charbel-a-hC/SKIPP
Repository for the End-to-end Sketch-Guided Path Planning through Imitation Learning for Autonomous Mobile Robots Publication
This project helps roboticists and automation engineers design paths for autonomous mobile robots (AMRs) in complex environments. By taking a sketch-like input of the desired path and information about the robot's surroundings, it generates precise, traversable paths. This is ideal for researchers and engineers working on robot navigation and planning.
No commits in the last 6 months.
Use this if you need to quickly generate and evaluate robot paths based on high-level conceptual sketches rather than precise waypoint programming.
Not ideal if you require real-time, on-the-fly path planning for highly dynamic environments or if your robots operate without any predefined environmental maps.
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Language
Python
License
MIT
Category
Last pushed
Mar 27, 2025
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