Welcome to the
AMOROSO Online Catalogue
This landing page gives a broad overview of all the different topics: robots, sensors, algorithms, use cases, …
Hardware
Robots (platforms)
This includes legged and wheel based robot (platforms) we researched during the AMOROSO project.
(Mini)-computers
A select overview of various small (companion) computers to improve the compute power of a robot (platform).
Sensors
A broad overview of the different sensors to add capabilities to a robot (platform).
Software
Algorithms
The list of algorithms to solve problems such as object detection, pose estimation, SLAM…. we explored.
Supporting infrastructure tools
Supporting infrastructure tools for Robot development and testing: GitHub Repos, Docker environments.
Datasets
Synthetic and real data to train computer vision and AI models.
Publications
Guidelines
Software safety measures for autonomous mobile robots in uncertain environments.
Papers
D. De Schepper, G. Schouterden, K. Kellens, E. Demeester (2022). Human-robot mobile co-manipulation of flexible objects by fusing wrench and skeleton tracking data. International Journal Of Computer Integrated Manufacturing. doi: 10.1080/0951192X.2022.2081362
https://lirias.kuleuven.be/retrieve/664398
D. De Schepper, I. Dekker, M. Simons, L. Brabants, W. Schroeyers, E. Demeester (2022). Towards a Semi-Autonomous Robot Platform for the Characterisation of Radiological Environments. IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), PP. 230-237. ISBN: 978-1-6654-5680-7. doi: 10.1109/SSRR56537.2022.10018668
https://lirias.kuleuven.be/retrieve/681789
R. Verbiest, K. Ruysen, J. Langenakens, H. Wirix, D. Dylemans, E. Demeester, K. Kellens (2022). Qualitative Leaf Coverage Validation based on a RGB Vision System: “Spray Quality Assessment Dome – SQUAD”. In: Aspects of applied biology / Association of Applied Biologists: vol. 147, pp. 277-282.
https://lirias.kuleuven.be/3663651 🡪 Access: mailto:eric.demeester@kul.be
D. De Schepper, M. Simons, W. Schroeyers, K. Kellens and E. Demeester. Learning Multiple Radiation Source Distribution Models using Gaussian Processes. 56th International Symposium on Robotics (ISR).
https://lirias.kuleuven.be/4089540 🡪 Access: mailto:eric.demeester@kul.be
P. Aerts, P. Slaets and E. Demeester (2023). Graph-based Simultaneous Localization and Mapping with incorporated dynamic object motion. European Conference on Mobile Robotics (ECMR).
https://lirias.kuleuven.be/4121945 🡪 Access: mailto:eric.demeester@kul.be
Theses
Nikki Bruls: Robot interaction techniques for autonomous mobile robots in uncertain environments: https://drive.google.com/file/d/1nuorNOXLfBRpgw6SzV-iriU3Zz8TadWt/view?usp=sharing
Tomas Van Doninck: Semantic SLAM for autonomous mobile robots in uncertain environments: https://drive.google.com/file/d/1qhD_IIn9eap_SmsKIIR2KzqvshNCgv06/view?usp=sharing
Thomas Ballet: Multi-agent shadow trailing for autonomous mobile robots in uncertain environments: https://drive.google.com/file/d/1hfsqeLuOHNHsvrOsxqbCOGjOS-HN7hJZ/view?usp=sharing
Wout Struys: Semantic FUSED SLAM for autonomous mobile robots in uncertain environments: https://drive.google.com/file/d/1SOLH8pLvps82zYTt3Gp451uBB56wUifl/view?usp=sharing
Education
Level up your Robot Skills
Discover the essentials of robotics with our interactive course materials. Dive into videos and detailed instructions covering ROS, Computer Vision, and SLAM. Perfect for learners at all levels, these resources are designed to give you practical, hands-on experience in the core technologies shaping the future of robotics.
Get Started
It’s Never Too Late or Too Early to Get Started
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam.