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Neural MP is a machine learning-based motion planning system for robotic manipulation tasks. It combines neural networks trained on large-scale simulated data with lightweight optimization techniques to generate efficient, collision-free trajectories. Neural MP is designed to generalize across diverse environments and obstacle configurations, making it suitable for both simulated and real-world robotic applications. This repository contains the model weights for Neural MP.
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All Neural MP checkpoints, as well as our [
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For full details, please read our [paper](https://mihdalal.github.io/neuralmotionplanner/resources/paper.pdf) and see [our project page](https://mihdalal.github.io/neuralmotionplanner/).
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Neural MP is a machine learning-based motion planning system for robotic manipulation tasks. It combines neural networks trained on large-scale simulated data with lightweight optimization techniques to generate efficient, collision-free trajectories. Neural MP is designed to generalize across diverse environments and obstacle configurations, making it suitable for both simulated and real-world robotic applications. This repository contains the model weights for Neural MP.
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All Neural MP checkpoints, as well as our [codebase](https://github.com/mihdalal/neuralmotionplanner) are released under an MIT License.
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For full details, please read our [paper](https://mihdalal.github.io/neuralmotionplanner/resources/paper.pdf) and see [our project page](https://mihdalal.github.io/neuralmotionplanner/).
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