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.
Teams of robots have the potential of tackling far more elaborate missions than individual robots, for instance, covering long distances faster, visiting different sites simultaneously, or monitoring larger geographical areas. Platforms that combine reliable hardware and software for multi-robot applications could help to advance research in this field, facilitating the testing of robot teams in specific real-world settings.
In a study published in Cyborg Bionic Systems, researchers from Shanghai University have unveiled a new artificial intelligence framework that improves the way robots interpret and execute tasks. The "Correction and Planning with Memory Integration" (CPMI) framework leverages large language models (LLMs) to improve the efficiency and effectiveness of robots performing complex, instruction-based tasks.
Humans and robots are increasingly interacting within built environments such as cities, buildings, walkways, and parks. Offering adaptability, cost-effectiveness, and scalability, robots are gradually being integrated into various aspects of everyday life, from manufacturing to health care to hospitality.
Researchers at Carnegie Mellon University's Robotics Institute (RI) have developed a robotic system that interactively co-paints with people. Collaborative FRIDA (CoFRIDA) can work with users of any artistic ability, inviting collaboration to create art in the real world.
Federal regulators have given Amazon key permission that will allow it to expand its drone delivery program, the company announced Thursday.
Over 100 years ago, Alexander Graham Bell asked the readers of National Geographic to do something bold and fresh—"to found a new science." He pointed out that sciences based on the measurements of sound and light already existed. But there was no science of odor. Bell asked his readers to "measure a smell."
The eyes of raptors can accurately perceive prey from kilometers away. Is it possible to model camera technology after birds' eyes? Researchers have developed a new type of camera that is inspired by the structures and functions of birds' eyes. A research team led by Prof. Kim Dae-Hyeong at the Center for Nanoparticle Research within the Institute for Basic Science (IBS), in collaboration with Prof. Song Young Min at the Gwangju Institute of Science and Technology (GIST), has developed a perovskite-based camera specializing in object detection.
To complete real-world tasks in home environments, offices and public spaces, robots should be able to effectively grasp and manipulate a wide range of objects. In recent years, developers have created various machine learning–based models designed to enable skilled object manipulation in robots.
Cambridge researchers have shown that members of the public have little trouble in learning very quickly how to use a third thumb—a controllable, prosthetic extra thumb—to pick up and manipulate objects.
Snake-inspired robots could have various advantages over conventional wheeled or legged robots. For instance, slithering robots can adapt the shape of their body, enter narrow spaces, and move freely in environments that are inaccessible to both humans and other robots.