In recent years, roboticists have created a growing number of autonomous systems based on different structures and designs. Among these are modular robots, which are composed of different elements or "modules" that can be reconfigured to carry out specific tasks more effectively.
Different people tend to have unique needs and preferences—particularly when it comes to cleaning or tidying up. Home robots, especially robots designed to help humans with house chores, should ideally be able to complete tasks in ways that account for these individual preferences.
Poems, essays and even books—is there anything the open AI platform ChatGPT can't handle? These new AI developments have inspired researchers at TU Delft and the Swiss technical university EPFL to dig a little deeper: For instance, can ChatGPT also design a robot? And is this a good thing for the design process, or are there risks? The researchers published their findings in Nature Machine Intelligence.
A simple sponge has improved how robots grasp, scientists from the University of Bristol have found.
A research collaboration between Cornell and the Max Planck Institute for Intelligent Systems has found an efficient way to expand the collective behavior of swarming microrobots: Mixing different sizes of the micron-scale 'bots enables them to self-organize into diverse patterns that can be manipulated when a magnetic field is applied. The technique even allows the swarm to "cage" passive objects and then expel them.
Our newsfeeds are filled with talk about the rapid rise of artificial intelligence (AI) in software such as ChatGPT and Stable Diffusion, which can quickly—albeit haphazardly—generate works such as essays and photographs from a text prompt. Reading these, you might be excused for thinking that writers and photographers are soon to go the way of the elevator operator, automated out of existence.
Learning from one's past mistakes is not limited to humans. Computers do it, too. In industries, this is done via computer-based control systems that help operate production systems. For industrial robots that perform specific tasks in batches, say producing clothing, computer chips, or baked goods, the most commonly used control technique is iterative learning control (ILC). Most industries still rely on ILC systems that use a learning strategy called the proportional-type update rule (PTUR). This technique improves the performance of ILC systems by repeating the same task over and over and updating its control input based on errors encountered in previous iterations.
Many existing robotics systems draw inspiration from nature, artificially reproducing biological processes, natural structures or animal behaviors to achieve specific goals. This is because animals and plants are innately equipped with abilities that help them to survive in their respective environments, and that could thus also improve the performance of robots outside of laboratory settings.
Researchers have trained a robotic 'chef' to watch and learn from cooking videos, and recreate the dish itself.
Stanford scientists have developed a soft and stretchable electronic skin that can directly talk to the brain, imitating the sensory feedback of real skin using a strategy that, if improved, could offer hope to millions of people with prosthetic limbs.
The accelerated pace of robotics development has given us a veritable zoo filled with creatures sometimes indistinguishable from the real deal.
Divers are often put at considerable risk when searching for people or objects underwater. The ETH spin-off Tethys has developed an underwater robot that can be used in situations that are too dangerous for human divers.
Ameca can speak French, Chinese or dozens of other languages, instantly compose a poem or sketch a cat on request. Ask for a smile, and you'll get a clenched grin on her rubbery blue face.
When a kitten is walking in a dangerous environment, it will gently step on the terrain with its feet to estimate the friction or bearing capacity. Based on this experience, the kitten can then predict the physical parameters of terrain with a similar appearance and avoid the soft, wet ground.
Imagine a world where science fiction meets reality, where cutting-edge technology brings to life the awe-inspiring scenes from movies like Prometheus. This is the groundbreaking research led by Dr. Fu Zhang, Assistant Professor of Department of Mechanical Engineering at the Faculty of Engineering, the University of Hong Kong (HKU), who has developed a Powered-flying Ultra-underactuated LiDAR-Sensing Aerial Robot (PULSAR) that is poised to redefine the world of unpiloted aerial vehicles (UAVs).