Papers
5
Total Citations
14
H-Index
2
About
Oto Haffner is a researcher focused on mobile robotics, human-robot interaction (HRI), and discrete-event control systems. His early work on metric mapping for mobile robots using laser rangefinders (2014, 6 citations) provided foundational algorithms for real robotic systems to navigate collision-free environments. Haffner has also contributed to the modeling and control of automated storage and retrieval systems (AS/RS) using Coloured Petri nets (2016). More recently, his research has centered on gesture recognition for mechatronic system control, employing motion-capture suits and LSTM/GRU neural networks (2023–2025). His 2023 study on gesture recognition using a motion-capture suit and LSTM networks (4 citations) explores intuitive human-robot interfaces, while subsequent work in 2025 evaluates the Rokoko SmartSuit Pro II for real-time control of mechatronic devices. With a growing portfolio in advanced HRI and neural-network-based gesture classification, Haffner’s contributions bridge classical robotics control with modern, data-driven interaction paradigms, offering practical pathways for seamless human-machine collaboration.
Research Focus
Key Achievements
Top Papers
- 1Making a map for mobile robot using laser rangefinder6 citations · 2014
- 2
- 3Modelling and control of AS/RS using Coloured Petri nets2 citations · 2016
- 4
- 5