Welcome to robotics research and development
Scientists at the US Army Research Laboratory (ARL) and the Johns Hopkins University Applied Physics Laboratory (JHU) have developed software to ensure that if a robot falls, it can get itself back up. This means future military robots will be less reliant on their soldier handlers. Based on feedback from soldiers at an Army training…
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The image recognition technology that underlies today’s autonomous cars and aerial drones depends on artificial intelligence: the computers essentially teach themselves to recognize objects like a dog, a pedestrian crossing the street or a stopped car. The problem is that the computers running the artificial intelligence algorithms are currently too large and slow for future…
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Engineers have 3D printed a physical artificial neural network that can analyze large volumes of data and identify objects at the actual speed of light. Developed at the UCLA Samueli School of Engineering the “diffractive deep neural network” uses the light bouncing from the object itself to identify that object in as little time as…
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Advanced Robotics for Manufacturing (ARM) has selected eight technology projects and six workforce development projects resulting from ARM’s first formal project call that was announced in October 2017. The 14 ARM projects have been selected for funding and will kick-off in the coming months, pending final contract negotiations. It’s expected that about $5.4 million in total…
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Researchers at MIT, who in 2017 designed a tiny computer chip called “Navion” to help honeybee-sized drones navigate, have now shrunk the chip design even further, both in size and power consumption. Navion is just 20 square millimeters in size and consumes just 24 milliwatts of power. However, the Navion chip is still able to process in real-time…
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Researchers from the Wyss Institute for Biologically Inspired Engineering at Harvard University and the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have shown how a multi-layered structure can allow robots to mimic an octopus’ kinematics, creating and eliminating joints on command. The structure can also allow robots to rapidly change their…
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Navigating roads less traveled in self-driving cars is a difficult task. One reason is that there aren’t many places where self-driving cars can actually drive. Companies like Google only test their fleets in major cities where they’ve spent countless hours meticulously labeling the exact 3-D positions of lanes, curbs, off-ramps, and stop signs. “The cars…
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One of the major challenges in the robotics industry is creating robots that are inspired by nature. This is no easy task, of course, and many of the major challenges associate with creating bio-inspired robots haven’t changed in years. Materials that couple sensing, actuation, computation, and communication must be developed before bio-inspired robots take off. And…
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