MehdiShahbazi/Webots-reinforcement-navigation
Implementing obstacle avoidance and path planning for the Pioneer 3-DX robot using Python, PyTorch, and the deep reinforcement learning algorithm REINFORCE in the Webots Simulator.
This project helps robotics engineers and researchers develop autonomous mobile robots that can navigate complex environments. You input a simulated environment and a robot model (specifically the Pioneer 3-DX), and it outputs a learned navigation policy that allows the robot to avoid obstacles and reach a destination without collisions. This is ideal for those working on robot control systems and intelligent navigation.
No commits in the last 6 months.
Use this if you are a robotics engineer or researcher experimenting with reinforcement learning to teach mobile robots autonomous navigation and obstacle avoidance in simulated environments.
Not ideal if you are looking for a solution for real-world robot deployment without prior simulation or deep reinforcement learning expertise.
Stars
36
Forks
5
Language
Python
License
MIT
Category
Last pushed
Mar 14, 2024
Commits (30d)
0
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