31st EAISI lunch meeting

Thursday May 19, 2022 from 12:00 PM to 1:00 PM
Online - MS Teams

Theme: Robotics

Many TU/e researchers are advancing or using Artificial Intelligence in their research projects. To support cross disciplinary learning and to strengthen the TU/e AI network, EAISI organizes a series of (internal) meetings during lunch time, where various researchers talk about their projects, followed by Q&A.

Login details for this online meeting will be shared in Outlook. Add the meeting to your calendar, or send an email to eaisi@tue.nl if you are interested to join.




Johan Lukkien | Dean of Department Board, EAISI

Hala Elrofai | Program Manager Robotics, EAISI

Welcome & introduction


Rob Wolfs | Assistant Professor at Concrete Structures, Department BE 

Jelle Versteege | PhD Candidate at Concrete Structures, Department BE

Robotics in construction and the role of AI


Cesar Lopez Martinez | Assistant Professor at Control Systems Technology, Department of ME

Safe and explainable navigation of mobile robots


Anna-Sophie Ulfert-Blank | Assistant Professor at Human Performance Management, Department IE&IS

When robots become colleagues: Implementing and adapting to robotization at work





Rob Wolfs & Jelle Versteege
The construction industry is increasingly digitizing to increase the sectors’ productivity and reduce its environmental impact. Buildings are designed more efficiently, using advanced numerical tools and optimization strategies. These optimized geometries can be manufactured by adopting robotics for construction, such as large-scale 3D printing. Researchers at the Built Environment department are studying these technologies, developing new materials, design strategies and manufacturing systems. As both process and object complexity increases, quality control and optimization can be reached by adopting AI technologies. First results for the case of 3D concrete printing are presented. 

Cesar Lopez Martinez
Environments such as hospitals, schools, offices, etc., are highly dynamic and state-of-the-art robot navigation performance is usually poor. We propose an approach that uses a direct relation between the semantic features of the environment and the robot’s actions, such that they can be explained to users and developers. Moreover, traffic rules that are usually followed by humans, can be explicitly followed by the robot, which can lead to safer and more efficient navigation of mobile robots.

Anna-Sophie Ulfert-Blank
Artificial intelligence is transforming work in many organizations and across industries. Today, software agents are supporting employees in diverse information processing tasks and are even introduced as team members. To ensure successful human-AI collaboration and team effectiveness, autonomous agents that operate alongside humans need to be trusted both as a technology and as a team member. But how does trust in human-AI teams develop?