Miloš Prágr
Postgradual student
Computational Robotics Laboratory
Department of Computer Science
Czech Technical University in Prague
Active perception and learning for mobile robot traversability.
― ReSearch ABSTRACT
My research aims to improve the autonomy of mobile robots on long-term, unsupervised missions in outdoor environments. I study traversability, which describes the ease or difficulty experienced by the robot when attempting to traverse a particular terrain. For a mobile robot, understanding its traversability is crucial for its ability to select safe and efficient paths through potentially hazardous environments without supervision. My main focus is on assessing traversability through complex environments, such as terrains whose traversability changes with time or vegetation that appears rigid but can be passed through. To address these challenges, I advocate that traversability models should be adapted incrementally during the deployment, both exploiting the robot's newly accrued experience and actively seeking new information about unknown areas. To this end, my contributions are centered on applying incremental learning and active perception in traversability modeling.
― MEDIA
― EDUCATION
Postgradual student
Topic - Learning Traversability from Mobile Robot Experience
Computational Robotics Laboratory, Department of Computer Science, Czech Technical University in Prague
2018 - present
Master Degree in Computer Vision and Image Processing
Thesis - Terrain Classification and Traversability Assessment from Exteroceptive Data
Faculty of Electrical Engineering, Czech Technical University in Prague
2016 - 2018
Bachelor Degree in Computer and Information Science
Thesis - Scalable Agent Navigation in Crowd Simulation
Faculty of Electrical Engineering, Czech Technical University in Prague
2013 - 2016
― ExpeRIENCE and COmmunity SERVICE
Participating
CTU-CRAS team in V4 Innovation Challenge Day
Debrecen, Hungary
2022
Participating
CTU-CRAS-NORLAB team in DARPA Subterranean Challenge
Virtual Track
2021
Research fellow
Computational Robotics Laboratory, Department of Computer Science, Czech Technical University in Prague
2018 - present
Reviewer
International Journal of Advanced Robotic Systems (IJARS)
Expert Systems With Applications (ESWA)
International Conference on Artificial Neural Networks (ICANN)
Project team member
Mobile Robot Pipeline Inspection for GasNet
2022
Project team member
Powerline Damage Detection from Thermal Imagery for ALEEGO
2021 - 2022
Project team member
Multi-Robot Persitent Monitoring of Dynamic Environments
Czech Science Foundation (GA ČR), Project No. 19-20238S, awarded to Jan Faigl
2019 - 2022
Project team member
Robotic Lifelong Learning of Multi-legged Robot Locomotion Control in Autonomous Data Collection Missions
Czech Science Foundation (GA ČR), Project No. 18-18858S, awarded to Jan Faigl
2018 - 2020
Internship
Robot Learning Lab, University of Washington
Seattle, WA, USA
2023
Teaching assistant
Department of Computer Science, Czech Technical University in Prague
AI in Robotics, Functional Programming, Procedural Programming
2018 - present
Project team member
Evaluation of Geometry-based Traversability Analysis for Off-road Navigation for the Ministry of Defence of the Czech Republic
2023
― Selected PUBLICATIONS
Miloš Prágr, Jan Bayer, and Jan Faigl
Autonomous exploration with online learning of traversable yet visually rigid obstacles
Autonomus Robots, 47, 2023
Miloš Prágr, Jan Bayer, and Jan Faigl
Autonomous robotic exploration with simultaneous environment and traversability models learning
Frontiers in Robotics and AI, 9, 2022
Rudolf Szadkowski, Miloš Prágr, and Jan Faigl
Self-learning event mistiming detector based on central pattern generator
Frontiers in Neurorobotics, 155, 2021
Miloš Prágr, Petr Čížek, Jan Bayer, and Jan Faigl
Online incremental learning of the terrain traversal cost in autonomous exploration
In Robotics: Science and Systems (RSS), 2019
Miloš Prágr, Petr Čížek, and Jan Faigl
Traversal cost modeling based on motion characterizationfor multi-legged walking robots
In European Conference on Mobile Robotics (ECMR), 2019
Miloš Prágr and Jan Faigl
Benchmarking incremental regressors in traversal cost assessment
In International Conference on Artificial Neural Networks (ICANN), 2019
Jan Faigl and Miloš Prágr
On Unsupervised learning of traversal cost and terrain types identification using self-organizing maps
In International Conference on Artificial Neural Networks (ICANN), 2019
Miloš Prágr, Petr Čížek, and Jan Faigl
Cost of transport estimation for legged robot based on terrain features inference from aerial scan
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018
Jan Faigl, Miloš Prágr, and Jiří Kubík
On Autonomous mobile robot exploration projects in robotics course
In International Conference on Robotics in Education (RiE), 2023