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Commit 54ee7d2

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Merge pull request #17 from sureshmaddina/master
Adding a section called "Path planning with Motion Planning Networks"...
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‎Images/mpnetarchitecture.png‎

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‎README.md‎

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### Robotics
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* [Manipulator Motion Planning](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#manipulator-motion-planning-)
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* [Path Planning with Motion Planning Networks](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#path-planning-with-motion-planning-networks-)
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## Image Classification <a name="ImageClassification"/>
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| Network | Application | Size (MB)| Location|
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| --- | --- | --- | --- |
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| [Deep-Learning-Based CHOMP (DLCHOMP)](https://www.mathworks.com/help/releases/R2024a/robotics/ref/dlchomp.html) | Trajectory Prediction | 25 | [Doc](https://www.mathworks.com/help/releases/R2024a/robotics/ref/dlchomp.html)<br />[GitHub](https://github.com/matlab-deep-learning/pretrained-dlchomp) |
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| [mazeMapTrainedMPNET](https://www.mathworks.com/help/nav/ug/get-started-with-motion-planning-networks.html) | Motion Planning | 0.234 | Doc ([Training](https://www.mathworks.com/help/nav/ug/train-deep-learning-based-sampler-for-motion-planning.html), [Accelerating](https://www.mathworks.com/help/nav/ug/accelerate-motion-planning-with-deep-learning-based-sampler.html))
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[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
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## Path Planning with Motion Planning Networks <a name="PathPlanningMPNet"/>
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Motion Planning Networks (MPNet) is a deep-learning-based approach for finding optimal paths between a start point and goal point in motion planning problems. MPNet is a deep neural network that can be trained on multiple environments to learn optimal paths between various states in the environments. The MPNet uses this prior knowledge to,
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- Generate informed samples between two states in an unknown test environment. These samples can be used with sampling-based motion planners such as optimal rapidly-exploring random trees (RRT*) for path planning.
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- Compute collision-free path between two states in an unknown test environment. MPNet based path planner is more efficient than the classical path planners such as the RRT*.
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To know more please visit [Get Started with Motion Planning Networks](https://in.mathworks.com/help/nav/ug/get-started-with-motion-planning-networks.html)
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![](Images/mpnetarchitecture.png)
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| Network | Application | Size (MB) | Location |
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| ----------------------------------------------------------------------------------------------------------- | ------------- | --------- | ------------------------------------------------------------------------------------------------------- |
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| [mazeMapTrainedMPNET](https://www.mathworks.com/help/nav/ug/get-started-with-motion-planning-networks.html) | Path Planning | 0.23 | [Doc](https://www.mathworks.com/help/nav/ug/train-deep-learning-based-sampler-for-motion-planning.html) |
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[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)
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## Model requests

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