ROB / Assistance Robot Race
EDAN
Germany
About the Team
At DLRs Re-Enabling Robotics group, we are investigating how assistive robotics technology can support people with severe physical disabilities. Following this goal, our research is twofold: On the one hand, we explore novel human-machine interfaces that enable people with severe physical disabilities to control assistive systems. On the other hand, we develop methods for autonomous and semi-autonomous control concepts that allow the intuitive use of an assistance robot and provide intelligent support in performing everyday activities. We combine all these methods in our wheelchair-based assistive robot system EDAN (EMG-controlled Daily Assistant), which consists of a power wheelchair equipped with a DLR lightweight robot. This system is supposed to enable people with severe physical disabilities to perform simple daily tasks such as drinking or opening doors independently.
About the Pilot
The pilot is Mattias Atzenhofer.
He is 30 years old and lives in a small town near Munich. Despite his muscular dystrophy, he is employed and has been working in an office job at Pfennigparade for several years.
Mattias has been collaborating with the EDAN team for about two years. On the one hand, he is fascinated by technology; on the other, he is passionate about advancing research in assistive robotics to help people in similar situations.
Mattias and EDAN won the CYBATHLON Challenge 2023, and now he is looking forward to competing in the CYBATHLON 2024 at the SWISS Arena alongside the other teams.
About the Device
EDAN is a research prototype of an assistive robotic system designed to restore mobility and manipulation capabilities to people with motors. EDAN combines several robotic techniques into one versatile and powerful system. The core components are the sEMG-based interface, coordinated whole-body control, and shared control capabilities to support the execution of complex tasks. We build our autonomy spectrum with a focus on flexibility, allowing the user to choose the level of autonomy on a task-dependent basis. In particular, we envisage that user-driven levelsbuilding of autonomy will allow the exploration of EDAN's autonomous functions at the user's own pace, thereby increasing the transparency of the system. Our approach keeps the user in control and provides transparent robot behaviour, which is essential to building trust in the system and its autonomous capabilities.