Humans have long been known to sympathize with the machines or computer representations they operate. Whether driving a car or directing a video game avatar, people are more likely to identify with something that they feel in control of. However, how the autonomous behavior of the robots affects their operators is not known. Now, researchers from Japan have found that when a person controls only a part of the body of a semi-autonomous robot, they are influenced by the robot's expressed "attitudes."
Research teams at the University of Tokyo, Keio University and Toyohashi University of Technology in Japan have developed a virtual robotic limb system which can be operated by users' feet in a virtual environment as extra, or supernumerary, limbs. After training, users reported feeling like the virtual robotic arms had become part of their own body. Published in Scientific Reports, this study focused on the perceptual changes of the participants, understanding of which can contribute to designing real physical robotic supernumerary limb systems that people can use naturally and freely just like our own bodies.
Magnetic technology mounted on drones can identify mines and unexploded munitions on land and at sea much more effectively than conventional mine clearance using handheld detectors. The DTU spinout company Umag Solutions has developed an ultra-precise drone magnetometer technology, and documented that in just a few days it can cover an area that either cannot be covered in conventional mine clearance operations or that it would take a month to cover.
The inner child in many of us feels an overwhelming sense of joy when stumbling across a pile of the fluorescent, rubbery mixture of water, salt, and flour that put goo on the map: play dough. (Even if this happens rarely in adulthood.)
An international team of scientists, led by the University of Leeds, have assessed how robotics and autonomous systems might facilitate or impede the delivery of the UN Sustainable Development Goals (SDGs).
As robots are gradually introduced into various real-world environments, developers and roboticists will need to ensure that they can safely operate around humans. In recent years, they have introduced various approaches for estimating the positions and predicting the movements of robots in real-time.
Autonomous robots have come a long way since the fastidious Roomba. In recent years, artificially intelligent systems have been deployed in self-driving cars, last-mile food delivery, restaurant service, patient screening, hospital cleaning, meal prep, building security, and warehouse packing.
A robot operating with a popular Internet-based artificial intelligence system consistently gravitates to men over women, white people over people of color, and jumps to conclusions about peoples' jobs after a glance at their face.
In late May, NTNU researchers and students used a small satellite, an unmanned aerial vehicle, two unmanned boats and subsea robots to survey the same area simultaneously. This is an approach called an observational pyramid.
Uncrewed aircraft responding to fire and medical emergencies will be used to save lives—if digitalized air-traffic control can help them navigate safely in the skies over Europe.
Fireflies that light up dusky backyards on warm summer evenings use their luminescence for communication—to attract a mate, ward off predators or lure prey.
As robots make their way into a variety of real-world environments, roboticists are trying to ensure that they can efficiently complete a growing number of tasks. For robots that are designed to assist humans in their homes, this includes household chores, such as cleaning, tidying up and cooking.
A team of UCLA engineers and their colleagues have developed a new design strategy and 3D printing technique to build robots in one single step.
A team of researchers at Tsinghua University's Center for Brain-Inspired Computing Research in Beijing, China, has developed a neuromorphic chip that can reduce the power consumption of a cat-and-mouse-type rolling robot by approximately half, compared to a conventional NVIDIA chip designed for AI applications. In their paper published in the journal Science Robotics, the group describes design concepts they used to build the chip and how well it worked when tested.
Just like us, robots can't see through walls. Sometimes they need a little help to get where they're going.