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LLM-Augmented Robot Navigation
Start
Goal
Start with
a plan
A* algorithm finds an efficient path through a known environment
But the environment
changes!
An unexpected obstacle makes the original path invalid.
Reason and Adapt
An LLM reasoning layer looks at the change and finds a new route.
Environment Update
> obstacle detected
> current path blocked
> analyzing environment...
> evaluating alternate routes...
> replanning
Navigation Complete
Goal reached
Featured Project
LLM-Augmented
LLM-Augmented
Robot Navigation
This is a project I built this year. It's a navigation system combining traditional A* pathfinding with an LLM reasoning layer that adapts when unexpected obstacles invalidate the robot's original route.
View project on GitHub ↗