Andreas Noll

Technical University of Munich, TU Dresden

Papers

Total Citations

H-Index

About

Andreas Noll is a leading researcher at the intersection of haptics, teleoperation, and the emerging Tactile Internet. His work focuses on enabling high-fidelity, low-latency transmission of touch and force feedback over communication networks—a critical challenge for remote robotics and skill transfer. Noll’s major contributions include pioneering haptic codecs that compress tactile data without compromising user perception, and developing learning-adaptive deadband sampling techniques that intelligently reduce packet rates while preserving task performance. These innovations directly address the “quality-of-learning” problem in teleoperation-based skill transfer, where network artifacts can degrade the demonstrations used to train remote robots. His most cited work, “Haptic codecs for the Tactile Internet” (2021), has garnered 7 citations and lays the foundation for next-generation telepresence systems. By systematically analyzing how communication constraints impact both human operator experience and robot learning outcomes, Noll is shaping the future of remote surgery, industrial automation, and collaborative robotics. His research is essential reading for anyone working on networked haptic systems or the practical deployment of the Tactile Internet.