H. Ritter

Papers

Total Citations

107

H-Index

About

H. Ritter is a pioneer in situated robot learning and human-robot interaction, with a career dedicated to bridging the gap between robotic manipulation and human-like intelligence. His key research areas include multi-modal learning, brain-computer interfaces, and dexterous manipulation of deformable objects. Ritter’s most cited work, “Situated robot learning for multi-modal instruction and imitation of grasping” (71 citations), introduced groundbreaking methods for robots to learn grasping tasks through demonstration and natural instruction, laying the foundation for intuitive human-robot collaboration. He also advanced assistive robotics with “A hybrid brain interface for a humanoid robot assistant” (20 citations), developing a semi-autonomous system that enables handicapped individuals to control Honda’s Humanoid Research Robot via brain signals—a notable achievement in neuroprosthetics. In “Bi-manual robotic paper manipulation based on real-time marker tracking and physical modelling” (16 citations), Ritter tackled the complex challenge of handling deformable objects, using marker tracking and physics models to achieve human-like manual dexterity. His work has profoundly influenced robotic learning and assistive technology, demonstrating how robots can adapt to human needs through imitation, brain control, and delicate manipulation.