motion_planning
PathPlanning
motion_planning | PathPlanning | |
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1 | 2 | |
311 | 7,399 | |
- | - | |
4.3 | 0.0 | |
3 months ago | over 1 year ago | |
Jupyter Notebook | Python | |
MIT License | MIT License |
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motion_planning
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Trouble with importing modules
This is the GitHub page: https://github.com/RuslanAgishev/motion_planning/blob/master/python_src/adaptive_formation/gradient_interactive.py
PathPlanning
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Can you please recommend me some resources on D* algorithm?
There is also a github repo I starred a while back that has a good amount of path planning algorithms in python, D* included: https://github.com/zhm-real/PathPlanning
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How to implement concurrent motion planning algorithms?
Do you need available algorithms in C++? Just Google "GitHub path planning algorithms C++". Otherwise, I do research on these algorithms and know about a good GitHub here: In Python. I recommend adding visualizations, random generator seeding, and unit tests that compare algorithms to make sure you've implemented them all correctly. Let me know if you need good papers, but in particular I like an RRT variant by Sidd Srinivasa's group from 2014. Original RRT papers are from LaValle
What are some alternatives?
Fields2Cover - Robust and efficient coverage paths for autonomous agricultural vehicles. A modular and extensible Coverage Path Planning library
Dstar-lite-pathplanner - Implementation of the D* lite algorithm in Python for "Improved Fast Replanning for Robot Navigation in Unknown Terrain"
fields2cover_ros - A ROS interface of Fields2Cover
multi_agent_path_planning - Python implementation of a bunch of multi-robot path-planning algorithms.
euler - A distributed graph deep learning framework.
PythonRobotics - Python sample codes for robotics algorithms.
progress - Easy to use progress bars for Python
openwebrx - Open source, multi-user SDR receiver software with a web interface
volesti - Practical volume computation and sampling in high dimensions
MT-RRT - General purpose library for multithreaded Rapidly Random exploring Trees