activity
20172026
most citedA Survey on Deep Learning Methods for Robot Vision

50 citations · 64 across the 12 of their papers we have counts for

collaborators
Showing 2018Show all

6 papers · 1 filter

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★ 1 cited

Visual SLAM-based Localization and Navigation for Service Robots: The Pepper Case

Cristopher Gómez, Matías Mattamala, Tim Resink +1

We propose a Visual-SLAM based localization and navigation system for service robots. Our system is built on top of the ORB-SLAM monocular system but extended by the inclusion of w…

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…

cs.LG2018

Interactive Learning with Corrective Feedback for Policies based on Deep Neural Networks

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

Deep Reinforcement Learning (DRL) has become a powerful strategy to solve complex decision making problems based on Deep Neural Networks (DNNs). However, it is highly data demandin…

cs.CV2018★ 50 cited

A Survey on Deep Learning Methods for Robot Vision

Javier Ruiz-del-Solar, Patricio Loncomilla, Naiomi Soto

Deep learning has allowed a paradigm shift in pattern recognition, from using hand-crafted features together with statistical classifiers to using general-purpose learning procedur…