Last month, we wrote about autonomous quadrotors from the University of Pennsylvania that use just a VGA camera and an IMU to navigate together in swarms. Without relying on external localization or GPS, quadrotors like these have much more potential to be real-world useful, since they can operate without expensive and complex infrastructure, even indoors.
The vast majority of the fancy autonomous flying we've seen from quadrotors has relied on some kind of external localization for position information. Usually it's a motion capture system, sometimes it's GPS, but either way, there's a little bit of cheating involved. This is not to say that we mind cheating, but the problem with cheating is that sometimes you can't cheat, and if you want your quadrotors to do tricks where you don't have access to GPS or the necessary motion capture hardware and software, you're out of luck.
Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. A new RoboBee from Harvard can swim underwater, and then launch itself into the air with a microrocket and fly away. At the millimeter scale, the water's surface might as well be a brick wall.
In January, we wrote about a cybernetic micro air vehicle under development at Draper called DragonflEye. The backpack interfaces directly with the dragonfly's nervous system to control it, and uses tiny solar panels to harvest enough energy to power itself without the need for batteries. The unique thing about DragonflEye (relative to other cyborg insects) is that it doesn't rely on spoofing the insect's sensors or controlling its muscles, but instead uses optical electrodes to inject steering commands directly into the insect's nervous system, which has been genetically tweaked to accept them. This means that the dragonfly can be controlled to fly where you want, without sacrificing the built-in flight skills that make insects the envy of all other robotic micro air vehicles.
Even aircraft designed to hover, like helicopters and quadrotors, have preferential directions of orientation and travel where their particular arrangement of motors and control surfaces makes them most effective. ETH Zurich's Omnicopter goes about flying in a totally different way. We have developed a computationally efficient trajectory generator for six degrees-of-freedom multirotor vehicles, i.e. The fetching work comes from Dario Brescianini and Raffaello D'Andrea at the Institute for Dynamic Systems and Control (IDSC), ETH Zurich, Switzerland.
If evolution is provided with suitable materials in order to devise the morphology of the robot, morphological computation will emerge, characterized by effective and natural-looking behaviors requiring very little active control. At the same time, our results suggest that automated optimization tools such as evolutionary algorithms should be put in place in order to design soft robots, whose effective behavior usually arises from a complex intertwining of different factors, whose complexity can easily become intractable for a human designer. The aim is to give people with little hardware or software experience a platform to get started and learn how autonomous vehicles work. In this video, we applied our Distributed Iterative Learning Control (ILC) approach to a team of four quadrotors.