Jef Peeters
Papers
15
Total Citations
203
H-Index
8
About
Jef Peeters is a prominent researcher at the intersection of robotics, artificial intelligence, and sustainable manufacturing, with a particular focus on automating waste electrical and electronic equipment (WEEE) recycling and circular economy processes. His work addresses one of modern industry's pressing challenges: making the disassembly, sorting, and recovery of end-of-life products economically viable and scalable through intelligent robotic systems. Peeters has made significant contributions to robotic grasping, developing CNN-based methods for vacuum gripper control and generating over 100,000 synthetic training grasps for deep learning applications — work that has collectively garnered over 56 citations. His innovative "You Only Demanufacture Once" (YODO) framework applies unsupervised learning to WEEE component retrieval, while his deep learning approaches to scrap metal classification have attracted 38 citations alone, reflecting strong industrial relevance. Beyond perception and grasping, Peeters has pioneered metrics for human-robot cooperative disassembly, intuitive robotic teaching methods, and techno-economic assessments of robotic sorting systems, demonstrating a rare ability to bridge technical innovation with real-world deployment considerations. His body of work positions him as a leading voice in advancing robotics for the circular economy.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Deep Learning Reactive Robotic Grasping With a Versatile Vacuum Gripper24 citations · 2022
- 4
- 5A CNN-Based Fast Picking Method for WEEE Recycling15 citations · 2022
- 6Techno-Economic Assessment of Robotic Sorting of Aluminium Scrap14 citations · 2022
- 7
- 8Design of a robotic system for battery dismantling from tablets13 citations · 2022
- 9
- 10Intuitive teaching approach for robotic disassembly7 citations · 2023