Update README.md

README.md

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 ## 🔥 Overview
 Recent advancements in Multimodal Large Language Models (MLLMs) have shown remarkable capabilities across various multimodal contexts. However, their application in robotic scenarios, particularly for long-horizon manipulation tasks, reveals significant limitations. These limitations arise from the current MLLMs lacking three essential robotic brain capabilities: **(1) Planning Capability**, which involves decomposing complex manipulation instructions into manageable sub-tasks; **(2) Affordance Perception**, the ability to recognize and interpret the affordances of interactive objects; and **(3) Trajectory Prediction**, the foresight to anticipate the complete manipulation trajectory necessary for successful execution. To enhance the robotic brain's core capabilities from abstract to concrete, we introduce ShareRobot, a high-quality heterogeneous dataset that labels multi-dimensional information such as task planning, object affordance, and end-effector trajectory. ShareRobot's diversity and accuracy have been meticulously refined by three human annotators. Building on this dataset, we developed RoboBrain, an MLLM-based model that combines robotic and general multi-modal data, utilizes a multi-stage training strategy, and incorporates long videos and high-resolution images to improve its robotic manipulation capabilities. Extensive experiments demonstrate that RoboBrain achieves state-of-the-art performance across various robotic tasks, highlighting its potential to advance robotic brain capabilities.
 
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-<img src="https://github.com/FlagOpen/RoboBrain/blob/main/assets/overview.png" />
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+![](https://github.com/FlagOpen/RoboBrain/blob/main/assets/overview.png)
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 ## 🚀 Features
 This repository supports:
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 - **[`A-LoRA for Affordance`](https://huggingface.co/BAAI/RoboBrain-LoRA-Affordance/)**: Based on the Base Planning Model, Stage 4 involves LoRA-based training with our Affordance dataset to predict affordance.
 - **[`T-LoRA for Trajectory`](https://huggingface.co/BAAI/RoboBrain/)**: Based on the Base Planning Model, Stage 4 involves LoRA-based training with our Trajectory dataset to predict trajectory. *(Coming Soon)*
 
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-<img src="https://github.com/FlagOpen/RoboBrain/blob/main/assets/training.png" />
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+![](https://github.com/FlagOpen/RoboBrain/blob/main/assets/training.png)
+<!-- <div align="center">
+<img src="https://github.com/FlagOpen/RoboBrain/blob/main/assets/training.png" width="400"/>
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 | Models               | Checkpoint                                                     | Description                                                | 
 |----------------------|----------------------------------------------------------------|------------------------------------------------------------|
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 ```
 
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+![](https://github.com/FlagOpen/RoboBrain/blob/main/assets/demo/examples.png)
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+<!-- <div align="center">
 <img src="https://github.com/FlagOpen/RoboBrain/blob/main/assets/demo/examples.png" />
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 ### 3. Usage for Trajectory Prediction
 *Coming Soon ...*
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 ## <a id="Evaluation">🤖 Evaluation</a>
 *Coming Soon ...*
 
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+![](https://github.com/FlagOpen/RoboBrain/blob/main/assets/result.png)
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+<!-- <div align="center">
 <img src="https://github.com/FlagOpen/RoboBrain/blob/main/assets/result.png" />
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 ## 😊 Acknowledgement