Michael Mende
Papers
7
Total Citations
91
H-Index
5
About
Michael Mende’s research sits at the intersection of robotics, human-robot interaction, and assistive technology, with a focus on making robotic systems more accessible, intelligent, and socially beneficial. His most influential work, a versatile capacitive tactile proximity sensor (35 citations), advanced the field of robotic perception by enabling robots to sense both touch and proximity, a critical capability for safe human-robot collaboration. Mende also spearheaded the KUKA Robot Learning Lab at KIT, a remotely accessible robotics testbed that democratizes access to expensive industrial robots for education and research (21 citations). In the domain of healthcare, his pilot study on robot-based training for people with mild cognitive impairment (15 citations) demonstrated how robotic systems can support motor skill retention and postural control, addressing the growing need for assistive technologies in aging societies. His work on model-free grasp planning for configurable vacuum grippers (11 citations) further showcases his contributions to autonomous manipulation. With a career spanning applications from nuclear decommissioning to neuromuscular training, Mende exemplifies how robotics can be engineered for real-world impact, from the factory floor to the rehabilitation clinic.
Research Focus
Key Achievements
Top Papers
- 1A versatile and modular capacitive tactile proximity sensor35 citations · 2016
- 2
- 3Robot-Based Training for People With Mild Cognitive Impairment15 citations · 2019
- 4Model-Free Grasp Planning for Configurable Vacuum Grippers11 citations · 2018
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- 7Overview of a Robot for a Neuromuscular Training – RoboTrainer2 citations · 2019