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Found 3 papers, 2 papers with code
Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks
Large Language Models (LLMs) have been shown to be capable of performing high-level planning for long-horizon robotics tasks, yet existing methods require access to a pre-defined skill library (e. g. picking, placing, pulling, pushing, navigating).
No RL, No Simulation: Learning to Navigate without Navigating
Most prior methods for learning navigation policies require access to simulation environments, as they need online policy interaction and rely on ground-truth maps for rewards.
Habitat 2.0: Training Home Assistants to Rearrange their Habitat
We introduce Habitat 2. 0 (H2. 0), a simulation platform for training virtual robots in interactive 3D environments and complex physics-enabled scenarios.
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