9 papers
Self Supervised Learning from Automatically Generated Demonstrations for Visual Robotic Manipulation
Andres Rivas, Anselmo R. Cukla, Rodrigo S. Guerra +2
Robotic manipulation often requires object specific programming, manual data annotation, or calibrated perception pipelines, which limits rapid deployment in practical settings. Le…
Reducing Latency in LLM-Based Natural Language Commands Processing for Robot Navigation
Diego Pollini, Bruna V. Guterres, Rodrigo S. Guerra +1
The integration of Large Language Models (LLMs), such as GPT, in industrial robotics enhances operational efficiency and human-robot collaboration. However, the computational compl…
Real-time Robotics Situation Awareness for Accident Prevention in Industry
Juan M. Deniz, Andre S. Kelboucas, Ricardo Bedin Grando
This study explores human-robot interaction (HRI) based on a mobile robot and YOLO to increase real-time situation awareness and prevent accidents in the workplace. Using object se…
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…
CURLing the Dream: Contrastive Representations for World Modeling in Reinforcement Learning
Victor Augusto Kich, Jair Augusto Bottega, Raul Steinmetz +3
In this work, we present Curled-Dreamer, a novel reinforcement learning algorithm that integrates contrastive learning into the DreamerV3 framework to enhance performance in visual…
Kolmogorov-Arnold Network for Online Reinforcement Learning
Victor Augusto Kich, Jair Augusto Bottega, Raul Steinmetz +3
Kolmogorov-Arnold Networks (KANs) have shown potential as an alternative to Multi-Layer Perceptrons (MLPs) in neural networks, providing universal function approximation with fewer…