Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
Yuanluo Technology Unveils First Autonomous Laboratory Utilizing Object-Centric Physics Model
Yuanluo Technology has successfully launched the world's first autonomous laboratory on a national research platform, marking a significant advancement in embodied intelligence. The laboratory's robotic system can autonomously perform over 40 operations, including nucleic acid extraction and cytotoxicity testing, with a precision of less than one millimeter. This achievement demonstrates the robot's capability to execute complex, multi-step tasks continuously for over three hours, addressing challenges in throughput and consistency in biochemical research. This development is crucial as it signifies a shift from demonstration to practical application of embodied intelligence in the biochemical and material science sectors. The Object-centric Physics Native Model (OPN), developed by Yuanluo, enables the robot to understand and adapt to the dynamic conditions of a real laboratory environment. By integrating visual, tactile, and force feedback, the robot can make real-time adjustments, ensuring stable execution of intricate experimental workflows across multiple devices. Looking ahead, the successful implementation of this autonomous laboratory sets the stage for further advancements in research and development processes across various industries, including public health and advanced manufacturing. The next milestones will involve expanding the capabilities of the OPN model and integrating it into more complex industrial systems. No further timeline was disclosed at the time of publication.
Autonomous Laboratories Embodied Intelligence Biochemical Research Robotics AI
MIT Researchers Selected for Funding in US Department of Energy’s Genesis Mission Phase I
MIT researchers have been chosen to participate in the U.S. Department of Energy’s Genesis Mission, with 15 collaborative projects receiving funding under Genesis Phase I. This national initiative aims to create a powerful integrated science discovery platform that leverages AI, supercomputing, and quantum systems to drive advancements in energy and scientific discovery. The Genesis Mission is significant as it fosters collaboration between universities, industry, and national laboratories, aligning research efforts with national priorities. Ian A. Waitz, MIT’s vice president for research, emphasized the importance of this initiative in catalyzing innovation for the benefit of both the nation and the world. Looking ahead, projects that demonstrate promising pathways for transformative capabilities may receive further funding from the DOE. Six projects will be led by MIT principal investigators, while MIT researchers will also contribute to nine additional projects led by other institutions, showcasing a robust collaborative effort in advancing scientific capabilities.
Funding Artificial intelligence Quantum computing Laboratory for Nuclear Science Plasma Science and Fusion Center Research Laboratory of Electronics
Bristol Myers Squibb Launches Advanced AI Factory with NVIDIA Vera Rubin Technology
Bristol Myers Squibb (BMS) has announced the deployment of its second NVIDIA DGX SuperPOD, featuring eight DGX Vera Rubin NVL72 systems. This new AI cluster is touted as the most powerful and energy-efficient in the life sciences sector, significantly enhancing researchers' access to AI capabilities. BMS aims to democratize AI access among its scientists, allowing for faster drug discovery processes without the constraints of resource limitations. The introduction of this advanced AI infrastructure is crucial for BMS as it seeks to translate AI capabilities into measurable impacts in drug discovery. The new system will facilitate a unified AI platform, including the NVIDIA BioNeMo Agent Toolkit, which will streamline predictions and model training across the drug discovery pipeline. BMS has already seen substantial benefits from its existing DGX SuperPOD, including significant time savings in target identification and the expansion of its library of CELMoD compounds. Looking ahead, BMS is focused on leveraging AI to optimize lead discovery and enhance the efficiency of laboratory experiments. The new system is expected to alleviate current computational bottlenecks and support large-scale predictions. As BMS continues to innovate in the AI space, it emphasizes the importance of making advanced technology accessible to scientists to drive impactful research outcomes. No further timeline was disclosed at the time of publication.
