Creating assembly products demands significant manual effort and expert knowledge in 1) designing the assembly and 2) constructing the product. This article introduces Prompt-to-Product, an automated pipeline that generates real-world assembly products from natural language prompts. Specifically, we leverage bricks as the assembly platform and automate the process of creating brick assembly structures. Given the user design requirements, Prompt-to-Product generates physically buildable brick designs and then leverages a bimanual robotic system to construct the real assembly products, bringing user imaginations into the real world. We conduct a comprehensive user study, and the results demonstrate that Prompt-to-Product significantly lowers the barrier and reduces manual effort in creating assembly products from imaginative ideas.
This article presents a comprehensive refurbishment of the interactive robotic art installationStandards and Double Standardsby Rafael Lozano-Hemmer. The installation features an array of belts suspended from the ceiling, each actuated by stepper motors and dynamically oriented by a vision-based tracking system that follows the movements of exhibition visitors. The original system was limited by oscillatory dynamics, resulting in torsional and pendulum-like vibrations that constrained rotational speed and reduced interactive responsiveness. To address these challenges, the refurbishment involved significant upgrades to both hardware and motion control algorithms. A detailed mathematical model of the flying belt system was developed to accurately capture its dynamic behavior, providing a foundation for advanced control design. An input shaping method, formulated as a convex optimization problem, was implemented to effectively suppress vibrations, enabling smoother and faster belt movements. Experimental results demonstrate substantial improvements in system performance and audience interaction. This work exemplifies the integration of robotics, control engineering, and interactive art, offering new solutions to technical challenges in real-time motion control and vibration damping for large-scale kinetic installations.
Earlier works with drawing robots were motivated by ideas of delegation and autonomy to create a distance between the artist's intentions and the final mark. In contrast, we present Companion, an artistic apparatus integrating a drawing robot with multimodal large language models (LLMs) to reintroduce the artist's presence through collaboration. Using in-context learning (ICL) and tool use for robot control, the system engages in bidirectional interaction via drawing and speech. Our goal is to develop an agent capable of pushing shared visual storytelling into unexpected aesthetic and narrative territories. Experiments demonstrate the system's potential as a playful cocreative partner. To validate the artistic contribution, we employed the consensual assessment technique (CAT) with a panel of seven art world experts (curators, a collector, and an artist) familiar with the authors' prior robotic works. The results confirm that the system produces artworks with a distinct aesthetic identity and professional exhibition merit.
