James Bruton Built Motion Capture Rigs for His Animatronic Robots

Cameron Coward
22 days agoRobotics

You can build a complex robot or animatronic with many motors and degrees of freedom, but that’s only half of the battle. You also need a way to control or program their motions. At the lowest level, you can explicitly program motor movement commands. However, that quickly becomes a laborious task if you want a lot of motions. Many people use animation software that lets them assign movements, but that’s still more cumbersome than it needs to be. The best solution, which James Bruton is using for his robots, is to create a scaled-down motion capture rig.

The two humanoid robots that Bruton built are quite large — essentially the same size as a typical man’s torso. They are very robust, and fully capable of acting as animatronic actors. Those robots are quite impressive in their own right, but the motion capture rigs that Bruton is using to program them are also very interesting. Those rigs look like miniature versions of the full-size robots and are posable. All Bruton has to do is move the joints on the rigs, and the robots will mimic the motions. Those motions can be saved and repeated, or Bruton can operate the robots in real-time like a puppeteer.

Each of the rigs is made up of 3D-printed mechanical parts, and simple potentiometers make up each joint. An Arduino is used to monitor the resistance of each potentiometer, which translates into a motor position for the full-sized robots. Bruton does admit that potentiometers may not be the best component for the job, as they’re under mechanical load and can wear out eventually. Bearings and rotary encoders are a better alternative, but also more expensive. For the time being, however, they do work quite well. In his newest video, Bruton demonstrates a head design he made for his robots. He should be able to use the same motion capture rigs to control those heads as well. Best of all, the robots and motion capture rigs are open-source, so you can build them yourself!

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