Personal information

Websites & social links

github profile
personal blog

Keywords

robot vision, mapping, 3D reconstruction, optimization, machine learning

Countries

Sweden

Activities

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Employment (3)

Electronic Arts Inc: Stockholm, SE

2020-12 to present | Software Engineer (DICE, tools development)
Employment
Source: Self-asserted source
Daniel Ricão Canelhas

Univrses AB: Stockholm, SE

2017-08 to 2020-12 | Computer Vision Scientist (R&D)
Employment
Source: Self-asserted source
Daniel Ricão Canelhas

Alstom Grid: Västerås, Västmanland, SE

2007-04 to 2012-06 | Mechanical Design Engineer (High-voltage T&D Substations)
Employment
Source: Self-asserted source
Daniel Ricão Canelhas

Education and qualifications (3)

Örebro University: Örebro, SE

2012 to 2017 | Doctor of Philosophy in Computer Science (AASS)
Education
Source: Self-asserted source
Daniel Ricão Canelhas

Örebro universitet Akademin för Naturvetenskap och Teknik: Orebro, SE

2010-08 to 2012-06 | M.Sc Robotics and Intelligent Systems (AASS)
Education
Source: Self-asserted source
Daniel Ricão Canelhas

Pontifícia Universidade Católica de Minas Gerais: Belo Horizonte, MG, BR

2001-02 to 2006-12 | B.Sc Mechanical Engineering with emphasis on Mechatronics (IPUC)
Education
Source: Self-asserted source
Daniel Ricão Canelhas

Professional activities (1)

Imperial College London: London, Westminster, GB

2013-04 to 2013-07 | Grad student - guest scholarship (Robot Vision Lab at the Department of Computing)
Invited position
Source: Self-asserted source
Daniel Ricão Canelhas

Works (9)

A Survey of Voxel Interpolation Methods and an Evaluation of Their Impact on Volumetric Map-Based Visual Odometry

2018 IEEE International Conference on Robotics and Automation (ICRA)
2018-05 | Conference paper
DOI: 10.1109/icra.2018.8461227
ISBN: 9781538630815
Source: Self-asserted source
Daniel Ricão Canelhas

Truncated Signed Distance Fields Applied To Robotics

2017 | Dissertation or Thesis
Part of ISBN: 978-91-7529-209-0
Source: Self-asserted source
Daniel Ricão Canelhas

Compressed Voxel-Based Mapping Using Unsupervised Learning

Robotics
2017-06 | Journal article
DOI: 10.3390/robotics6030015
Source: check_circle
Multidisciplinary Digital Publishing Institute

From Feature Detection in Truncated Signed Distance Fields to Sparse Stable Scene Graphs

IEEE Robotics and Automation Letters
2016 | Journal article
Source: Self-asserted source
Daniel Ricão Canelhas

No more heavy lifting: Robotic solutions to the container unloading problem

Robotics and Automation Magazine
2016 | Journal article
Source: Self-asserted source
Daniel Ricão Canelhas

Robotic Solutions to the Container-Unloading Problem

2016 | Journal article
Source: Self-asserted source
Daniel Ricão Canelhas

Improved local shape feature stability through dense model tracking

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
2013 | Conference paper
Source: Self-asserted source
Daniel Ricão Canelhas

SDF Tracker: A parallel algorithm for on-line pose estimation and scene reconstruction from depth images

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
2013 | Conference paper
Source: Self-asserted source
Daniel Ricão Canelhas

Scene Representation, Registration and Object Detection in a Truncated Signed Distance Function Representation of 3D Space

2012-06 | Dissertation or Thesis
URN:

urn:nbn:se:oru:diva-25594
Source: Self-asserted source
Daniel Ricão Canelhas
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