Project - ROBOPROX

ROBOPROX

Duration: 2024–2028

Description

The aim of the ROBOPROX project is to establish a foundation for the growth of cutting-edge research in the fields of robotics and industrial manufacturing by supporting excellent research teams in this domain, expanding current knowledge, creating original inventions, strengthening the academic programs of project partners, and leveraging both national and international collaboration in top-tier research. The goal is to transform Czech and European industries to deliver more flexible, complex, competitive, and sustainable industrial production. Mathematical modeling, data-driven approaches, simulation, optimization algorithms, and formal methods are increasingly popular in industry. However, there is a lack of fundamental concepts, interoperable models, and high-performance algorithms—highlighting the need for suitable tools. This need presents a clear opportunity for ROBOPROX to create an outstanding new research environment for developing and deploying innovative research approaches in the industrial sector.

Related publications

Bayer, Jan and Faigl, Jan: Reward-field Guided Motion Planner for Navigation with Limited Sensing Range, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024, pp. 3167–3174.

PDF url BibTeX

@inproceedings{bayer24iros,
	author = {Bayer, Jan and Faigl, Jan},
	title = {Reward-field Guided Motion Planner for Navigation with Limited Sensing Range},
	booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
	pages = {3167–3174},
	year = {2024},
	doi = {10.1109/IROS58592.2024.10801843},
}

Hulchuk, Vsevolod and Bayer, Jan and Faigl, Jan: LiDAR-Visual-Inertial Tightly-coupled Odometry with Adaptive Learnable Fusion Weights, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024, pp. 5641–5647.

PDF url BibTeX

@inproceedings{hulchuk24iros,
	author = {Hulchuk, Vsevolod and Bayer, Jan and Faigl, Jan},
	title = {LiDAR-Visual-Inertial Tightly-coupled Odometry with Adaptive Learnable Fusion Weights},
	booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
	pages = {5641–5647},
	year = {2024},
	doi = {10.1109/IROS58592.2024.10802180},
}

Prágr, Miloš and Bayer, Jan and Faigl, Jan: On Predicting Terrain Changes Induced by Mobile Robot Traversal, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024, pp. 11693–11698.

PDF url BibTeX

@inproceedings{pragr24iros,
	author = {Prágr, Miloš and Bayer, Jan and Faigl, Jan},
	title = {On Predicting Terrain Changes Induced by Mobile Robot Traversal},
	booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
	pages = {11693–11698},
	year = {2024},
	doi = {10.1109/IROS58592.2024.10802070},
}

Szadkowski, Rudolf and Faigl, Jan: Interpretable Active Inference Gait Control Learning, IEEE International Conference on Robotics and Automation (ICRA), 2025, pp. –.

PDF BibTeX

@inproceedings{szadkowski25icra,
	author = {Szadkowski, Rudolf and Faigl, Jan},
	title = {Interpretable Active Inference Gait Control Learning},
	booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
	pages = {–},
	year = {2025},
	doi = {},
}

Zoula, Martin and Faigl, Jan: Wireless Communication Infrastructure Building for Mobile Robot Search and Inspection Missions, IEEE International Conference on Robotics and Automation (ICRA), 2024, pp. 5970–5976.

PDF url BibTeX

@inproceedings{zoula24icra,
	author = {Zoula, Martin and Faigl, Jan},
	title = {Wireless Communication Infrastructure Building for Mobile Robot Search and Inspection Missions},
	booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
	pages = {5970–5976},
	year = {2024},
	doi = {10.1109/ICRA57147.2024.10611561},
}