H. -K. Scherrer

École Polytechnique Fédérale de Lausanne, Institute of Robotics

Papers

Total Citations

H-Index

About

H.-K. Scherrer is a pioneering figure in intelligent robotic manipulation, whose work bridges neural computation and mechanical design. His primary research areas include neural network applications in robotics, adaptive grasping systems, and the development of general-purpose robot grippers. Scherrer’s major contribution lies in integrating artificial neural networks—specifically the Hopfield net—into robotic gripper control, enabling three-finger systems to autonomously compute optimal, stable grasps. This innovative approach, detailed in his seminal 1990 paper (16 citations), laid the groundwork for intelligent, self-adaptive end-effectors that can handle diverse objects without manual reprogramming. His later work (2006, 6 citations) refined these concepts for practical, general-purpose use. While his citation counts reflect a focused, specialized audience, Scherrer’s research is notable for being ahead of its time, anticipating the deep-learning-driven robotics that would emerge decades later. His contributions remain foundational for engineers developing dexterous, sensor-driven grippers for industrial and service robotics.