Bewegungsfelder Is A Wireless IMU Motion Capturing System

For several years, hackers have been exploring inertial measurement units (IMUs) as cheap sensors for motion capturing. [Ivo Herzig’s] final Diploma project “Bewegungsfelder” takes the concept of IMU-based MoCap one step further with a freely configurable motion capturing system based on strap-on, WiFi-enabled IMU modules.

The Bewegungsfelder system consists of multiple, ESP8266-powered standalone IMU sensor nodes and a motion capturing server. Attached to a person’s body (or anything else) the nodes wirelessly stream the output of their onboard MPU6050 6-axis accelerometer/gyroscope to a central motion capturing server. A server application translates the incoming data into skeletal animations, visualizes them as a live preview and stores the MoCap data for later use. Because the sensor nodes are entirely self-contained, they can be easily reconfigured to any skeletal topology, be it a human, a cat, or an industrial robot.

robocap

[Ivo] already included support for custom skeleton definitions, as well as BVH import/export to use the generated data in commonly used tools like Blender of Maya. The software portion of the project is released as open source under MIT License, with both the firmware and the server application code being available on GitHub. According to [Ivo], these nodes can be built for as few as $5, which puts them in a sweet price range for AR/VR applications — or for making your own cartoons.

mocap-opti

20 thoughts on “Bewegungsfelder Is A Wireless IMU Motion Capturing System

    1. Looks like its just a veroboard hooking your run of the mill ESP-12 to your run of the mill MPU6050 breakout over I2C. You could probably make the schematic in ASCII art pretty quickly :p

  1. This tech can be used to record all of your movements over an extended period of time so that the data set could be provided to a neural network to jump-start robot motion training. i.e. You give it a large set of successful motions from the complete set of possible motions. You can construct Markov relationships between poses, this would let the robot move around randomly but constrained and biased by the recorded motion data. This would result in the motion being choreographically valid, and sometimes even meaningful to an observer, in the same way that Markov chains can be used to generate text that is “readable” if mostly nonsense.

          1. It is NASA who are stupid, they made a robot to go in the space station and gave it arms and legs, FFS all it needs is 4 arms because it can’t walk anywhere anyway! Try arguing with that you wanker, actually I expect you will because you are a pathetic troll who doesn’t actually know what I was talking about. The only fallacy here is your pseudo scientific verbal diarrhoea.

  2. I think I need to make a batch of these, and track down my old Taijiquan instructor. He was trying to get this kind of data working with a university, with access to mo-cap and other tools; he and I both wondered how certain disabilities and joint/muscle problems impacted the way people walked through the forms. Something like this would be a huge step from the method I last heard was being worked on: using a WiiFit balance board to compare total weight (measure at start) to weight distribution (one foot on the board while in a pose), with WiiMotes in hands to get positional data. They were recording reference with the bigger tools, but wanted a low-cost method to get a gamified version to end-users.

  3. there are so many projects like this out there. Problem usually isn’t building the hardware, but getting EMI under control and the horrible drift most (cheap) IMU show. I know that Xsense, for example, invest far more money into their software development than into their hardware dep.

    1. looking at the data viz of the “dancing woman” … there’s a lot left to do about the software. Ground contact control for starters. Catch drifting feet. Yeah … like I said above. The hardware part’s the easy one. Nailing the software is where the money burns.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s