Matthew Krebs
Papers
1
Total Citations
14
H-Index
1
About
Matthew Krebs is a leading researcher in the fields of robotic manipulation, fiber optic sensing, and deep learning for dexterous control. His work focuses on enhancing the autonomy and safety of remote robotic systems, particularly for complex and hazardous environments where human operation poses significant risk. Krebs’s major contribution lies in the development of a force-sensitive robotic end-effector that integrates embedded fiber optics with deep learning characterization. This innovation enables more precise and intuitive remote manipulation, overcoming the performance and efficiency limitations of traditional teleoperation. His most cited paper, "Force Sensitive Robotic End-Effector Using Embedded Fiber Optics and Deep Learning Characterization for Dexterous Remote Manipulation" (2019), has garnered 14 citations, reflecting its impact on advancing human-robot interaction. Krebs’s research is pivotal for applications in nuclear decommissioning, space exploration, and disaster response, where reliable, high-fidelity remote control is critical. His work continues to push the boundaries of what autonomous robotic systems can achieve in high-stakes scenarios.
Research Focus
Key Achievements
Top Papers
- 1