How fresh are your data? For drones searching a disaster zone or robots inspecting a building, working with the freshest data is key to locating a survivor or reporting a potential hazard. But when multiple robots simultaneously relay time-sensitive information over a wireless network, a traffic jam of data can ensue. Any information that gets through is too stale to consider as a useful, real-time report.
Humans innately learn to adapt their movements based on the materials they are handling and the tasks that they are trying to complete. When chopping specific fruits or vegetables, for instance, they might learn to cut around harder parts, such as avocado or peach seeds, or carefully eliminate the outer skin.
In recent years, computer scientists have developed increasingly advanced algorithms for controlling the movements of robotic agents. These include model predictive control (MPC) techniques, which use a model of the agent's dynamics to optimize its future behavior toward a given goal while simultaneously satisfying a number of constraints (e.g., cannot crash into obstacles).
A review paper by scientists at the Beijing Institute of Technology summarized recent efforts and future potential in the use of in vitro biological neural networks (BNNs) for the realization of biological intelligence, with a focus on those related to robot intelligence.
If you've ever wondered what a lack of diversity in robotics looks like, just do a Google image search for "humanoid robot" and check out the simulated skin color of the thousands of robots that fill your screen. (Hint: it's white.)
Carnegie Mellon University engineers have developed a soft material with metal-like conductivity and self-healing properties that is the first to maintain enough electrical adhesion to support digital electronics and motors. This advance, published in Nature Electronics, marks a breakthrough in softbotics and the fields of robotics, electronics, and medicine.
A team of researchers, led by Matthew Gombolay, an assistant professor in the School of Interactive Computing and director of the Cognitive Optimization and Relational (CORE) Robotics Lab at Georgia Tech, are using the sport of table tennis to showcase that humans may not always trust a robot's explanation of its intended action.
Roboticists have developed many advanced systems over the past decade or so, yet most of these systems still require some degree of human supervision. Ideally, future robots should explore unknown environments autonomously and independently, continuously collecting data and learning from this data.
It isn't just artists and teachers who are losing sleep over advances in automation and artificial intelligence. Robots are being brought into Hinduism's holiest rituals—and not all worshippers are happy about it.
It isn't just artists and teachers who are losing sleep over advances in automation and artificial intelligence. Robots are being brought into Hinduism's holiest rituals—and not all worshippers are happy about it.
Robots are all around us, from drones filming videos in the sky to serving food in restaurants and diffusing bombs in emergencies. Slowly but surely, robots are improving the quality of human life by augmenting our abilities, freeing up time, and enhancing our personal safety and well-being. While existing robots are becoming more proficient with simple tasks, handling more complex requests will require more development in both mobility and intelligence.
Recently, a research team from Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, proposed a bionic quadruped soft thin-film microrobot actuated by magnetic fields with a mass of only 41 mg, which promises to be applied to stomach examination and treatment. Researchers realized the multimodal locomotion control of the soft microrobot in magnetic fields and the grasping and transportation of micro-objects by the soft microrobot.
Researchers from North Carolina State University and Iowa State University have demonstrated an automated technology capable of accurately measuring the angle of leaves on corn plants in the field. This technology makes data collection on leaf angles significantly more efficient than conventional techniques, providing plant breeders with useful data more quickly.
Robotics specialists from a group led by ETH professor Raffaello D'Andrea have created a new, cube-shaped robot that can balance on its pivot and compensate for external disturbances. What makes the One-Wheel Cubli unique? Unlike its predecessors, it only requires a single reaction wheel.
Researchers from Bochum and Saarbrücken have detected security vulnerabilities, some of them serious, in several drones made by the manufacturer DJI. These enable users, for example, to change a drone's serial number or override the mechanisms that allow security authorities to track the drones and their pilots. In special attack scenarios, the drones can even be brought down remotely in flight.