Marcus Futterlieb

Technische Universität Braunschweig, Laboratoire d'Analyse et d'Architecture des Systèmes

Papers

Total Citations

H-Index

About

Marcus Futterlieb’s research bridges industrial robotics and autonomous navigation, with a focus on solving real-world challenges in unstructured environments. His most influential work tackles the classic bin-picking problem—a critical bottleneck in manufacturing where robots must isolate and grasp individual parts from bulk boxes. In his 2013 paper on efficient bin-picking and grasp planning using depth data (51 citations), Futterlieb advanced object localization techniques that enable robots to reliably handle randomly oriented industrial components, directly improving automation efficiency in factories. More recently, his 2017 work on vision-based navigation in dynamic environments (3 citations) contributes to the Air-Cobot project, a collaborative initiative led by Akka Technologies and involving Airbus, aimed at developing long-term autonomous navigation for wheeled mobile robots in complex, changing settings. While his citation counts reflect a focused, application-driven impact, Futterlieb’s contributions are notable for their practical relevance—addressing fundamental problems in industrial robotics and autonomous systems that bridge the gap between laboratory research and real-world deployment. His work continues to influence the design of robust perception and manipulation systems for manufacturing and service robotics.