activity
20172026
most citedUsing Convolutional Neural Networks in Robots with Limited Computational Resources: Detecting NAO Robots while Playing Soccer

1 citations · 1 across the 5 of their papers we have counts for

collaborators

11 papers

cs.RO2026

A real-time RGB-D perception pipeline for autonomous impact hammers in mining: self-filtering, rock segmentation and rock-breaking poses generation

Martín Gallegos, Francisco Leiva, Patricio Loncomilla +2

Impact hammers, also known as rock-breakers, are essential machines in mining operations, where they perform secondary reduction. In underground mining, these machines are typicall…

cs.LG2021

Learning to Play Soccer From Scratch: Sample-Efficient Emergent Coordination through Curriculum-Learning and Competition

Pavan Samtani, Francisco Leiva, Javier Ruiz-del-Solar

This work proposes a scheme that allows learning complex multi-agent behaviors in a sample efficient manner, applied to 2v2 soccer. The problem is formulated as a Markov game, and…

cs.RO2019

Continuous Control for High-Dimensional State Spaces: An Interactive Learning Approach

Rodrigo Pérez-Dattari, Carlos Celemin, Javier Ruiz-del-Solar +1

Deep Reinforcement Learning (DRL) has become a powerful methodology to solve complex decision-making problems. However, DRL has several limitations when used in real-world problems…

cs.CV2018

Playing Soccer without Colors in the SPL: A Convolutional Neural Network Approach

Francisco Leiva, Nicolás Cruz, Ignacio Bugueño +1

The goal of this paper is to propose a vision system for humanoid robotic soccer that does not use any color information. The main features of this system are: (i) real-time operat…

cs.RO2018

Towards Long-Term Memory for Social Robots: Proposing a New Challenge for the RoboCup@Home League

Matías Pavez, Javier Ruiz del Solar, Victoria Amo +1

Long-term memory is essential to feel like a continuous being, and to be able to interact/communicate coherently. Social robots need long-term memories in order to establish long-t…

cs.RO2018

Near Real-Time Object Recognition for Pepper based on Deep Neural Networks Running on a Backpack

Esteban Reyes, Cristopher Gómez, Esteban Norambuena +1

The main goal of the paper is to provide Pepper with a near real-time object recognition system based on deep neural networks. The proposed system is based on YOLO (You Only Look O…