Guntis V. Strazds, Katrīna Viltrake, Gergely Hollosi, Laura Leja, Arnis Priedītis, Diāna Dupļevska, Makss Meiers, Christos Chronis, Iraklis Varlamis, George Dimitrakopoulos, Kārlis Freivalds . Applied AI for Adaptive Robotic Conveyor-Feeding (I). 1st IFAC Joint Conference on Computers, Cognition, and Communication, 1, IFAC, 2025.
Bibtex citation:
Bibtex citation:
@inproceedings{19807_2025,
author = {Guntis V. Strazds and Katrīna Viltrake and Gergely Hollosi and Laura Leja and Arnis Priedītis and Diāna Dupļevska and Makss Meiers and Christos Chronis and Iraklis Varlamis and George Dimitrakopoulos and Kārlis Freivalds },
title = {Applied AI for Adaptive Robotic Conveyor-Feeding (I)},
journal = {1st IFAC Joint Conference on Computers, Cognition, and Communication},
issue = {1},
publisher = {IFAC},
year = {2025}
}
author = {Guntis V. Strazds and Katrīna Viltrake and Gergely Hollosi and Laura Leja and Arnis Priedītis and Diāna Dupļevska and Makss Meiers and Christos Chronis and Iraklis Varlamis and George Dimitrakopoulos and Kārlis Freivalds },
title = {Applied AI for Adaptive Robotic Conveyor-Feeding (I)},
journal = {1st IFAC Joint Conference on Computers, Cognition, and Communication},
issue = {1},
publisher = {IFAC},
year = {2025}
}
Abstract: This paper presents a modular AI-driven robotic system for dynamic production line tasks, integrating real-time vision, adaptive motion planning, and making use of LLM-based code generation to facilitate reconfiguration for new products or tasks. The architecture of the overall system is described, as are design considerations and initial evaluation results for AI-based components for bottle pose estimation, tracking of moving sockets into which bottles need to be inserted, and training of a neural network for dynamic robot-motion control.
Quartile: Q3