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most citedDouble Deep Reinforcement Learning Techniques for Low Dimensional Sensing Mapless Navigation of Terrestrial Mobile Robots

2 citations · 4 across the 22 of their papers we have counts for

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cs.RO2023

Enhanced Low-Dimensional Sensing Mapless Navigation of Terrestrial Mobile Robots Using Double Deep Reinforcement Learning Techniques

Linda Dotto de Moraes, Victor Augusto Kich, Alisson Henrique Kolling +4

In this study, we present two distinct approaches within the realm of Deep Reinforcement Learning (Deep-RL) aimed at enhancing mapless navigation for a ground-based mobile robot. T…

cs.RO2023

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…

cs.RO2023★ 1 cited

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…

cs.RO2023★ 2 cited

Double Deep Reinforcement Learning Techniques for Low Dimensional Sensing Mapless Navigation of Terrestrial Mobile Robots

Linda Dotto de Moraes, Victor Augusto Kich, Alisson Henrique Kolling +6

In this work, we present two Deep Reinforcement Learning (Deep-RL) approaches to enhance the problem of mapless navigation for a terrestrial mobile robot. Our methodology focus on…