Hackable motion cueing for the 21st Century
Don't buy a new Simulator
Did you know that the majority of simulators aren't used to their full potential? Simulator vendors want you to believe that replacement is the only option.
However, many otherwise good simulators are let down by their motion cueing algorithm. Said algorithm can be replaced at very low cost, in many cases completely transforming the motion experience.
Reclaim
... your simulator. Minimise time wasted on tuning cueing systems and safety stops due to bad tuning. Maximise productivity with a state-of-the-art, multithreaded optimiser. Perform massive parameter sweeps split across many cores.
Maximise cueing quality. Happy drivers, more accurate insights, superior translation to the real-world.
Experiment with alternative Motion Control Algorithm (MCA's), shipped with ProCue. We read (and occasionally write) the academic papers, so you don't have to.
Everything you would expect
Globally Optimal
Demolish even the trickiest motion cueing optimisation problems with our derivative-free, local optima resistant solver.
Maximal compute
Whether a manual parameter sweep or a large scale optimisation, ProCue will make full use of all your CPU cores.
Illuminating feedback
Plot and compare an arbitrary number of motion cueing algorithms together. Compare platform accelerations to those perceived by the driver.
Arbitrary workspace
Thanks to the power of our solver, workspaces can be of arbitrary shape. Incorporate multiple, layered speed, acceleration and jerk limits as a function of position.
Alternative MCA's
Deploy ProCue's alternative MCA's to your simulator, shipped as compilable Simulink models.
Experiment Management
Manage the many permutations of scenario(s), MCA('s) and driver(s). Detect accidental changes with in-built "Git-like" traceability. Plain text JSON storage for ease of version control.
You're the Expert
MCA's
Incorporate and share your own motion cueing algorithms. Simple compilation process from Simulink leading to completely stand-alone MCA at run-time.
Drivers
Incorporate and share your own perception models. Simple compilation process from Simulink leading to completely stand-alone perception model at run-time.
Workspaces
Write arbitrary workspaces as a simple Python module. Carry out simulator studies before a simulator is even purchased/built.
Optimise your Optimiser
Customise your optimisation. Separate constants from tunable variables. Link axes for symmetrical cueing and save computing time. Or leave everything up to the optimiser!
Supporting academic research
BrownSim is committed to academic research. Be part of the BrownSim community or help improve your favorite cueing software.
Keep in touch
| in/craigrobertbrown | |
| craig.brown@brownsim.io |