Daniel Malicki
Papers
1
Total Citations
9
H-Index
1
About
Daniel Malicki is a researcher whose work sits at the intersection of human-computer interaction and assistive robotics, with a particular focus on intuitive control systems. His most cited contribution, "Remote control of the artificial arm model using 3D hand tracking" (2013, 9 citations), pioneered a novel method for driving a robotic arm using the Microsoft Kinect sensor. By leveraging gesture recognition and 3D hand tracking, Malicki demonstrated how off-the-shelf gaming technology could be repurposed to create more natural, accessible interfaces for prosthetic and robotic control—eliminating the need for dedicated, expensive manipulators. This work, while modest in citation count, represents an early and influential step in the broader movement toward low-cost, vision-based human-robot interaction. Malicki’s research has helped lay the groundwork for more intuitive control schemes in assistive technology, showing how modern sensing can bridge the gap between human intention and machine action. His contributions remain relevant to researchers exploring accessible robotics, gesture-based interfaces, and the democratization of prosthetic control systems.
Research Focus
Key Achievements
Top Papers
- 1Remote control of the artificial arm model using 3D hand tracking9 citations · 2013