Ruben Gomez-Ojeda

Orcid: 0000-0002-5338-1746

According to our database1, Ruben Gomez-Ojeda authored at least 13 papers between 2015 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2020
The UMA-VI dataset: Visual-inertial odometry in low-textured and dynamic illumination environments.
Int. J. Robotics Res., 2020

Improving Visual SLAM in Car-Navigated Urban Environments with Appearance Maps.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

2019
PL-SLAM: A Stereo SLAM System Through the Combination of Points and Line Segments.
IEEE Trans. Robotics, 2019

Automatic Multi-Sensor Extrinsic Calibration For Mobile Robots.
IEEE Robotics Autom. Lett., 2019

2018
Geometric-based Line Segment Tracking for HDR Stereo Sequences.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Learning-Based Image Enhancement for Visual Odometry in Challenging HDR Environments.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017
Appearance-invariant place recognition by discriminatively training a convolutional neural network.
Pattern Recognit. Lett., 2017

PL-SLAM: a Stereo SLAM System through the Combination of Points and Line Segments.
CoRR, 2017

Accurate stereo visual odometry with gamma distributions.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

2016
PL-SVO: Semi-direct Monocular Visual Odometry by combining points and line segments.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Robust stereo visual odometry through a probabilistic combination of points and line segments.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

2015
Training a Convolutional Neural Network for Appearance-Invariant Place Recognition.
CoRR, 2015

Extrinsic calibration of a 2d laser-rangefinder and a camera based on scene corners.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015


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