2025 / Undergraduate research assistant
Learning Social Navigation in Mobile Robots
A robotics research project on learning socially compliant navigation behaviors in dynamic pedestrian environments.
At Boğaziçi University COLORSLAB, I worked on a social navigation project for mobile robots. The work was published as Mobil Robotlarda Sosyal Navigasyon Öğrenme / Learning Social Navigation in Mobile Robots at IEEE SIU 2025.
The project focused on navigation behaviors that are not only collision-free, but socially legible: for example, passing behind pedestrians rather than cutting through their likely path. We modeled the environment as a dynamic social graph and combined graph-based interaction modeling with temporal trajectory prediction.
My Contributions
- Designed and implemented a hybrid learning framework using Graph Attention Networks and Conditional Neural Processes.
- Reverse-engineered and extended the Unity-based SEAN 2.0 simulation environment for custom data collection.
- Built dynamic multi-agent scenarios for training and evaluation.
- Validated the learned model in social environments against simpler linear baselines.
Outcome
The work produced a conference paper and a research prototype that reduced social norm violations compared with baseline navigation behavior in the evaluated scenarios.