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.

• Added a new lifecycle node for state management.
• Logged delay spikes from the joint trajectory action.
• Verified collision boundaries in the simulator.

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