%Aigaion2 BibTeX export from Idiap Publications
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@INPROCEEDINGS{Berio_RO-MAN_2025,
                      author = {Berio, D. and Clivaz, G. and Stroh, M. and Deussen, O. and Plamondon, R. and Calinon, Sylvain and Leymarie, F. F.},
                    keywords = {movement primitives, robot drawing},
                    projects = {Idiap},
         mainresearchprogram = {Human-AI Teaming},
                       title = {Image-driven robot drawing with rapid lognormal movements},
                   booktitle = {In Proc. IEEE Intl Symp. on Robot and Human Interactive Communication (Ro-Man)},
                        year = {2025},
                    abstract = {The democratization of cobots makes them accessible for physically producing paintings and drawings in collaboration with artists. At the same time, large deep-learning models are becoming increasingly common tools for a variety of complex image generation tasks. We present a method that combines these two advancements by enabling gradient-based optimization of natural human-like motions guided by cost functions defined in image space. To this end, we use the sigma-lognormal model of human hand/arm movements with an adaptation that enables its use in conjunction with a differentiable vector graphics (DiffVG) renderer. We demonstrate how this pipeline can be used to generate feasible trajectories for a robot by combining image-driven objectives with a minimum-time smoothing criterion. We demonstrate applications with generation and robotic reproduction of synthetic graffiti as well as image abstraction.},
                         pdf = {https://publications.idiap.ch/attachments/papers/2025/Berio_RO-MAN_2025.pdf}
}