Benjamin Felbrich's Videos (Grasshopper) - Grasshopper

FlexHopper Intro & Tutorial 1: Cloth Simulation, Collision Objects, Wind, Solver Tuning

2018-01-30T20:24:45.107Z

Welcome to FlexHopper, fast physics simulation in Grasshopper. Written on top of the common language interface FlexCLI, this Grasshopper plugin offers various modes of physics computation within Rhino.
This video shows a brief introduction of FlexHopper's background and explains how to simulate a cloth of approx. 50000 springs, acting under wind an colliding with a sphere. Tuning the solver options is also mentioned.
FlexHopper is constantly maintained and developed open source, here:
https://github.com/HeinzBenjamin/FlexCLI
The user's software package can be downloaded here:
http://food4rhino.com/app/flexhopper
Contact me at:
flexhopper@felbrich.com

Special thanks to Long Nguyen for constant advice and support.

BB8 vs Tie Fighter Swarm in Rhino (C#)

2017-12-20T14:00:26.446Z

BB8 vs a swarm of 100 tie fighters hunting him with their lasers! I added swarm behavior to the fighters so they fly in a formation similar to birds or schools of fish!
Thanks a lot to my friend and colleague Long Nguyen from ICD for animating BB8's belly and head movement a designing the Tatooine landscape (here: youtu.be/9__mU__FGvA)!
Everything done in C# in Rhino and Grasshopper

BB8 bravely fights of 100 Tie Fighters!

2017-12-20T02:31:53.104Z

It's Star Wars time! So why not have some fun and let BB8 be chased by evil tie fighters!
This programming exercise shows a flock of 40 (later 100) mean tie fighters revolving around BB8 and trying to shoot him with their lasers. Flocking behavior But no worries.... BB8 thankfully survives at the end (spoiler alert)
Thanks a lot to my friend and colleague Long Nguyen from ICD for animating BB8's belly and head movement a designing the Tatooine landscape (here: https://youtu.be/9__mU__FGvA)!
Everything done in C# in Rhino and Grasshopper

Crow - Visualisation of Object Classification Network

2017-12-16T16:53:05.301Z

The new ShowCrow feature let's you visualise network training in real time. I hope this will help get a better intuition on how to setup a good network topology.

The object (fruit) classification shown in the example is a very simple use case. Try Crow and use it for more exciting…

Crow Tutorial1: Neural Sensing and Control in Grasshopper

2017-10-10T13:43:45.819Z

Supervised learning is a branch of machine learning in which a mapping function is programmed into a neural network by exposing examples to the network (training).
This tutorial shows how to use the plug in Crow to classify certain environmental states (based on sensor data) and relate them to a parametric model, hence a neural network classifies sensor states and maps them to respective parametric outputs.

All the files can be found here:
https://github.com/HeinzBenjamin/Crow/tree/master/Study%20Material/Supervised%20Learning/Sensor_classification

...and here:
http://www.food4rhino.com/app/crow-artificial-neural-networks