The Project
AURRERA: Automatic generation of multiform geometry trajectories in new generation robotics (KK-2024/00024)
- Lead Researchers: Aitziber Mancisidor Barinagarrementeria - (01/04/2024 - 31/12/2025)
- Research Area: Collaborative and intelligent Robotics
- Funding Body: Government of the Basque Country - Elkartek program
Abstract
The industry is facing a new market trend towards very demanding levels of productivity and quality, high product variety in small quantities and high customisation. This creates the need to build highly flexible and intelligent manufacturing environments, which allow rapid adaptation of processes and systems to changing conditions, while maintaining high product quality with lower production costs and energy consumption.
Currently, the reconfiguration of automated and robotic systems is approached manually, which entails a number of limitations and disadvantages. In the AURRERA project, with the intention of responding to these limitations, the aim is to develop a methodology for automatic generation of multiform geometry trajectories in new generation robotics.
The consortium is led by IDEKO is made up of the University of the Basque Country (UPV/EHU), BCAM, TEKNALIA, LORTEK, VICOMTECH, University of Mondragón and AUTOTECH.
Objectives
The aim of the AURRERA project is to generate a paradigm shift in advanced manufacturing with robots to provide flexibility to generic installations through the automatic generation of trajectories in product manufacturing processes regardless of their geometry.
In order to achieve the main objective of the project, the AURRERA consortium has defined the following specific objectives that will lead to different particular results:
- Develop advanced algorithm for automatic trajectory generation.
- Implement the simulations for each of the different process typologies.
- Accelerate automatic path generation algorithms for near real-time execution times.
- Deploy automatic trajectory generation algorithms at laboratory level.
Achievements
Research and development work is currently underway. At the end of the project, the achievements will be made public.
Acknowledgements
This work has been funded by the Government of the Basque Country under project KK-2024/00024 (Elkartek program for Cooperative Research)