Call for Contributions

Important dates

  • Submission dealine: Tuesday, September 23, 2025;

  • Notification of acceptance: Tuesday, September 30, 2025;

  • Early bird registration to the conference: Friday, October 3, 2025;

  • Workshop date: Friday, October 17, 2025;

Submission Format

Submitted papers must adhere to the I-RIM 3D conference contribution guidelines, detailed in this document.

Authors are strongly encouraged to include an accompanying video that showcases the robotic application discussed in the manuscript.

How to submit

The abstract submission is handled by the EasyChair platform of the conference, and can be accessed at the following link: https://easychair.org/cfp/irim3d_2025.

While completing the submission form, you can specify in the Type of submission field to send the article to the workshop Industry 5.0: Workplace Transformation with Next Generation Smart Robots. Observe that it is not required to create double submission to the main conference, as all accepted article of the workshop will be included in the I-RIM 3D proceedings, which are open access.

Note: By submitting your paper, you agree—on behalf of all authors—to have the paper and any additional material published on the workshop webpage in open access format.

Review

All submissions will undergo a peer-review process (single-blind) for relevance to the workshop themes and overall quality. Accepted extended abstract and additional material will be published in this website, and are eligible for a poster presentation in the session following the keynote talks. Based on the judgment of the review committee, 3 best paper abstracts will be selected for a 5 minute oral presentation each.

Topic of interests

This workshop is interested in covering and addressing all topics related to Industry 5.0, including (but not limited to):

  • flexible manufacturing systems;

  • digital twin for manufacturing

  • robotics and AI for automation;

  • human-centered manufacturing;

  • collaborative robot for manufacturing;

  • machine learning for manufacturing;

  • safe manufacturing;

  • automated manufacturing processing;

  • metrology and data analysis;

  • human-machine interaction;

  • intelligent task and motion planning;

  • shared autonomy and adaptive control;

  • reinforcement learning and large behavioral model for the industry;