Focus
The main objective of this workshop is to take stock and make a state of the art of the situation regarding reproducibility and benchmarking in robotics research,
in particular when robots integrate or are used together AI technologies and AI scientific methods.
Another objective of this workshop is to provide practical examples, case studies, and guidance for a thorough comprehension of reproducibility and objective performance assessment in intelligent robotics,
facilitated by expert inspiration and mentorship, presentations of specific reproducible works in the literature (R- and r-articles ), benchmarking methodologies, and interactive discourse.
By emphasizing the importance of consistent and replicable results in practical robotic applications, we seek to expand the frontiers of knowledge, stimulate vigorous discourse, and facilitate collaborative research that will shape the forthcoming era of robotic progress.
The workshop will put in the same room the persons who gave the more significant contributions so far and aims to inspire new relevant contribution from the community, in particular, but not only, from its younger member.
The workshop will focus on the prevalent challenges and potential solutions associated with autonomous mobile systems, manipulation and grasping, and humanoids, while addressing general aspects of reproducibility and benchmarking in robotic research. R- and r-articles will be presented as essential instruments for enhancing reproducibility and facilitating objective quantitative assessment of results, thereby aiding in the abstraction of universal models applicable to all intelligent robots.
The event will be distributed into two workshops: one more focused on reproducibility at ICRA 2026 and one more focused on benchmarking at IROS 2026.
Key Topics
This workshop is designed to encompass a wide range of topics, with special focus, but not limited, to the following areas:
• Benchmarking methods for robotics research
• R-, r- and reply article in Robotics
• Software Tools and Platforms
• Benchmarking methods for robotics research
• Statistical significance of results
• Benchmarking of Machine Learning and Deep Learning systems used in intelligent robotics
• Open-Source and Novel Platforms for Reproducible Research