Legged robots, robotic systems with legs that typically resemble those of animals or humans, could be advantageous for completing tasks in home environments or populated, dynamic spaces. These robots may look like humans or animals, yet they often cannot reliably replicate complex whole-body movements in a short time.
"Swarms" of cyborg cockroaches with cameras and miniature medical injectors could deliver supervised emergency care to people trapped in collapsed buildings, caves or other places too dangerous for rescuers to reach. The "Paraborgs" developed by University of Queensland biorobotics researchers, working with biomedical engineers at the University of New South Wales (UNSW), move cyborg insects of the future beyond searching for survivors to actively assisting them. The research is published in the journal Advanced Science.
A new, patent-pending underwater robot developed at Purdue University's College of Engineering could improve ocean research, underwater infrastructure inspection and search-and-rescue efforts by adapting to mission needs in real time, acting as a drifter, a glider or a thruster-driven vehicle when necessary.
Propeller-powered underwater vehicles have long helped scientists explore and monitor aquatic environments. But they're limited by their own mechanics: Spinning blades can snag on vegetation, stir up sediment and startle the wildlife they're often sent to study, making them poorly suited to shallow creeks, dense weeds or close encounters with fish.
A Chinese humanoid robot set a new 100-meter sprint record of 8.86 seconds in Beijing on Tuesday, beating its robot competitors — and the fastest recorded human time.
Chinese humanoid robots broke records set by humans, including beating Usain Bolt's 100-meter sprint world record, on the opening day of the Olympics-like World Humanoid Robot Games in Beijing on Saturday.
Cyborg insects combine the mobility of living organisms with miniature electronic devices, offering potential applications in search-and-rescue operations, infrastructure inspection and exploration of environments that are difficult for conventional robots.
To operate reliably in dynamic real-world settings, robots should be able to acquire new skills quickly without undergoing extensive additional training. Most existing robotic systems, however, primarily perform well on the tasks that they were trained to complete.
Robots sorting parcels and serving fried chicken enthralled visitors at a robotics expo in Beijing on Wednesday, where hundreds of companies set out their pitches for a future labor market transformed by artificial intelligence.
A horde of schoolchildren watched excitedly as a diminutive humanoid tour guide named Wuji welcomed them to a robot school in eastern China, gesticulating theatrically as it described the institute's aspiration to train the mechanical workforce of the future.
Shares of Unitree, one of China's largest humanoid robot makers, initially soared as much as 629% in its public stock trading debut Wednesday in Shanghai, in the latest highlight of investor optimism over China's technological advances.
From searching disaster zones and responding to chemical spills to monitoring fragile ecosystems, future robot swarms may have to act in places where direct human control is difficult or dangerous. To operate autonomously, the robots must be able to decide together which problem to address and where to go next. But collective decision-making creates its own vulnerability: Robots improve their decisions by sharing information, yet faulty machines, inaccurate observations or manipulated messages can mislead the entire swarm.
The rules of tag are simple enough for a playground: catch or be caught. But when the players are autonomous drones, the game becomes a test of machine learning, split-second decision-making and cooperative strategy.
A new paper from Monash University and Australia's national science agency, CSIRO, argues that effective human–robot teams depend on alignment: a shared and up-to-date understanding of each teammate's capabilities and limitations, the task and situation, and their respective roles and timing.
The human hand is a dexterous and versatile machine. Scientists have conventionally tried to replicate these traits in robots by copying the biological mechanics of the hand, resulting in complex and difficult-to-control structures. An alternative solution to these challenges was proposed in a new study published in Advanced Science: the BioflexBot, a novel robot that mimics and even exceeds core motions of the hand with a simple design.