Jonas Berlin
Papers
1
Total Citations
6
H-Index
1
About
Jonas Berlin is a robotics researcher whose work centers on autonomous navigation and motion planning for mobile robots in complex, dynamic environments. His most-cited contribution, "Trajectory Generation for Mobile Robots in a Dynamic Environment using Nonlinear Model Predictive Control" (2021), tackles the critical challenge of enabling robots to safely and efficiently navigate industrial settings filled with both static and dynamic obstacles. Berlin’s approach elegantly combines a visibility graph and A* algorithm for long-range path planning with nonlinear model predictive control for real-time trajectory generation, ensuring collision-free movement even as the environment changes. This work has garnered 6 citations, reflecting its practical relevance to the field of autonomous robotics. By bridging global path planning with local reactive control, Berlin has provided a robust framework that advances the state of the art in mobile robot autonomy, making his research particularly valuable for students and engineers developing next-generation warehouse, factory, or service robots.
Research Focus
Key Achievements
Top Papers
- 1