Hand gesture recognition as a quick interface to command robot behaviour
The SMARTHANDLE project is developing a hand gesture recognition system that uses machine learning and real-time visual processing to control robots intuitively through natural movements. Currently being developed at AIMEN for use with different robot models, the system is being refined for greater accuracy and user-friendliness by training on diverse hand data and simplifying gesture execution.
AI-based 6D Pose Estimation Leveraging the Power of Synthetic Data
AI-driven 6D pose estimation is transforming industrial automation by enhancing robotic vision and efficiency. Synthetic data provides a scalable solution for training deep learning models, addressing challenges in real-world data collection. A case study in the metal industry showcases how Roboception leverages Blender-generated synthetic datasets to improve object detection and pose estimation, ensuring adaptability in dynamic manufacturing environments.
Robot learns from demonstration in car battery dismantling
Efficient and safe disassembly of electric vehicle batteries is crucial for meeting the growing demand for sustainable transportation. By integrating automation, machine learning, and teleoperation, the process can be optimized to ensure worker safety, precision, and adaptability to diverse battery designs. These innovations not only reduce risks and environmental impact but also accelerate recycling efforts, paving the way for a more sustainable and scalable electric vehicle ecosystem.
Battery Recycling: How to Handle the Battery Pack Disassembly Process
ABEE is leading the way in sustainable battery recycling, focusing on the efficient disassembly of electric vehicle (EV) battery packs. Through the integration of robotics and automation, ABEE enhances safety and operational efficiency in the recycling process, while contributing to a circular economy by repurposing or recovering valuable materials for future use in energy solutions.
Smart handling of contact lenses in automated manufacturing
The SMARTHANDLE project focuses on developing advanced handling systems for automated manufacturing processes. The project brings together partners specialising in hardware, software, and specific manufacturing needs to innovate and improve automated handling technologies. The authors of this blog participate in the Menicon use case.
ALUMIL participates in the European Research Project SMARTHANDLE
ALUMIL is pleased to announce its participation as a pilot case in the European Research Project SMARTHANDLE which aims to address the modern challenges of the manufacturing sector in the European Union by enhancing productivity, flexibility, and sustainability in the production process.