PPolySim OS
Use case · powered by Robot Arm Controller

Robot Arm Controller for a mobile rover

Simulate a mobile rover live in your browser. This runs the real Robot Arm Controller solver — adjust the inputs, watch it respond instantly, and export the result. No install, no account.

1

Forward Kinematics

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Forward KinematicsLive

Controls

Presets

Forward kinematics computes where a robot arm's tip ends up from its joint angles. Each link rotates relative to the previous one, so the transforms chain together. It is fast and unique — every set of angles gives exactly one end-effector position — which is why controllers use it constantly.

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Data Inspector

End X172.2
End Y110.4
Reach204.6
Links3

Governing equation

Reading this result: Reach 205 sits near the 210 maximum: the three links are nearly collinear, so the arm is almost fully extended.

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

2

Inverse Kinematics

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Inverse KinematicsLive

Controls

Presets

Inverse kinematics is the hard direction: given where you want the tip, find the joint angles. For a 2-link arm the law of cosines gives a clean closed form — but with two solutions (elbow-up or elbow-down) and none at all when the target is out of reach. Drag the target, or click anywhere to move it there.

▶ Run in Python

Data Inspector

Joint 1-20.8°
Joint 291.4°
Target dist126
Total reach180
Reachableyes

Governing equation

Reading this result: This 2-link arm (segments 100 and 80, total reach 180) has a closed-form inverse: the law of cosines gives the joint angles that place the tip exactly on the target, with two branches — elbow-up and elbow-down. Iterative methods like CCD or the Jacobian transpose converge to one of them.

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

PID ControllerLive

Controls

Presets

A PID controller drives a system to its setpoint using three terms: proportional reacts to the current error, integral eliminates steady-state offset, and derivative damps overshoot. Tuning the three gains trades off speed, overshoot, and stability — the workhorse of industrial control.

▶ Run in Python

Data Inspector

Overshoot0%
Settling time0.00 s
Steady-state error0.000

Governing equation

Reading this result: Balanced gains — proportional for speed, integral to remove offset, derivative to damp overshoot: the textbook well-tuned response.

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

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About this simulation

The full Robot Arm Controller tool models a mobile rover 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 Robot Arm Controller

Other ways to simulate a mobile rover

Frequently asked questions

How do I simulate a mobile rover?
Open this page and use the live Robot Arm Controller 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 mobile rover from your own measurements.