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Use case · powered by Mobile Robot Navigation

Mobile Robot Navigation for a surgical robot

Simulate a surgical robot live in your browser. This runs the real Mobile Robot Navigation solver — adjust the inputs, watch it respond instantly, and export the result. No install, no account.

1

Differential Drive

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Differential Drive RobotLive

Controls

Presets

A differential-drive robot steers by spinning its two wheels at different speeds — like a tank. Equal speeds go straight, a difference curves the path, and opposite speeds spin in place. Its forward speed is the average of the wheels and its turn rate is their difference over the wheelbase.

▶ Run in Python

Data Inspector

Forward v2.50
Turn rate ω0.030
Turn radius83

Governing equation

Reading this result: The faster right wheel pushes the robot into an arc that curves toward the slower left side, with radius set by how close the two speeds are.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

2

RRT Path Planning

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RRT Path PlanningLive

Controls

Presets

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.

▶ Run in Python

Data Inspector

Tree nodes0
Path foundno
Path length0

Governing equation

Reading this result: No path yet at step 18 — the tree ran out of iterations before reaching the goal. Try Replan or a smaller step.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

3

Kalman Filter

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Kalman FilterLive

Controls

Presets

The Kalman filter fuses a motion model with noisy measurements to track a hidden state optimally. Each step it predicts, then corrects using the Kalman gain — trusting the measurement more when the model is uncertain, and vice versa. It smooths the jittery sensor (gray) into a clean estimate (cyan) that hugs the truth. The math behind GPS, radar, and spacecraft navigation.

▶ Run in Python

Data Inspector

Measurement RMSE0.0
Kalman RMSE0.0
Noise reductionNaN%

Governing equation

Reading this result: Measurement noise dwarfs process noise, so the Kalman gain stays small — the filter leans on its motion model and smooths the jitter hard.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

or unlock everything with Pro →

About this simulation

The full Mobile Robot Navigation tool models a surgical robot with the same numerics engineers and scientists use — running entirely client-side. Change any parameter and the result updates in real time, so you can build intuition, check a design, or teach the concept without spreadsheets or installs.

More you can do with Mobile Robot Navigation

Other ways to simulate a surgical robot

Frequently asked questions

How do I simulate a surgical robot?
Open this page and use the live Mobile Robot Navigation tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.
Is it free?
Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.
Can I use my own numbers?
Absolutely — every input is adjustable, and with data import you can drive a surgical robot from your own measurements.