Daniel Ewert
Papers
11
Total Citations
125
H-Index
7
About
Daniel Ewert is a robotics and automation researcher whose work sits at the intersection of factory automation, human-robot interaction, and intelligent assembly systems. He is perhaps best known for his foundational contributions to the RoboCup Logistics League Sponsored by Festo, a competitive testbed for cyber-physical factory automation that has garnered over 50 citations across multiple publications and established itself as a landmark benchmark in the field. His research extends into cognitively inspired robotic assembly, with his 2011 paper exploring how architectures modeled on human cognition can drive more adaptive robotic processes. Ewert has also made notable advances in practical robotics challenges, including an efficient collision avoidance system for industrial manipulators operating in overlapping workspaces and a visual servoing framework enabling intuitive human-robot object transfer. His self-optimized assembly planning work, implemented within ROS-based robot cells, reflects a consistent drive toward autonomous, adaptable manufacturing systems. Beyond research, Ewert has demonstrated a commitment to education, contributing to problem-based learning approaches using LEGO Mindstorms. Collectively, his publications have accumulated over 120 citations, reflecting meaningful influence across both academic and applied robotics communities.
Research Focus
Key Achievements
Top Papers
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- 4Towards Benchmarking Cyber-Physical Systems in Factory Automation Scenarios11 citations · 2013
- 5A Visual Servoing System for Interactive Human-Robot Object Transfer10 citations · 2015
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- 7Selfoptimized Assembly Planning for a ROS Based Robot Cell7 citations · 2012
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- 9Selfoptimized Assembly Planning for a ROS Based Robot Cell2 citations · 2016
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