Robot

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