University of Toronto Engineers Develop Six New Metal Alloys for Extreme Environments
Researchers at the University of Toronto Engineering have created six innovative metal alloys using an AI-driven discovery platform. These alloys are designed to enhance the durability of components in jet engines and nuclear reactors, capable of withstanding temperatures exceeding 1,832°F. The AI-assisted approach significantly accelerates the identification of high-performance materials, demonstrating the potential for rapid advancements in material science. The significance of this development lies in the growing demand for materials that can endure extreme temperature and pressure fluctuations, which are common in applications like jet engines and nuclear power plants. Yu Zou, the project leader, emphasized the need for materials that can be produced through 3D metal printing, allowing for the creation of complex components that traditional manufacturing methods cannot achieve. Looking ahead, the researchers aim to further refine their AI-driven system to explore additional material compositions. No further timeline was disclosed at the time of publication, but the initial success in identifying six new alloy formulations suggests a promising future for advanced materials in extreme environments.
AI and Robotics Energy Innovation
Argonne National Laboratory launches ChemGraph framework for automated chemistry simulations
Researchers at Argonne National Laboratory have introduced ChemGraph, an open-source framework that automates complex computational chemistry simulations using AI agents. Built on the Aurora exascale supercomputer, ChemGraph simplifies the simulation process by allowing users to describe scientific problems in plain language, which the system then translates into computational tasks. This innovation aims to enhance research in materials science, battery design, and combustion systems by streamlining workflows and reducing the need for specialized expertise. The significance of ChemGraph lies in its ability to combine large language models with agent-based automation, enabling researchers to conduct simulations without manually navigating every technical step. By distributing tasks among AI agents, the framework enhances efficiency and reduces costs associated with computational resources. This approach not only improves the accuracy of simulations but also allows for the integration of various scientific software and libraries, ensuring that results are physics-based rather than solely reliant on language model outputs. Looking ahead, ChemGraph's open-source nature has already led to adaptations for other applications, such as X-ray absorption spectroscopy and high-throughput materials screening. The research team envisions further educational applications, providing a platform for professors to teach advanced computational techniques while simplifying the exploration of research questions for students. No further timeline was disclosed at the time of publication.
AI and Robotics
NVIDIA Vera CPU Opens the Way for Agentic Scientific AI at Los Alamos National Laboratory
Los Alamos National Laboratory (LANL) is set to enhance its computational capabilities with the development of new supercomputers, named Mission, Vision, and Veritas, in collaboration with HPE and NVIDIA. This initiative aims to harness NVIDIA Vera CPUs to significantly accelerate scientific discovery and advance the integration of agentic AI in scientific research. The project underscores LANL's commitment to leveraging cutting-edge technology to address complex scientific challenges. The supercomputers are expected to play a crucial role in various research domains, facilitating breakthroughs that could have far-reaching implications for science and technology.
How JPL Keeps the 13-Year-Old Curiosity Rover Doing Science
The Curiosity rover, which has been exploring Mars for 13 years, continues to operate effectively despite the challenges of its hostile environment. Since its successful landing in August 2012 at the Jet Propulsion Laboratory (JPL) in Pasadena, California, Curiosity has traveled nearly 37 kilometers, drilled into 42 rocks, and captured approximately 763,000 images. JPL engineers, including assistant team chief Alexandra Holloway, have implemented ongoing software updates and innovative solutions to keep the rover functional, even as it faces wear and diminishing power. Holloway highlighted the rover's longevity, attributing it to robust engineering and continuous maintenance efforts. While Curiosity and the younger Perseverance rover share similar hardware, Perseverance features additional capabilities for autonomous navigation, reflecting their distinct mission objectives. Curiosity's operational challenges include wheel wear from sharp rocks and power consumption from its nuclear source, which decreases over time. Engineers have developed strategies to optimize power usage, such as reducing computer activation time and parallel processing tasks. Looking ahead, Holloway noted that while Curiosity's arm may eventually fail, the rover still possesses valuable remote sensing instruments that will contribute to future Mars exploration. With its power source expected to remain viable through at least 2035, Curiosity's mission continues to yield significant scientific insights, paving the way for future missions.
