This workshop introduces experimental and creative approaches to robotic motion generation through data analysis. Students will explore how to extract structured information from raw datasets and apply scalable methods—such as dimensionality reduction—to design complex, multi-axis trajectories. Emphasis is placed on experimentation, iteration, and how data-driven processes can support expressive, adaptable motion design in artistic, architectural, and performative contexts.
Understand how data, motion, and materiality converge in creative robotic applications.
Analyze multi-scale datasets and translate insights into robotic motion trajectories for artistic and practical uses.
Build foundational skills in Python scripting, data analysis, and parametric design in Grasshopper.
Program robotic toolpaths and design custom effectors aligned with project goals.
Engage in experimental material exploration and refine designs through iterative prototyping and peer collaboration.
The Black Paintings are a group of 14 works created by Francisco de Goya between 1819 and 1823, during the final years of his life. Painted directly onto the walls of his house, the Quinta del Sordo, these works represent one of the most intimate, radical, and unsettling moments in Western art. They are now … Read more
In this article, we explain our Workshop 1.2 project, in which we analyzed data to transform it into movements to control an ABB IRB 6700-150/3.20 industrial robot equipped with a plastic pellet extruder for additive manufacturing. The main idea of our project was to analyze climate data from the city of Barcelona during the years … Read more
