Paul Daelman
Papers
4
Total Citations
33
H-Index
4
About
Paul Daelman is a leading researcher in industrial collaborative robotics, focusing on the safe and efficient integration of autonomous mobile manipulators into modern manufacturing environments. His work centers on human-robot co-manipulation, particularly the development of control strategies for dual-arm robots handling large or flexible objects—a critical challenge in industries like automotive and aerospace. Daelman’s most cited paper (15 citations) presents a real-world application of an Autonomous Industrial Mobile Manipulator (AIMM) under the European SHERLOCK project, demonstrating how low-value processes can be automated through safe human-robot cooperation. He further advanced this field with a path-driven architecture for dual-arm co-manipulation of large parts (6 citations) and control strategies for flexible objects (6 citations). Notably, his recent HUMANISE project (2023, 6 citations) addresses the pressing issue of an aging workforce by developing human-inspired smart management systems that monitor worker health and safety in collaborative settings. With a growing citation impact and a clear focus on bridging robotics research with industrial deployment, Daelman’s work is shaping the future of safe, adaptive, and human-centric automation.
Research Focus
Key Achievements
Top Papers
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