Google's autonomous cars may look cute, like a yuppie cross between a Little Tikes Cozy Coupe and a sheet of flypaper, but to make it in the real world they're going to have to act like calculating predators. At least, that's what a handful of scientists at the Institute of Neuroinformatics at the University of Zurich in Switzerland believe. They recently taught a robot to act like a predator and hunt its prey--which was a human-controlled robot--using a specialized camera and software that allowed the robot to essentially teach itself how to find its mark. The end goal of the work is arguably more beneficial to humanity than creating a future robot bloodsport, however. The researchers aim to design software that would allow a robot to assess its environment and find a target in real time and space.
Some scientists are hard at work making a "kill switch" to overpower a too-strong AI and protect us, if needed. Others are specifically teaching robots how to hunt prey, also to help us. Researchers at the University of Zurich's Institute of Neuroinformatics are teaching a small, truck-shaped robot to see, track, and hunt its prey (another small, truck-shaped robot). The predator robot uses an advanced "silicon retina" to see instead of a traditional camera. This "silicon retina," which is modeled after animals' eyes, uses pixels to smoothly detect changes in real time instead of slowly processing frame-by-frame images.
We joke around a lot about bringing about a horrific robot apocalypse, but let's get real: sometimes, building a killer robot is just the right thing to do. Well, at least when those robots are being used to cull invasive species. Researchers at Robots In Service of the Environment (RISE) are developing a robot to fight an invasive population of Lionfish that's threatening ecosystems off the coast of Florida as well as in the Caribbean and Bermuda. Creating a robot to exterminate a specific species sounds a bit harsh, but it's an environmental issue: the Lionfish population in question isn't native to Caribbean waters, and are don't register as predators to the local wildlife. By decimating the area's food supply, the voracious carnivores are killing coral reef systems and starving other species.
Biological retinas extract spatial and temporal features in an attempt to reduce the complexity of performing visual tasks. We have built and tested a silicon retina which encodes several useful temporal features found in vertebrate retinas.The cells in our silicon retina are selective to direction, highly sensitive to positive contrast changes around an ambient light level, and tuned to a particular velocity. Inhibitory connections in the null direction performthe direction selectivity we desire. This silicon retina is on a 4.6 x 6.8mm die and consists of a 47 x 41 array of photoreceptors.
Both vertebrate and invertebrate retinas are highly efficient in extracting contrastindependent of the background intensity over five or more decades. This efficiency has been rendered possible by the adaptation of the DC operating point to the background intensity whilemaintaining high gain transient responses. The centersurround propertiesof the retina allows the system to extract information atthe edges in the image.