Bart Engelen
Papers
7
Total Citations
83
H-Index
5
About
Bart Engelen is an emerging researcher at the forefront of robotic automation and sustainable manufacturing, with a particular focus on recycling, waste sorting, and circular economy applications. His work addresses one of the most pressing challenges in modern industry: developing intelligent, automated systems capable of handling the complex material streams generated by end-of-life products. Engelen's most impactful contribution to date is his 2022 deep learning framework for simultaneous mass estimation and scrap metal classification, which has garnered 38 citations and demonstrated that AI-driven perception can meaningfully advance recycling automation. Complementing this, his techno-economic assessments of robotic aluminium scrap sorting (14 citations) and battery dismantling systems for tablet devices (13 citations) bridge the gap between technical feasibility and real-world industrial deployment. His research extends into novel gripper technologies for handling shredded metal residues, intuitive robotic teaching methodologies for disassembly tasks, and multi-robot scheduling optimization — reflecting a remarkably broad yet cohesive research agenda. Across just a few years of publication, Engelen has established himself as a versatile contributor to the growing field of demanufacturing robotics, with work that directly supports Europe's circular economy ambitions and the sustainable management of electronic and metallic waste streams.
Research Focus
Key Achievements
Top Papers
- 1
- 2Techno-Economic Assessment of Robotic Sorting of Aluminium Scrap14 citations · 2022
- 3Design of a robotic system for battery dismantling from tablets13 citations · 2022
- 4Intuitive teaching approach for robotic disassembly7 citations · 2023
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