The abilities of humans provide both, a goal and inspiration, for the development of robotic systems. We try to understand these abilities to meld them into technical systems and to assist the human in various settings.

In order to understand the human “model”, we acquire bio-data like muscle activity, exerted forces, and performed motions by recording different measures, e.g., electromyography (EMG) and ultrasound. This data can expose very different sets of information, including the behavior of the subject, his intentions, and his abilities. Our goal is to process the data in a manner that lets us extract “interesting” information. Depending on the task under investigation the notion of interestingness might differ.

Once the information is extracted we can use it for different purposes. On the one hand, we want to build and optimize technical systems that---under a specific focus---offer similar performance like the human, an example being bi-articular joints to allow stiffness control. On the other hand, we want to use the information we receive as control commands. For example, we use different electrical impulses provided naturally by the human to control a robot on-line which in turn can either act as an additional limb for the subject or it can support the subject at performing self-motion.


We want to design robotic systems that offer specific desirable abilities, like flexibility and fast adaptability, of the human. In order to do that, we first need to identify the underlying structure and mechanisms. The goal is not to exactly copy nature's example. We want to see how nature implemented functionality and, if possible, why in that way. To acquire the necessary information we conduct studies with humans. The data we collect are thoroughly analyzed and evaluated. Using this knowledge, the question is how to design systems that mimic the behavior rather than the architecture. [...]


Bio-data exploitation for supportive robotics

Trying to retrieve the most benefit from the robotic systems, we are also targeting to support the human in his daily living. There are multiple scenarios where the human has limited control over his environment due to medical and health issues. Our objective is to let these people use robotic systems to interact with the environment instead of themselves. In order to facilitate highly intuitive control of robotic systems, we use bio-data from these people that we transfer to suitable control commands for the robots. Besides evaluating how to best process the data to enable easy control, we are looking for new technologies to generate this data. [...]


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