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Pedro F. Proença

Assistant Professor

FCT - Universidade NOVA de Lisboa

About me

Pedro Proença (English pronunciation: Peh-dru Pru-ensuh) is a roboticist, computer vision researcher. He was previously an engineer at NASA-JPL, where he developed perception and state estimation software for Moon rovers and future Mars Helicopter. Most notably, he lead the development of the traversability mapping module for the CADRE Flight mission and its testing from simulation to autonomous driving on flight modules. He then worked in a few tech startups before joining FCT-NOVA.

His PhD was on Probabilistic Visual Odometry using RGB-D and Geometric primitives. Most of his research is in modelling uncertainty and using multiple view geometry, deep learning and computer graphics to solve robotics and computer vision problems. However, He is generally interested in all aspects of robot autonomy.

News

• 2025-12-01 Joined FCT-NOVA as an Assistant Professor specialized in AI
• 2025-07-01 Joined Tekever UAS 🦄 Computer Vision group
• 2025-10-23 New paper accepted to Field Robotics on Mars Ingenuity Autonomy
• 2024-03-02 New paper on our CADRE multi-agent autonomy software ready for the 🌙
• 2023-01-01 JPL Team Award for CADRE GNC Team
• 2022-05-23 ICRA 2022 Outstanding Deployed Systems Paper Finalist

Education

• PhD in Computer Vision, 2018

  University of Surrey

• MSc in Telecommunications and Computer Science, 2013

  ISCTE - Instituto Universitário de Lisboa

• BSc in Telecommunications and Computer Science, 2011

  ISCTE - Instituto Universitário de Lisboa

Selected Publications

Lennart Werner, Pedro Proença, Andreas Nuchter and Roland Brockers Covariance Based Terrain Mapping for Autonomous Mobile Robots ICRA, 2024.

Paper

Vaquero et al. EELS: Autonomous snake-like robot with task and motion planning capabilities for ice world exploration Science Robotics, 2024.

Paper Video

Pedro F. Proença, Patrick Spieler, Robert Hewitt, Jeff Delaune. TRADE: Object Tracking with 3D Trajectory and Ground Depth Estimates for UAVs. ICRA, 2023.

Preprint Video

Pedro F. Proença, Jeff Delaune, Roland Brockers . Optimizing Terrain Mapping and Landing Site Detection for Autonomous UAVs. ICRA (Outstanding Deployed Systems Paper Finalist), 2022.

Preprint Video

Pedro F. Proença, Yang Gao . Deep Learning for Spacecraft Pose Estimation from Photorealistic Rendering. ICRA, 2020.

Preprint Code Dataset Video

Pedro F. Proença, Yang Gao . Fast Cylinder and Plane Extraction from Depth Cameras for Visual Odometry. IROS, 2018.

PDF Code Video

Pedro F. Proença, Yang Gao . Probabilistic RGB-D Odometry based on Points, Lines and Planes Under Depth Uncertainty. Robotics and Autonomous Systems, 104, 2018.

Preprint PDF Code Video

Pedro F. Proença, Yang Gao . SPLODE: Semi-Probabilistic Point and Line Odometry with Depth Estimation from RGB-D Camera Motion. IROS, 2017.

PDF Video

Projects

URSO

Photorealistic rendering and deep learning for spacecraft pose estimation

Visual Odometry

Visual Odometry for Man-made Environments

TACO

Trash Annotations in Context Dataset

Target 3D Tracking

Object Tracking and 3D Localization for UAV Target Following

Contact

• pproenxa@gmail.com
• Faculdade de Ciências e Tecnologia, 2829-516 Caparica