Merge pull request #102 from H-Freax/main

add thinkgrasp

content/publication/Yaoyao(Freax)_Thinkgrasp/cite.bib

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+@inproceedings{
+qian2024thinkgrasp,
+title={ThinkGrasp: A Vision-Language System for Strategic Part Grasping in Clutter},
+author={Yaoyao Qian and Xupeng Zhu and Ondrej Biza and Shuo Jiang and Linfeng Zhao and Haojie Huang and Yu Qi and Robert Platt},
+booktitle={8th Annual Conference on Robot Learning},
+year={2024},
+url={https://openreview.net/forum?id=MsCbbIqHRA}
+}

content/publication/Yaoyao(Freax)_Thinkgrasp/index.md

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+---
+title: "ThinkGrasp: A Vision-Language System for Strategic Part Grasping in Clutter"
+authors: 
+- Yaoyao(Freax) Qian
+- Xupeng Zhu
+- Ondrej Biza
+- Shuo Jiang
+- Linfeng Zhao
+- Haojie Huang
+- Yu Qi
+- Robert Platt
+date: "2024-11-09T00:00:00Z"
+doi: ""
+
+# Schedule page publish date (NOT publication's date).
+publishDate: "2024-07-18T00:00:00Z"
+
+# Publication type.
+# Legend: 0 = Uncategorized; 1 = Conference paper; 2 = Journal article;
+# 3 = Preprint / Working Paper; 4 = Report; 5 = Book; 6 = Book section;
+# 7 = Thesis; 8 = Patent
+publication_types: ["1"]
+
+# Publication name and optional abbreviated publication name.
+publication: In *Conference on Robot Learning 2024*
+publication_short: In *CoRL 2024*
+
+abstract: Robotic grasping in cluttered environments remains a significant challenge due to occlusions and complex object arrangements. We have developed ThinkGrasp, a plug-and-play vision-language grasping system that makes use of GPT-4o's advanced contextual reasoning for heavy clutter environment grasping strategies. ThinkGrasp can effectively identify and generate grasp poses for target objects, even when they are heavily obstructed or nearly invisible, by using goal-oriented language to guide the removal of obstructing objects. This approach progressively uncovers the target object and ultimately grasps it with a few steps and a high success rate. In both simulated and real experiments, ThinkGrasp achieved a high success rate and significantly outperformed state-of-the-art methods in heavily cluttered environments or with diverse unseen objects, demonstrating strong generalization capabilities.
+
+# Summary. An optional shortened abstract.
+summary: 
+
+tags:
+- Source Themes
+featured: true
+
+links:
+- name: Website
+  url: https://h-freax.github.io/thinkgrasp_page/
+url_pdf: https://arxiv.org/abs/2407.11298
+
+# Featured image
+# To use, add an image named `featured.jpg/png` to your page's folder. 
+image:
+  caption: 'Image credit: [**Unsplash**](https://unsplash.com/photos/pLCdAaMFLTE)'
+  focal_point: ""
+  preview_only: false
+
+# Associated Projects (optional).
+#   Associate this publication with one or more of your projects.
+#   Simply enter your project's folder or file name without extension.
+#   E.g. `internal-project` references `content/project/internal-project/index.md`.
+#   Otherwise, set `projects: []`.
+projects:
+- internal-project
+
+# Slides (optional).
+#   Associate this publication with Markdown slides.
+#   Simply enter your slide deck's filename without extension.
+#   E.g. `slides: "example"` references `content/slides/example/index.md`.
+#   Otherwise, set `slides: ""`.
+slides:
+---
+
+
+<!-- Markdown & HTML begins here  -->
+
+<meta http-equiv = "refresh" content = " 0.01 ; url = https://arxiv.org/pdf/1811.12929.pdf"/>
+