Henry Stoutjesdijk

Philips (Netherlands)

Papers

2

Total Citations

8

H-Index

2

About

Henry Stoutjesdijk is a robotics researcher whose work lies at the intersection of autonomous navigation, human-robot interaction, and optimal control. His primary contributions focus on developing intelligent frameworks that enable robots to operate safely and predictably alongside humans. Stoutjesdijk’s notable work on collision-free trajectory planning introduced an adaptive virtual target approach that effectively prevents deadlock in human-centred environments—a critical challenge for robots following predefined paths. This paper, along with his research on Bayesian optimization for tuning Model Predictive Control (MPC)-based shared controllers, has garnered early citations, reflecting the growing relevance of his methodologies. By automating the tuning of shared controllers through simulation-based performance metrics and user input representation, Stoutjesdijk addresses the practical need for adaptable, human-aware robotic systems. His work bridges the gap between theoretical control frameworks and real-world deployment, making autonomous robots more predictable and acceptable to humans. With each publication laying groundwork for safer, more efficient human-robot collaboration, Stoutjesdijk is establishing himself as a promising voice in the field of shared autonomy and motion planning.

Research Focus

Key Achievements

2
H-Index
2
Papers
8
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
A Bayesian Optimization Framework for the Automatic Tuning of MPC-based Shared Controllers
4 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Philips (Netherlands)

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago