To reliably assist humans with daily tasks in a broad range of real-world settings, robots should be able to effectively and dexterously manipulate different types of objects. The development of new cost-effective robotic grippers or other hand-like artificial systems plays a key role in enabling dexterous object manipulation in robots.
In the ever-evolving field of robotics, a groundbreaking approach has emerged, revolutionizing how robots perceive, navigate, and interact with their environments. This new frontier, known as brain-inspired navigation technology, integrates insights from neuroscience into robotics, offering enhanced capabilities and efficiency.
In an innovative leap forward for workplace safety, a research team at Seoul National University has developed the Bilateral Back Extensor Exosuit (BBEX), a robotic back-support device designed to prevent spinal injuries and assist workers in heavy lifting tasks.
Robotic automation has become a game-changer in addressing labor shortages. While traditional rigid grippers have effectively automated various routine tasks, boosting efficiency and productivity in industries that deal with objects of well-defined specifications, they fall short in sectors like the food industry, where delicate objects of varying sizes and shapes need to be handled. In these cases, a more specialized type of gripper is required.
West Virginia University roboticists are working on an alternative path to robot autonomy in Loopy, a "multicellular robot" composed of a ring of individual interconnected robot cells.
A multidisciplinary research team based across China and Brazil has used a dog-like robot and AI to create a new way to find fire ant nests. Published in the journal Pest Management Science, the study highlights how a "CyberDog" robot integrated with an AI model can automate the identification and control of Red Imported Fire Ants (RIFA), a globally destructive pest.
On a research cruise around Hawaii in 2018, Yuening Zhang SM '19, Ph.D. '24 saw how difficult it was to keep a tight ship. The careful coordination required to map underwater terrain could sometimes lead to a stressful environment for team members, who might have different understandings of which tasks must be completed in spontaneously changing conditions.
Over the past few decades, electronics engineers have developed increasingly flexible, versatile and highly performing devices for a wide range of real-world applications. Some of their efforts have been aimed at creating smart and sensing textiles, which could be used to fabricate stretchy robotic systems, medical devices and wearable technologies.
In recent years, roboticists worldwide have designed various robotic grippers that can pick up and manipulate different types of objects. The grippers that are most effective in tackling real-world manual tasks, particularly complex object manipulation tasks, are often those inspired by human hands.
Researchers have made groundbreaking advancements in the field of soft robotics by developing film-balloon (FiBa) soft robots. These innovative robots, designed by a team led by Dr. Terry Ching and corresponding author Professor Michinao Hashimoto, introduce a novel fabrication approach that enables lightweight, untethered operation with advanced biomimetic locomotion capabilities.
A tiny battery designed by MIT engineers could enable the deployment of cell-sized, autonomous robots for drug delivery within in the human body, as well as other applications such as locating leaks in gas pipelines.
A new algorithm may make robots safer by making them more aware of human inattentiveness. In computerized simulations of packaging and assembly lines where humans and robots work together, the algorithm developed to account for human carelessness improved safety by about a maximum of 80% and efficiency by about a maximum of 38% compared to existing methods.
A team of engineers from several institutions in South Korea has developed a type of wheel with spokes that can be adjusted in real time to conform the wheel's shape to uneven terrain. In their paper published in the journal Science Robotics, the group describes the principles behind their wheel design and how well it worked in two- and four-wheeled test models.
Large language models (LLMs), such as OpenAI's ChatGPT, are known to be highly effective in answering a wide range of user queries, generalizing well across many natural language processing (NLP) tasks. Recently, some studies have also been exploring the potential of these models for detecting and mitigating robotic system failures.
The smaller carbon footprint, or wheel print, of automatic delivery robots can encourage consumers to use them when ordering food, according to a Washington State University study.