Intelligent robotic systems and AI-driven automation for industrial manufacturing and sustainable product lifecycle management
Applying generative AI and large language models to automate and accelerate CAD design workflows. Includes AI-assisted geometry generation, design optimisation, and integration with robotic manufacturing pipelines for rapid prototyping and production.
Programming and motion planning for industrial manipulators (UR5, KUKA). Developing ROS-based control architectures for automated manufacturing tasks including pick-and-place, inspection, and precision assembly.
Applying deep learning and large language models to automate component recognition, defect detection, and decision-making in robotic manufacturing cells. Directly applicable to quality inspection on automotive production lines.
Designing AI and DLT-based systems for the lifecycle management of industrial robots and electric vehicle batteries — supporting remanufacturing, refurbishment, and end-of-life automation in the automotive supply chain.
Creating AI-driven frameworks for computer-aided design and automated disassembly sequence planning — critical for EV battery recycling and remanufacturing of automotive components.
Ongoing research and engineering initiatives
Developing AI-powered robotic systems for the automated disassembly and remanufacturing of industrial robots and electric vehicle batteries. Research outcomes directly address the automotive industry's challenge of scaling sustainable end-of-life processing for EVs and industrial machinery.
Learn More - icircular3.euAn open-source Python library for controlling and programming the UR5 robotic manipulator, supporting motion planning, kinematics, and automation workflows for research and industrial applications.
View on GitHub — masoodad/ur5lib