stalhabukhari/comp-sdf-dyn-nav
Code for ICRA'25 paper: "Differentiable Composite Neural Signed Distance Fields for Robot Navigation in Dynamic Indoor Environments"
This project helps robotics engineers and researchers design and test robots that can navigate complex indoor spaces with moving obstacles. It takes detailed 3D environment data and robot movement commands to simulate how a robot can safely move without collisions. The output is a simulation of the robot's path, avoiding both static furniture and dynamic elements like people or other robots.
No commits in the last 6 months.
Use this if you are developing or testing autonomous robots that need to operate reliably and safely in busy, changing indoor environments.
Not ideal if you are looking for a simple path planning tool for static, unchanging environments without the need for advanced collision avoidance with moving objects.
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Language
Python
License
MIT
Category
Last pushed
Apr 02, 2025
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