# Robot

- **Event:** [OpenEnv Hackathon SF](https://cerebralvalley.ai/e/openenv-hackathon-sf)
- **When:** Mar 7 at 9:00 AM – Mar 8 at 12:00 AM (PST)
- **Where:** Shack15, San Francisco, CA
- **Team:** [Jwalin Shah](https://cerebralvalley.ai/u/jwalinshah)
- **GitHub:** https://github.com/jwalin-shah/robo-replan
- **Website:** https://colab.research.google.com/github/jwalin-shah/robo-replan/blob/main/train/colab_train.ipynb
- **Demo video:** https://youtu.be/1waYHPytoNE
- **Hugging Face:** https://huggingface.co/spaces/jshah13/roboreplan
- **Gallery:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/20

RoboReplan is a tabletop planning environment for OpenEnv that targets Problem Statement 3.1 (World Modeling: Professional Tasks). LLMs often fail at long-horizon robot tasks because they can't replan — they loop or freeze when something goes wrong (blockers, grasp slips, mid-task instruction changes). RoboReplan benchmarks this failure mode and trains agents to recover: clear blockers, pick and place in the right bins, and adapt when the instruction changes. The env is deliberately hard for a small model so we can show improvement over time (0% → 78% success with SFT + GRPO). Four domain skins (Default, Pharmacy, Warehouse, Lab) ground the same mechanics in professional scenarios. Built with OpenEnv 0.2.1, deployed on HF Spaces, trained with HF TRL (GRPO) in Colab

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Markdown version of https://cerebralvalley.ai/e/openenv-hackathon-sf/hackathon/gallery/20. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt