Building
Working on LLM-powered robotic task planning systems that translate natural-language commands into executable ROS2 action sequences for simulated manipulators. The goal: making robots that can take verbal instructions and turn them into safe, verifiable motion plans.
Learning
Exploring diffusion-based robot policies and vision-language-action (VLA) models — particularly how they can replace hand-coded task planners in unstructured environments. Also getting deeper into Isaac Sim for large-scale sim-to-real workflows.
Reading
- Probabilistic Robotics — Thrun, Burgard & Fox (finally finishing it)
- Recent papers from CoRL 2025 on world models for robot learning
- The Art of Doing Science and Engineering — Richard Hamming
Side Project
Building a small robotics simulation benchmark for evaluating LLM planners across a variety of household manipulation tasks — dishes, drawers, object sorting. Planning to release it as open source.
Location
Currently based in Tehran, Iran. Open to remote research collaborations and freelance robotics engineering work.