs poorly with high-dim…
Trajectory Planning for Hybrid Unmanned Aerial Underwater Vehicles with Smooth Media Transition
Pedro Miranda Pinheiro, Armando Alves Neto, Ricardo Bedin Grando +5
In the last decade, a great effort has been employed in the study of Hybrid Unmanned Aerial Underwater Vehicles, robots that can easily fly and dive into the water with different l…
Double Critic Deep Reinforcement Learning for Mapless 3D Navigation of Unmanned Aerial Vehicles
Ricardo Bedin Grando, Junior Costa de Jesus, Victor Augusto Kich +2
This paper presents a novel deep reinforcement learning-based system for 3D mapless navigation for Unmanned Aerial Vehicles (UAVs). Instead of using a image-based sensing approach,…