Curiosity-rover Mars Jpl
Wi-Fi That Can Withstand a Nuclear Reactor
Researchers at the Institute of Science Tokyo have developed a robust Wi-Fi receiver capable of functioning within the extreme conditions of a nuclear reactor, a breakthrough presented by graduate student Yasuto Narukiyo at the IEEE International Solid-State Circuits Conference in San Francisco this February. The receiver can withstand radiation doses of up to 500 kilograys, significantly exceeding the tolerance levels of typical electronics used in space. This innovation aims to enhance wireless communication for robots tasked with decommissioning nuclear reactors, a process that has become increasingly vital since the Fukushima Daiichi disaster in 2011. Currently, many robotic systems rely on cumbersome LAN cables, which can complicate operations in hazardous environments. With over 200 reactors expected to reach the end of their operational lives in the next two decades, the need for effective decommissioning solutions is pressing. To achieve radiation hardening, Narukiyo and his team modified the receiver's components, reduced the number of transistors, and adjusted their design to minimize vulnerability to radiation damage. They focused on optimizing the performance of PMOS and NMOS transistors, leading to a receiver that maintained comparable performance to standard Wi-Fi devices even after exposure to high radiation levels. Looking ahead, Narukiyo plans to enhance the receiver's capabilities and develop a transmitter for two-way communication, which presents additional challenges due to the high current requirements for Wi-Fi signal generation. The team is also investigating alternative semiconductor materials, such as diamond, to improve the transmitter's resilience.
Wi-fi Nuclear-reactors Isscc Decommissioning Industrial-robots Radiation-hardening
Underwater ribbon cutting ushers in new URI Ocean Robotics Laboratory
The Narragansett Bay Campus recently celebrated a significant milestone, marking a pivotal moment in its development and contributions to marine research and education. The event, which took place on October 15, 2023, brought together faculty, students, and community members to recognize the campus's achievements and future goals. This gathering highlighted the institution's commitment to advancing knowledge in marine sciences and fostering collaboration among researchers. Attendees participated in various activities, including presentations and discussions, aimed at showcasing the campus's innovative projects and its role in addressing environmental challenges. The celebration underscored the importance of the Narragansett Bay Campus as a hub for scientific inquiry and community engagement, reinforcing its mission to enhance understanding of marine ecosystems and promote sustainability efforts in the region.
Import AI 446: Nuclear LLMs; China's big AI benchmark; measurement and AI policy
As artificial intelligence continues to evolve, questions arise about the potential for AIs to experience emotions such as jealousy. Researchers in the field of AI and cognitive science are exploring the implications of advanced machine learning systems, particularly those trained on vast datasets, to understand whether these systems could develop complex emotional responses similar to humans. This inquiry has gained traction in recent months, with discussions intensifying around the ethical and philosophical ramifications of AI emotions. The investigation into AI jealousy is particularly relevant as developers strive to create more sophisticated and autonomous systems. Experts argue that while current AI lacks the capacity for genuine emotions, the rapid advancements in technology could lead to scenarios where AIs exhibit behaviors that mimic jealousy, particularly in competitive environments or when they perceive threats to their operational efficiency. This exploration is taking place in various research institutions and tech companies worldwide, with findings expected to influence future AI design and implementation. The motivation behind this research stems from a desire to ensure that as AI systems become more integrated into daily life, they do not inadvertently develop harmful behaviors or biases. By understanding the potential for emotional responses in AIs, researchers aim to create guidelines that promote ethical AI development and usage. As the conversation around AI emotions evolves, it raises critical questions about the nature of intelligence and the ethical considerations of creating machines that could potentially experience feelings akin to jealousy.
