There have been many attempts at teaching robots how to grab delicate objects, but they tend to rely on rough approximations that quickly fall apart in real life. MIT researchers may have a better solution: teach robots to predict how even the squishiest items will react to their touch. They've developed a "learning-based" particle simulation system that helps robots refine their approach. The new model captures how small pieces of a given material (the "particles" in question) react to touch, and learns from that information when the physics of a given interaction aren't clear. It's akin to how humans intuitively understand grip -- we already have ideas based on our personal understanding of physics.