Papers
9
Total Citations
105
H-Index
5
About
Jan Kristof Behrens is a robotics researcher whose work sits at the intersection of human-robot interaction, robot programming, and autonomous manipulation. His research focuses on making robots more accessible, intuitive, and capable of operating alongside humans in both industrial and domestic environments. Behrens has made notable contributions to multi-modal robot teaching, demonstrating how natural language and physical demonstration can be combined to specify complex dual-arm robot tasks — work that has garnered over 40 citations across two closely related studies. His research on active visuo-haptic object shape completion (25 citations) addresses a fundamental challenge in robotic perception: reconstructing occluded object geometry by combining touch and vision, significantly improving downstream manipulation performance. Beyond perception, he has tackled the coordination challenges inherent in multi-robot systems, proposing simultaneous task allocation and motion scheduling approaches for complex shared-workspace scenarios. More recently, Behrens has explored gesture-based communication frameworks and constraint-based scheduling for human-robot collaboration, reflecting a sustained commitment to flexible, user-friendly robot programming. His work on embodied reasoning and interactive learning of physical object properties further highlights his interest in robots that actively discover and reason about their environments. Collectively, his research advances the vision of robots as genuine collaborative partners in real-world workplaces.
Research Focus
Key Achievements
Top Papers
- 1
- 2Active Visuo-Haptic Object Shape Completion25 citations · 2022
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- 5
- 6Context-aware robot control using gesture episodes4 citations · 2023
- 7
- 8Embodied Reasoning for Discovering Object Properties via Manipulation3 citations · 2021
- 9CoBOS: Constraint-Based Online Scheduler for Human-Robot Collaboration2 citations · 2024