Papers
48
Total Citations
793
H-Index
18
About
Eric Demeester is a robotics researcher whose work spans human-robot interaction, assistive robotics, agricultural automation, and intelligent systems. Based at KU Leuven, his career reflects a sustained commitment to making robots safer, smarter, and more collaborative partners for humans across diverse settings. Demeester's early and influential contributions focused on assistive wheelchair technology, where he developed probabilistic and Bayesian frameworks for estimating driver intent — work that has accumulated over 80 citations across multiple publications and meaningfully advanced shared-control systems for elderly and disabled users. This thread of intent recognition later extended into industrial settings, where his research on visual tracking and human safety in robotic cells (87 combined citations) helped lay groundwork for fence-free human-robot collaboration. More recently, Demeester has tackled challenges at the frontier of modern robotics: agricultural automation for apple and pear orchards (59 citations), CNN-based grasp planning for vacuum grippers, decentralized task allocation for AGV systems, and probabilistic decision models for adaptive human-robot assembly. His 2021 papers collectively reflect a researcher deeply engaged with the practical realities of deploying robots in unstructured, human-centered environments. With over 400 citations across his most recognized works, Demeester's research offers an important bridge between theoretical robotics and real-world application.
Research Focus
Key Achievements
Top Papers
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- 5Lino, the User-Interface Robot38 citations · 2003
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