Oak Ridge National Lab reveals ‘hidden workforce’ behind AI-powered research facilities
By Clint Keaton Behind every self-driving laboratory at the US Department of Energy’s Oak Ridge National Laboratory is a team most people never see. Facilities and Operations (F&O) workers are building and maintaining the infrastructure that makes autonomous science possible. Autonomous labs run with little human intervention. Instead, they rely on robotics, sensors and automation […]
Autonomous Vehicles Features Science artificial intelligence autonomous laboratories autonomous science
MIT's FloatForm Swarm Robots Create Adaptive Floating Structures for Urban Spaces
MIT researchers have developed FloatForm, a swarm of small robotic boats that autonomously assemble into larger floating structures. Each robot, measuring 21 centimeters square, is equipped with thrusters, sensors, and magnetic latches, allowing them to form bridges, platforms, and other structures with minimal human input. This innovative system aims to transform urban waterfronts into dynamic, programmable spaces, enhancing public infrastructure and emergency response capabilities. The significance of FloatForm lies in its potential to revolutionize how urban areas utilize water surfaces. By mimicking the self-organizing behavior of fire ants, the robots can adaptively create and reconfigure structures on demand, addressing challenges such as traffic alleviation during emergencies or creating temporary public spaces. This modular approach to floating infrastructure could lead to more livable cities by expanding usable public space onto underutilized water areas. Looking ahead, the research team plans to explore further applications of FloatForm in urban environments, with no specific timeline disclosed for future developments. The project builds on previous work with full-size autonomous vessels in Amsterdam, indicating a growing interest in leveraging water for urban mobility and public space expansion. The open-access findings were published in Nature Communications, highlighting the collaborative efforts of MIT's Computer Science and Artificial Intelligence Laboratory and the Senseable City Lab.
Research Robotics Autonomous vehicles Artificial intelligence Computer science and technology Machine learning
16-Year-Old Evan Booz Develops AI Turtle for Microplastic Detection, Wins $50,000 Scholarship
Evan Booz, a 16-year-old from Canada, has created an AI-powered robotic turtle capable of swimming autonomously to detect microplastics. His innovation earned him the Gordon E. Moore Award at the Regeneron International Science and Engineering Fair in May, along with a $50,000 scholarship. The robotic turtle, inspired by a camping trip where Booz observed a snapping turtle, took about five months to develop. It features an underwater 3D holographic camera and an AI model trained to identify microplastics, achieving a 94% accuracy rate. This technology allows for real-time analysis in water, eliminating the need for time-consuming and costly laboratory sample testing. Booz plans to use the scholarship for his college education in science or engineering and aims to open-source his research to advance microplastic monitoring technology. As the AI turtle quietly navigates lakes, it represents both the curiosity of a young inventor and a critical tool in addressing the urgent issue of microplastic pollution.
AI Robotics Environmental Technology Microplastic Detection Sustainable Innovation
MIT Unveils Miniature Robots for Creating Floating Bridges and Stages
A group of palm-sized square robots autonomously converge, lock together, and form a temporary floating bridge within minutes. This innovative achievement comes from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and was recently published in Nature Communications. Inspired by fire ants, these robots utilize decentralized control, allowing them to coordinate movements without a central command, enhancing their scalability. Each FloatForm robot measures 21 centimeters on each side and is equipped with propellers, sensors, and magnetic locks. The robots can synchronize their movements by exchanging positions with neighbors, making the planning complexity dependent on local interactions rather than the total number of robots. Simulations indicate that the framework can smoothly scale up to 64 units, showcasing significant potential for various applications. The team has successfully tested the robots in controlled environments, achieving a 90% success rate with four robots and 70% with eight in completing tasks autonomously. Future developments will focus on integrating GPS or visual navigation and mechanical locking for real-world applications, including floating markets and emergency bridges in urban areas with waterways. No further timeline was disclosed at the time of publication.
Robotics Autonomous Systems Modular Robotics Water Navigation
RSS2026: Development of Consensus and China's Role in Embodied Intelligence
The Robotics: Science and Systems (RSS) conference is set to commence in St. Louis this June, marking a significant event in the robotics academic community. Since its inception in 2006, RSS has been known for its selective approach, accepting only about 60 papers annually, and is regarded as a leading indicator in the field of robotics. The 2026 conference will introduce a new focus on embodied intelligence alongside traditional motion planning and operational algorithms. Embodied intelligence has rapidly transitioned from a laboratory concept to an industrial hotspot over the past two years. The integration of large language models with visual models has led to the development of the Vision-Language-Action (VLA) framework, enabling robots to comprehend natural language commands and execute multi-step tasks. This technological pathway has sparked extensive academic debate regarding the reliability of end-to-end Transformer-based strategies in real-world applications versus potential overfitting in datasets. The positioning of embodied intelligence at RSS2026 will be symbolically significant for China. In recent years, international conferences have often viewed Chinese teams as representatives of engineering implementation rather than contributors of original theory. An increase in Chinese academic contributions at RSS this year could indicate a subtle shift in the international academic community's perception of the landscape of embodied intelligence research, highlighting the importance of high-quality theoretical innovation.
