Papers
12
Total Citations
79
H-Index
6
About
Marc Bestmann is a robotics researcher whose work centers on humanoid robotics, computer vision, and control systems for autonomous robots. His major contributions include the development of the **Wolfgang-OP**, an open-source humanoid robot platform designed for robustness and high-frequency control, which has become a key resource for research and competitions (10 citations). He also advanced embedded vision with **YOEO**, a hybrid CNN that unifies object detection and semantic segmentation for resource-constrained robots (7 citations), and proposed a real-time ball localization system using CNNs (13 citations). Bestmann’s impact is further demonstrated through his work on the **Dynamic Stack Decider** (DSD), a lightweight control architecture for complex robot behaviors (6 citations), and fast, reliable stand-up motions for humanoids using spline interpolation (6 citations). His research has been applied to practical challenges, such as teleoperation for aircraft fuel tank inspection (4 citations). With over 70 total citations, Bestmann’s contributions to open-source robotics and efficient perception systems have significantly advanced the field, making humanoid robots more capable and accessible for real-world applications.
Research Focus
Key Achievements
Top Papers
- 1Towards Real-Time Ball Localization Using CNNs13 citations · 2019
- 2
- 3Wolfgang-OP: A Robust Humanoid Robot Platform for Research and Competitions10 citations · 2021
- 4An Open Source Vision Pipeline Approach for RoboCup Humanoid Soccer7 citations · 2019
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- 6
- 7Replacing cables on robotic arms by using serial via Bluetooth6 citations · 2017
- 8DSD - Dynamic Stack Decider6 citations · 2021
- 9
- 10Humanoid Control Module: An Abstraction Layer for Humanoid Robots3 citations · 2020