How can robots independently perform complex tasks in real-world environments? This is the question being explored by the AICOR Institute for Artificial Intelligence (IAI) at the University of Bremen, headed by Prof. Dr. h.c. Michael Beetz.The research focuses on robotic systems that can perceive their environment, plan actions and make decisions autonomously. Instead of simply executing pre-programmed motion sequences, these systems are designed to respond flexibly to different situations – both in household and industrial environments.

A key prerequisite for this is reliable interaction with the physical world. This is exactly where gripping technology comes into play. Malte Huerkamp, Research Associate at the IAI, describes its importance as follows: “Without a reliable gripping system, neither tools can be operated nor objects handled, which blocks any further research progress.”

Flexible gripping technology for demanding research scenarios

For the experimental setups at the IAI, a gripping system was required that is precise, durable and flexible to use. The decision was made in favor of gripping modules from WEISS Robotics.
The grippers are currently being used in experiments for cutting fruit and vegetables – a subtask of automated meal preparation. Tasks like these clearly demonstrate how demanding robotic manipulation is in real-world scenarios: different objects, tools and materials require flexible solutions at the robot arm.
One important advantage is the ability to individually design and replace the gripper fingers. The team around Prof. Dr. h.c. Michael Beetz explains: “This allows us to use the same gripper for different tools and objects without having to change the entire system every time.”

Easy integration into existing robot platforms

In addition to mechanical flexibility, integration into the existing laboratory environment also played an important role. At the IAI, the gripping systems are used in combination with UR5 robots.
The software integration was also straightforward. The researchers report: “Thanks to the supplied ROS2 and Python interfaces, the gripping system could be quickly integrated into our existing system landscape without major integration effort.”
This enabled the grippers to be integrated quickly into the existing research environment and used for various experiments.

Professional gripping technology for research, teaching and student projects

The gripping systems have now become an integral part of the robot platforms at the IAI. As a result, they are used not only in research projects, but also in courses, project work, and bachelor’s and master’s theses.
For students, this provides direct access to professional gripping technology and realistic application scenarios. Working with the systems connects theoretical knowledge with practical robotics experience and supports the development of technical skills for their future careers.

Precise gripping systems as a key component for robots as everyday assistants

One central research focus in the coming years will be on manipulation tasks that enable robots to become reliable and largely autonomous assistants in everyday life. These include applications such as meal preparation or loading and unloading dishwashers.
For such scenarios to be not only planned but actually carried out, gripping systems are needed that are precise, reliable and flexible to integrate. This is exactly where the gripping systems from WEISS Robotics make a decisive contribution: they combine mechanical precision with adaptable gripper fingers and suitable interfaces for integration into modern robot platforms.

Looking to the future, the team at the AICOR Institute writes: “In the coming years, the trend will continue toward robots increasingly working together with humans and performing complex tasks based on natural-language instructions.”

We are pleased that gripping systems from WEISS Robotics are supporting the research work at the AICOR Institute for Artificial Intelligence at the University of Bremen and that we are contributing to the next generation of cognitive robotic systems.