A fully edible robot could soon end up on our plate if we overcome some technical hurdles, say EPFL scientists involved in RoboFood—a project which aims to marry robots and food.
A team of roboticists at the University of Tokyo has taken a new approach to autonomous driving—instead of automating the entire car, simply put a robot in the driver's seat. The group built a robot capable of driving a car and tested it on a real-world track. They also published a paper describing their efforts on the arXiv preprint server.
Artificial intelligence (AI) systems that can play games with humans have become increasingly advanced and have already been deployed by countless videogame developers worldwide. Most of these systems, however, are designed to compete against humans online, on digital platforms and in virtual environments, as opposed to physically in the real-world.
A robotic gripper developed by Washington State University researchers is able to gently grab the majority of apples out of a tree without damaging the fruit.
Someday, you may want your home robot to carry a load of dirty clothes downstairs and deposit them in the washing machine in the far-left corner of the basement. The robot will need to combine your instructions with its visual observations to determine the steps it should take to complete this task.
Robotic systems are already being deployed in various settings worldwide, assisting humans with a highly diverse range of tasks. One sector in which robots could prove particularly advantageous is agriculture, where they could complete demanding manual tasks faster and more efficiently.
Researchers from North Carolina State University have demonstrated miniature soft hydraulic actuators that can be used to control the deformation and motion of soft robots that are less than a millimeter thick. The researchers have also demonstrated that this technique works with shape memory materials, allowing users to repeatedly lock the soft robots into a desired shape and return to the original shape as needed.
Today's intelligent robots can accurately recognize many objects through vision and touch. Tactile information, obtained through sensors, along with machine learning algorithms, enables robots to identify objects previously handled.
Today's intelligent robots can accurately recognize many objects through vision and touch. Tactile information, obtained through sensors, along with machine learning algorithms, enables robots to identify objects previously handled.
Nightmare material or truly man's best friend? A team of researchers equipped a dog-like quadruped robot with a mechanized arm that takes air samples from potentially treacherous situations, such as an abandoned building or fire. The robot dog walks samples to a person who screens them for potentially hazardous compounds, says the team that published its study in Analytical Chemistry. While the system needs further refinement, demonstrations show its potential value in dangerous conditions.
The public release of ChatGPT and other large language models (LLMs) has allowed developers worldwide to start experimenting with these models to enhance the interactive capabilities of their own systems. Similar generalizable models for robotic manipulation, however, remain scarce.
A disembodied woman's head mugged and grimaced, aping the facial expressions of a user on a nearby laptop as visitors to the China Humanoid Robot Developer Conference watched in fascinated unease.
Fast-moving autonomous mobile robots could help to deliver goods to various locations, helping to tackle disruptions to product supply chains. Nonetheless, wheeled or legged robots alone might not be sufficient to complete deliveries both efficiently and independently.
When it comes to mapping new territory, NASA's record swamps Lewis and Clark's. And the space agency doesn't only chart other stars and planets—a vantage point from space also allows a great view of Earth. Now a recent NASA invention could allow robots to map our planet's entire seafloor, helping to unlock valuable resources while protecting marine habitats. While the aquatic sonar devices for such an operation are not new, they've been severely hampered by batteries that leave them dead in the water.
Engineers at the University of Maryland (UMD) have developed a model that combines machine learning and collaborative robotics to overcome challenges in the design of materials used in wearable green tech.