https://www.sciencedaily.com/releases/2019/10/191022124914.htm

To capture the data, the researchers designed an automated system consisting of an industrial robotic arm with precise control, a 3D motion-tracking system, depth and traditional cameras, and software that stitches everything together. The arm pushes around modular objects that can be adjusted for weight, shape, and mass distribution. For each push, the system captures how those characteristics affect the robot's push.

The dataset, called "Omnipush," contains 250 different pushes of 250 objects, totaling roughly 62,500 unique pushes. It's already being used by researchers to, for instance, build models that help robots predict where objects will land when they're pushed.