Thomas Stoll

Papers

Total Citations

H-Index

About

Thomas Stoll is a researcher specializing in human-robot interaction and intelligent intralogistics, with a particular focus on gesture-based control systems for autonomous guided vehicles (AGVs). His most cited work, "FiFi – Controlling an AGV by detection of gestures and persons" (2024, 6 citations), introduces a novel contactless control system for automated guided vehicles in warehouse environments. Stoll's key contribution lies in developing a 3D sensor-based system that enables operators to control AGVs through natural gestures and person detection, eliminating the need for manual transport interfaces. This work addresses critical challenges in intralogistics by improving operational efficiency and safety in material handling. While his citation count is still growing, Stoll's research represents an important step toward more intuitive human-machine collaboration in industrial settings. His approach combines computer vision, gesture recognition, and autonomous navigation to create seamless interaction between workers and robotic systems. As the logistics industry increasingly adopts automation, Stoll's work on contactless AGV control systems positions him at the forefront of developing more accessible and efficient warehouse automation technologies.