Embodied Intelligence Robotics Research Vision-Language-Action AI Robotics Algorithms
MIT and Toyota Research Institute Unveil SceneSmith for Robot Household Training
MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Toyota Research Institute have developed SceneSmith, an AI-powered system that allows robots to practice household tasks in a virtual environment. This system utilizes three visual language models to collaboratively create realistic 3D scenes, enabling robots to learn complex skills through extensive simulation. SceneSmith not only generates lifelike environments but also incorporates physical properties like mass, friction, and inertia, allowing robots to interact meaningfully within these spaces. The research team tested over 100 unique action plans in the digital world, revealing flaws in the robots' planning that were validated by human consensus over 99% of the time, helping to refine their strategies before real-world application. The effectiveness of SceneSmith was highlighted at a recent international machine learning conference, where it received positive feedback from over 200 testers, with more than 90% rating its visual realism highly. As robots learn to perform tasks like moving objects in a kitchen, the prospect of robots handling household chores may soon become a reality.
AI Robotics Virtual Reality Machine Learning
New Quantum Hermite Transform Algorithm Enhances AI and Scientific Computing Potential
Researchers from the U.S. Department of Energy’s Brookhaven National Laboratory, Northeastern University, Google Quantum AI, and the University of Texas at Austin have introduced a new quantum computing algorithm called the quantum Hermite transform (QHT). This algorithm aims to broaden the scope of problems that future quantum computers can address, particularly in artificial intelligence and scientific simulations. The significance of the quantum Hermite transform lies in its potential to improve data processing and simulation capabilities of quantum computers. By introducing a new computational building block, the QHT could lead to more efficient quantum algorithms in various fields, including materials science and energy research. The findings were presented at the 58th Annual ACM Symposium on Theory of Computing in Salt Lake City. Looking ahead, the researchers emphasize that expanding the library of reusable quantum primitives like the QHT will facilitate the development of innovative quantum algorithms. This advancement could provide exponential speed advantages over classical methods, marking a pivotal step in the evolution of quantum computing applications. No further timeline was disclosed at the time of publication.
AI and Robotics
IEEE Honors Robotics Pioneer Toshio Fukuda
Toshio Fukuda has been blazing trails for most of his career. He is considered to be one of the most prolific scholars in robotics, writing more than 2,000 research papers and authoring several books on the field. He’s an influential figure thanks to his pioneering work developing biomedical robotic systems, industrial robots, micro-nano robotics, mechatronics, and AI-driven automation.Fukuda launched one of the first robotics conferences, the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). It is still popular almost 40 years later.Toshio FukudaEmployerEgypt-Japan University of Science and Technology, in Alexandria TitleProfessor and vice president of research Member gradeLife Fellow Alma matersWaseda University, in Tokyo; University of Tokyo An IEEE Life Fellow, he is a professor emeritus in the department of micro-nano systems engineering and a visiting professor at Nagoya University, in Japan, where he taught for nearly 25 years. Currently, he is a vice president of research at the Egypt-Japan University of Science and Technology, in Alexandria, Egypt.Within IEEE, Fukuda has held top volunteer positions including the organization’s highest office: He served as IEEE president in 2020, becoming the first person of Asian descent to hold the role.He’s a former program director of Japan’s Moonshot program, which by 2050 intends to develop advanced AI robots.Born in Japan, Fukuda has been recognized by the country for his contributions to science with two of its highest awards: the Medal of Honor with a purple ribbon in 2015 and the Order of the Sacred Treasure in 2022.IEEE honored him with this year’s Richard M. Emberson Award for “distinguished service advancing the technical objectives of IEEE, especially in the area of robotics.” The IEEE Board-level award is sponsored by the IEEE Technical Activities Board. Fukuda received the award on 24 April at a ceremony in New York City.As a former IEEE president who has served as a master of ceremonies at several of the organization’s major award events, Fukuda noted that he is more accustomed to bestowing awards than receiving them.