How does a robot find its way through a cluttered room? A Rapidly-exploring Random Tree branches outward, quickly filling free space and snaking around obstacles to the goal.
RRT Path PlanningLive
rapidly-exploring random tree
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A Rapidly-exploring Random Tree grows toward random points in free space, quickly filling the map and snaking around obstacles to connect start (blue) to goal (yellow). It is a cornerstone of motion planning for robot arms, self-driving cars, and drones — fast even in high dimensions where grid search fails.
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How it works
RRT grows a tree from the start by repeatedly sampling a random point, extending toward it by a fixed step, and rejecting moves that hit an obstacle. It rapidly explores open space and biases occasionally toward the goal. Fast and effective even in high dimensions, it powers motion planning for robot arms, self-driving cars, and drones.
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The math, the assumptions, real-world uses, or a code translation — explained for this exact simulation.
Yes. RRT Path Planning runs entirely in your browser using your device's own compute, so local use is free forever. You only pay Compute Tokens if you scale a job to the cloud.
Do I need to install anything?▾
No. Everything runs client-side in a modern browser — no downloads, no license, no account required to start.
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How accurate are the results?▾
The solver uses established numerical methods, but results are for research and educational purposes and should be validated against experiment or professional review before you rely on them.