Professor Sukho Song of the Department of Robotics and Mechatronics Engineering at DGIST has proposed "Sustainability Robotics," a new academic field that evaluates robots not only in terms of their technical performance but also their contributions to environmental, social and economic sustainability.
When a robot offers you candy, it is hard not to be curious. In an experiment conducted by ethologists at ELTE, visitors at public events noticed an autonomous service robot more often than a human server, and the candy on the robot's tray disappeared faster. The study also suggests that the presence of robots may influence the way people behave in social situations.
From the Ferranti Mark I to empathetic AI, Manchester researchers are exploring how intelligent machines can understand human behavior, respond to social cues and earn trust in our workplaces, hospitals and homes.
For robots to be used in various settings, such as factories, logistics, service industries and households, they must be able to stably handle a diverse range of objects differing in shape, size, weight and rigidity. However, conventional robotic hands often require multiple motors and complex control systems, presenting challenges in terms of weight, cost, failure risk and control difficulties.
An era in which robots decide "how to walk" on their own has arrived. A four-legged robot has been developed that, much like a person or an animal, autonomously chooses the appropriate gait strategy for its surroundings—changing its gait on stairs, leaping over gaps and keeping its balance on forest trails.
Japanese communications company Fujitsu is leading a major push in artificial intelligence using Nvidia's technology, bringing together what it said was the best in Japan's manufacturing prowess in robotics with AI.
Robots walking down the street, surrounded by astounded onlookers, are an increasingly common sight. But these machines aren't yet the do-it-all assistants you'd want working in a kitchen or factory, and a major bottleneck is data. Much like humans, robots learn best by experience. The challenge is that it's labor-intensive and time-consuming to physically teach these machines so many actions across different settings.
When South Korea's professional baseball league introduced "robot umpire" ball-and-strike calls in 2024, famous batters appeared to lose an edge—but star pitchers did not.
Built from flexible, compliant materials, soft robots are gaining relevance for tasks ranging from minimally invasive surgery to deep-sea exploration but remain held back by a fundamental constraint. To sense their surroundings and react, most soft robots rely on separate electronic sensors, signal-processing circuits and powered actuators, all coordinated by computers. This chain of components adds weight, complexity and points of failure, particularly in wet, hot or high-pressure settings where electronics are highly susceptible to disruption.
As technology advances, more is expected from humanoid robots. What were once seen as gimmicks that could walk, if not like us, then close to it, are now pulling their weight and doing more work in places like factories. They are being developed for real work, such as carrying heavy boxes, pushing furniture, pulling heavy objects and wiping tables.
Robotics researchers often spend weeks, or even months, simply getting a new robot up and running before they can begin testing new behaviors. Researchers in the Carnegie Mellon University School of Computer Science have developed an open-source software framework designed to eliminate much of that setup work, making it easier to deploy AI systems across different robots without rebuilding software from scratch.
Robotics researchers often spend weeks, or even months, simply getting a new robot up and running before they can begin testing new behaviors. Researchers in the Carnegie Mellon University School of Computer Science have developed an open-source software framework designed to eliminate much of that setup work, making it easier to deploy AI systems across different robots without rebuilding software from scratch.
Most people think of the waterfront as the edge of the city. A team of MIT researchers sees it as a dynamic, Lego-like construction site. Their new system, called "FloatForm," is a swarm of small square robotic boats that assemble themselves into larger structures on the water, break apart and reassemble into something new, all with minimal human direction.
Loons, gulls, puffins and petrels are some of the 100 species of birds that can both fly and swim. These diving birds can plunge into water to swim after prey, and leap back into the air to fly away.
Walking robots, such as quadruped robotic dogs, must be able to move safely through rough, often changing environments. Today, there are two main ways to program these walking, or legged, robots. The first is called model predictive control. This technique optimizes the robot's behavior but relies on accurate dynamics models, which are challenging to achieve in real-world settings and often require simplifying assumptions. The second is model-free reinforcement learning, which allows the robot to learn reliable but fixed behaviors, making them difficult to adapt after training.