07/10/2025
The JARVIS project was proudly featured at ESAIM2025 – the 3rd European Symposium on Artificial Intelligence in Manufacturing. The JARVIS team presented the latest research on a deep learning-based robot perception system, developed to support high-precision automotive battery assembly.
The presented work addresses one of the major challenges in modern manufacturing: enabling robots to reliably detect and manipulate small, flexible components, such as screws and cable connectors, even when randomly placed or oriented. By integrating point cloud processing techniques with advanced deep learning models, the system achieves accurate 6DoF pose estimation, supporting precise and autonomous robotic assembly.
The solution was validated in a real-world industrial setting, and the study includes a comparison of three leading deep learning approaches, offering practical insights for scaling AI-driven perception systems from lab environments to the factory floor.
This milestone brings the JARVIS project closer to enabling agile, intelligent automation for complex manufacturing tasks!
🔗 Learn more about ESAIM2025: https://aim-net.eu/esaim2025/
This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement nº 101135708. The dissemination of results herein reflects only the author’s view, and the European Commission is not responsible for any use that may be made of the information it contains.
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