1 citations · 1 across the 7 of their papers we have counts for
7 papers
Parallel Distributional Deep Reinforcement Learning for Mapless Navigation of Terrestrial Mobile Robots
Victor Augusto Kich, Alisson Henrique Kolling, Junior Costa de Jesus +8
This paper introduces novel deep reinforcement learning (Deep-RL) techniques using parallel distributional actor-critic networks for navigating terrestrial mobile robots. Our appro…
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…
Parallel Distributional Prioritized Deep Reinforcement Learning for Unmanned Aerial Vehicles
Alisson Henrique Kolling, Victor Augusto Kich, Junior Costa de Jesus +4
This work presents a study on parallel and distributional deep reinforcement learning applied to the mapless navigation of UAVs. For this, we developed an approach based on the Sof…
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…
Virtual Reality Platform to Develop and Test Applications on Human-Robot Social Interaction
Jair A. Bottega, Raul Steinmetz, Alisson H. Kolling +4
Robotics simulation has been an integral part of research and development in the robotics area. The simulation eliminates the possibility of harm to sensors, motors, and the physic…
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…