Pascal Becker
Papers
7
Total Citations
51
H-Index
5
About
Pascal Becker is a versatile robotics researcher whose work spans neuromorphic learning, space robotics, additive manufacturing automation, and human-robot interaction. His research bridges foundational computational neuroscience with real-world engineering challenges, making him a distinctive voice across multiple cutting-edge domains. Among his most notable contributions is his 2019 work on dopamine-modulated spike-timing-dependent plasticity (STDP) for robotic arm control, where he drew on brain-inspired learning mechanisms to teach robots target-reaching behaviors — an approach that earned 13 citations and reflects his interest in biologically plausible machine learning. His parallel investigations into additive manufacturing have been equally impactful: papers on real-time 3D printing error detection, automated post-processing with industrial robots, and flexible object handling collectively demonstrate a systems-level vision for fully automated fabrication pipelines, together accumulating over 24 citations. Becker's 2022 work on the ReCoBot, a walking space robot designed for on-orbit satellite servicing, highlights his ambitions beyond terrestrial applications. His more recent focus on assistive robotics and intuitive human-robot interfaces underscores a commitment to socially meaningful technology. Across his career, his research consistently aims to make robots more adaptive, autonomous, and accessible.
Research Focus
Key Achievements
Top Papers
- 1
- 2Real-Time In-Situ Process Error Detection in Additive Manufacturing9 citations · 2020
- 3A Walking Space Robot for On-Orbit Satellite Servicing: The ReCoBot9 citations · 2022
- 4
- 5Flexible Object Handling in Additive Manufacturing with Service Robotics7 citations · 2019
- 6
- 7