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Awesome-LLM-Robotics
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update: add OVSG and LGMCTS

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changhaonan 2023-11-05 15:24:07 -05:00
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@ -44,7 +44,7 @@ If you find this repository useful, please consider [citing](#citation) and STAR
--- ---
## Planning ## Planning
* **LGMCTS**: "LGMCTS: Language-Guided Monte-Carlo Tree Search for Executable Semantic Object Rearrangement", *arXiv, Sep 2023*. [[Paper](https://arxiv.org/abs/2309.15821)]
* **Prompt2Walk**: "Prompt a Robot to Walk with Large Language Models", *arXiv, Sep 2023*, [[Paper](https://arxiv.org/abs/2309.09969)] [[Website](https://prompt2walk.github.io)] * **Prompt2Walk**: "Prompt a Robot to Walk with Large Language Models", *arXiv, Sep 2023*, [[Paper](https://arxiv.org/abs/2309.09969)] [[Website](https://prompt2walk.github.io)]
* **DoReMi**: "Grounding Language Model by Detecting and Recovering from Plan-Execution Misalignment", *arXiv, July 2023*, [[Paper](https://arxiv.org/abs/2307.00329)] [[Website](https://sites.google.com/view/doremi-paper)] * **DoReMi**: "Grounding Language Model by Detecting and Recovering from Plan-Execution Misalignment", *arXiv, July 2023*, [[Paper](https://arxiv.org/abs/2307.00329)] [[Website](https://sites.google.com/view/doremi-paper)]
* **LLM+P**:"LLM+P: Empowering Large Language Models with Optimal Planning Proficiency", *arXiv, Apr 2023*, [[Paper](https://arxiv.org/abs/2304.11477)] [[Code](https://github.com/Cranial-XIX/llm-pddl)] * **LLM+P**:"LLM+P: Empowering Large Language Models with Optimal Planning Proficiency", *arXiv, Apr 2023*, [[Paper](https://arxiv.org/abs/2304.11477)] [[Code](https://github.com/Cranial-XIX/llm-pddl)]
@ -123,7 +123,7 @@ If you find this repository useful, please consider [citing](#citation) and STAR
--- ---
## Instructions and Navigation ## Instructions and Navigation
* **OVSG**: "Context-Aware Entity Grounding with Open-Vocabulary 3D Scene Graphs", *CoRL, Nov 2023*. [[Paper](https://openreview.net/forum?id=cjEI5qXoT0)] [[Code](https://github.com/changhaonan/OVSG)] [[Website](https://ovsg-l.github.io/)]
* **ADAPT**: "ADAPT: Vision-Language Navigation with Modality-Aligned Action Prompts", *CVPR, May 2022*. [[Paper](https://arxiv.org/abs/2205.15509)] * **ADAPT**: "ADAPT: Vision-Language Navigation with Modality-Aligned Action Prompts", *CVPR, May 2022*. [[Paper](https://arxiv.org/abs/2205.15509)]
* "The Unsurprising Effectiveness of Pre-Trained Vision Models for Control", *ICML, Mar 2022*. [[Paper](https://arxiv.org/abs/2203.03580)] [[Pytorch Code](https://github.com/sparisi/pvr_habitat)] [[Website](https://sites.google.com/view/pvr-control)] * "The Unsurprising Effectiveness of Pre-Trained Vision Models for Control", *ICML, Mar 2022*. [[Paper](https://arxiv.org/abs/2203.03580)] [[Pytorch Code](https://github.com/sparisi/pvr_habitat)] [[Website](https://sites.google.com/view/pvr-control)]
* **CoW**: "CLIP on Wheels: Zero-Shot Object Navigation as Object Localization and Exploration", *arXiv, Mar 2022*. [[Paper](https://arxiv.org/abs/2203.10421)] * **CoW**: "CLIP on Wheels: Zero-Shot Object Navigation as Object Localization and Exploration", *arXiv, Mar 2022*. [[Paper](https://arxiv.org/abs/2203.10421)]