Vansh404/PathPlanning_withRL

Using Q-Learning Control for path planning of mobile agents in an enviroment.

14
/ 100
Experimental

This project helps robotics engineers and automation specialists efficiently program mobile robots to navigate complex environments. It takes information about the robot's surroundings and desired destination, and outputs an optimized path, ensuring the robot reaches its goal effectively. It's ideal for anyone responsible for deploying or managing autonomous mobile agents.

No commits in the last 6 months.

Use this if you need to quickly determine efficient, collision-free routes for robots in a dynamic or unknown space.

Not ideal if you require path planning for non-mobile entities or for situations where learning an optimal path over time is not feasible.

robotics automation motion-planning robot-navigation AI-control-systems
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 0 / 25

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Language

Python

License

Last pushed

Oct 28, 2022

Commits (30d)

0

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