The Project

SENDOA: Secure Design and Development of AI-Based Robotic Systems (KK-2025/00102)

Abstract

The SENDOA project is a key initiative for the design and development of safe and highly capable robotic systems capable of collaborating effectively with humans. The manufacturing industry, faces significant challenges related to the need to improve efficiency and competitiveness. Robotic systems have the potential to go beyond the mere automation of repetitive tasks, enabling the execution of operations that require high precision and strict quality control.  These technologies can be applied in various areas, from the assembly of complex components to automated inspection, which helps minimize defects and optimize production.

The consortium is led by IKERLAN is made up of the University of the Basque Country (UPV/EHU),  LORTEK, IDEKO, University of Mondragón and INVEMA.

Objectives

SENDOA aims to create a comprehensive ecosystem that ensures the implementation of secure AI capabilities, the development of advanced cognitive capabilities that enable more natural and fluid interactions between humans and machines, and the creation of virtual environments that optimize the design, development, and validation of intelligent robotic systems.

In order to achieve the main objective of the project, the SENDOA consortium has defined the following specific objectives that will lead to different particular results:

- Ensure the safety of the AI capabilities of robotic systems by implementing safety components and specific development and validation methodologies.

- Develop advanced AI cognitive capabilities for intelligent robotic systems, with the aim of enhancing their dexterity and replicating human behavior, thereby facilitating more natural, fluid, and efficient interactions.

- Define and implement an advanced ecosystem based on virtual environments to accelerate and strengthen the holistic process of training, design, development, and validation of safe intelligent robotic systems.

Achievements

Acknowledgements

This work has been funded by the Government of the Basque Country under project KK-2025/00102 (Elkartek program for Cooperative Research).

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