A little over a year ago, we wrote about some clumsy-looking but really very clever research from Vijay Kumar's lab at the University of Pennsylvania. That project showed how small drones with just protective cages and simple sensors can handle obstacles by simply running into them, bouncing around a bit, and then moving on. The idea is that you don't have to bother with complex sensors when hitting obstacles just doesn't matter, which bees figured out about a hundred million years ago. Over the past year, Yash Mulgaonkar, Anurag Makineni, and Luis Guerrero-Bonilla (all in Kumar's lab) have come up with a bunch of different ways in which smashing into obstacles can actually be a good and useful thing. From making maps to increased agility to (mostly) on purpose payload deployment, running into stuff and bouncing off again can somehow do it all. You can read more about the non-collision avoidance that these drones have going on in our previous article, but it's essentially as simple as ignoring collisions while relying on a roll cage (made out of heat-cured carbon fiber yarn) modeled after the general shape of a gömböc, which is maybe my favorite shape ever. Right now, this all requires an external motion-capture system to work, and the computation isn't done on the robots either, meaning that it'll work in a comfortably equipped robotics lab but not anywhere particularly useful. The good news is that the researchers are working on on-board localization and visual odometry, and we're pretty sure that they'll make it happen. They're pretty sure too, and the paper promises that "the ideas described in this paper can be realized on independent robots with cameras and IMUs within the next year or two."