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.
A study conducted by researchers at the Jiangsu Provincial Key Laboratory of Advanced Robotics, Soochow University, presents the development of a highly sensitive and responsive mechanosensor. This novel device is inspired by the ultrasensitive trigger hairs found in Venus flytraps, known for their rapid response to external stimuli. The study was published in the latest issue of Cyborg and Bionic Systems.
A new study by Carnegie Mellon University researchers found that when roboticists and people with disabilities collaborate on robot designs, interesting ideas emerge that could make existing robots more accessible and inspire new uses.
When robots come across unfamiliar objects, they struggle to account for a simple truth: Appearances aren't everything. They may attempt to grasp a block, only to find out it's a literal piece of cake. The misleading appearance of that object could lead the robot to miscalculate physical properties like the object's weight and center of mass, using the wrong grasp and applying more force than needed.
A team of researchers from Huazhong University of Science and Technology has introduced an innovative human-following surveillance robot designed to assist individuals with lower limb muscle weakness, a condition prevalent among the elderly and those suffering from neurological and motor system diseases. This cutting-edge technology promises to enhance daily mobility and accelerate recovery, offering a significant boost to rehabilitation efforts.
A research group at Osaka University has developed an innovative positioning system by correctly aligning the coordinates of the real and virtual worlds without the need to define routes in advance. This is achieved by integrating two vision-based self-location estimation methods: visual positioning systems (VPS) and natural feature-based tracking.
The world of robotics is witnessing a transformative shift with the rise of soft robotics, which offers unparalleled flexibility and adaptability in various applications, from medical interventions to intricate rescue operations.
In an advance for robotics technology, researchers from Shanghai Jiao Tong University have unveiled a novel hybrid-driven origami gripper, designed to tackle the challenge of grasping and manipulating objects with unprecedented versatility and precision.
Let's say you want to train a robot so it understands how to use tools and can then quickly learn to make repairs around your house with a hammer, wrench, and screwdriver. To do that, you would need an enormous amount of data demonstrating tool use.
In an advancement for robotics and artificial intelligence, researchers at Chongqing University of Technology, along with their international collaborators, have developed a cutting-edge method for enhancing interaction recognition. The study, published in Cyborg and Bionic Systems, introduces the Merge-and-Split Graph Convolutional Network (MS-GCN), a novel approach specifically designed to address the complexities of skeleton-based interaction recognition.