Vision For Robotfusion – Brabant.ai
Collaborative AI and data-sharing project for robotic vision and applied AI development.
NLAI Solutions is participating in the Vision For Robotfusion – Brabant.ai project, a collaborative initiative focused on exploring how shared image data can support the development and improvement of AI models for agricultural and robotic applications.
Challenge
Sharing image data is a structural problem
AI models in robotics and agriculture depend heavily on high-quality image data. However, data sharing between organizations requires more than technical infrastructure. It also requires clear governance, reusable formats, trust, and practical workflows.
NLAI Contribution
What NLAI is contributing
AI model validation
Hands-on validation of computer vision models against shared, multi-source image data.
Image transformation
Pipelines for normalizing, transforming, and preparing image data for downstream model training.
Dataset development
Structured dataset preparation, annotation review, and quality checks for reusable assets.
Tooling support
Engineering support for tooling that makes AI workflows reproducible and inspectable.
Data-sharing methodology
Practical methods for responsible data sharing across organizations and use cases.
Community documentation
Documentation that helps the broader Brabant AI community adopt and reuse what is built.
Focus areas
Where the work is concentrated
AI model development & validation
Validating how shared image datasets support the development and improvement of AI models for robotic and agricultural use.
Image transformation & datasets
Preparing, transforming, and structuring image data so that it can be reused responsibly across organizations.
Shared data structures & governance
Defining structures and governance principles that make multi-organization data sharing practical and trustworthy.
Tooling for AI workflows
Supporting tooling and engineering work that helps teams build, evaluate, and document AI workflows.
Reusable templates & methodologies
Contributing to reusable templates, formats, and methodologies that other Brabant.ai initiatives can adopt.
Generic community approach
Supporting a generic community approach for data sharing within the wider Brabant AI ecosystem.
Work packages
Two parallel work tracks
The project is structured around two complementary packages: one technical proof of concept, and one community-oriented method.
WP1
Proof of Concept for Data Sharing in Weed Robots
Technical and organizational validation of using shared image data to improve AI models for robotic and agricultural applications.
WP2
Generic Community Approach for Data Sharing
Development of a reusable approach, toolkit, templates, and practical methods that can support data sharing within the wider Brabant AI community.
Project impact
A stronger, more reusable AI ecosystem
The project contributes to a stronger AI ecosystem in Brabant by creating practical methods and reusable building blocks for shared data, collaborative AI development, and applied innovation.
Partners & Ecosystem
Built together with the Brabant AI ecosystem
Part of the broader AI community Brabant initiative, with partners across Brainport Development and Breda Robotics.
Interested in collaborative AI projects?
We are open to applied research and ecosystem collaborations focused on data sharing, computer vision, and reliable AI systems.