Marvin Chancán

mchancanl at

I am completing a Ph.D. in electrical engineering and robotics at Queensland University of Technology, Australia, advised by Michael Milford.

Previously, I received a B.Sc. in mechatronics engineering (1st in my class) from UNI in 2009, and an M.Sc. in mechatronics systems from PUC-Rio in 2012. I also worked in the automation and IT industries for over 6 years in several countries of The Americas and Europe.

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During my PhD, I focused on the intersection between deep learning, computer vision, neuroscience, and reinforcement learning for motion-and-vision based localization and navigation tasks in the context of mobile robots and autonomous vehicles. Specifically, I studied biological neural architectures underlying these complex tasks in insect and rat mammalian brains, and developed novel high-performance and robust neural network models that were shown to be orders of magnitude faster and smaller than classical methods, while setting new state-of-the-art performance metric standards with very high throughput and low latency. My research papers have been published at top-tier machine learning and robotics conferences/journals such as NeurIPS, RA-L, ICRA, and RSS.



Sequential Place Learning: Heuristic-Free High-Performance Long-Term Place Recognition
Marvin Chancán, Michael Milford
arXiv:2103.02074, March 2021
Project page | ArXiv | Codebase
MVP: Unified Motion and Visual Self-Supervised Learning for Large-Scale Robotic Navigation
Marvin Chancán, Michael Milford
arXiv:2003.00667, March 2020
Project page | ArXiv


DeepSeqSLAM: A Trainable CNN+RNN for Joint Global Description and Sequence-based Place Recognition
Marvin Chancán, Michael Milford
Machine Learning for Autonomous Driving Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS 2020)
Project page | Video | Code
Robot Perception enables Complex Navigation Behavior via Self-Supervised Learning
Marvin Chancán, Michael Milford
Self-Supervised Robot Learning Workshop at the Robotics: Science and Systems XVI (RSS 2020)
Project page | Video | ArXiv
CityLearn: Diverse Real-World Environments for Sample-Efficient Navigation Policy Learning
Marvin Chancán, Michael Milford
IEEE International Conference on Robotics and Automation (ICRA 2020)
Project page | Video | Code
A Hybrid Compact Neural Architecture for Visual Place Recognition
Marvin Chancán, Luis Hernandez-Nunez, A. Narendra, Andrew B. Barron, Michael Milford
IEEE Robotics and Automation Letters (RA-L)
Presented at ICRA 2020
Project page | Video | Code

Research Experience


Honors, Awards and Scholarships

  • 2021 HDR Internship from QUT.
  • 2020 High Achiever HDR Award for high quality research outputs from QUT.
  • 2018 Full President of the Republic Scholarship for a PhD degree at QUT.
  • 2017 Full Huiracocha PhD Scholarship from PUCP (declined).
  • 2010 Full Master's degree Scholarship from PUC-Rio.
  • 2009 Graduated First in Class from UNI.
  • 2008 Academic Honors Diploma for best performance in BSc class.
  • 2005 Admitted in the top 2% (~2000 applicants) at UNI (top national science & engineering university).

Copyright 2005-2021 © Marvin Chancán