“It’s very interesting to be on the receiving end,” he says.The journey into robotics researchAs a teenager, Fukuda spent his summer breaks teaching himself how to build things including transistor radios and steam engines.“It was very nice to have a hands-on hobby and make these kinds of things myself,” he says. His experimentation led him to study engineering.He earned a bachelor’s degree in engineering in 1971 from Waseda University, in Tokyo. He says one of his professors there—Ichiro Kato, regarded as the father of Japanese robotics research—was a good mentor who made a positive impact.Fukuda’s research interests were robotics and mechatronics, a field that combines robotics, electronics, computer science, and control systems.He went on to earn a master’s degree and a doctorate in science from the University of Tokyo, in 1971 and 1977. During those years, he also attended Yale, where he conducted research on advanced control theory in 1973.He reflects fondly on his time at Yale: “It was a very nice environment and a kind of free-thinking atmosphere. It motivated me to study more.”“IEEE doesn’t care who you are, what you do, what country you are from, or whether you are male or female. IEEE accepts people who have energy and passion.”While at Yale, Fukuda served as an assistant to his advisor—which led him to consider a career in academia, he says, because he enjoyed the freedom that research work afforded him.But he realized that such freedom comes with a price. University researchers are expected to raise the money that funds their work. He compares researchers to small-business owners who have to bring in money to keep their enterprise afloat.That realization led him to select robotics as his field because he intended to develop technologies useful to industry, he says.After earning his doctorate, he returned to Japan in 1977 to work as a research scientist at the government’s Mechanical Engineering Laboratory, later renamed the National Institute of Advanced Industrial Science and Technology, in Tsukuba.“There was a lot of research going on at the lab, including practical robotics and theory,” he says.He left Japan in 1979 to become a visiting research fellow at the University of Stuttgart, in Germany. During his year there, he studied systems, software problems, and related topics.He returned to Japan and was hired as an associate professor of mechanical engineering at the Tokyo University of Science. He conducted research into practical uses for robots by visiting industrial plants. He decided to develop robots that inspect industrial equipment such as those used in assembly plants, oil refineries, and power stations—places that “can be hostile environments for humans,” he says.His work drew interest from chemical, oil, and utility companies.“I got a lot of money from them for this very practical application, which funded my research,” he says, laughing.Developing popular robotic systemsFukuda grew tired of making those robots, he says, so he switched to creating ones for scientific applications. He developed many techniques, but he probably is best known for his modular, cellular robotic systems (CEBOTs), which he introduced in 1985.He has described how CEBOTs work in numerous papers published in the IEEE Xplore Digital Library.The CEBOT system is composed of a number of autonomous robotic cells that stick together like interlocking Lego plastic bricks, he says.Each cell is a fundamental modular unit that has a function. When a simple task is given, the system can analyze it and generate the structure of the cellular manipulator. The cells connect to and detach from each other through connection mechanisms and cooperate mutually, creating complex structures and configurations.“You start developing from the component-wise to the cell-wise to a small functional unit—and then you come up with clusters that make bigger systems. We can make a society of robot beings like that,” he explained in his oral history published on the Engineering and Technology History Wiki. “It’s a distributed robotic system, a self-organized robotic system, and also an evolutionary robotic system.“It’s also a fault-tolerant robot system because if something is wrong, you just remove those things and make a new one. You keep the system working. That’s a great thing.”Today CEBOTs are used for a variety of tasks such as delivering medication in hospitals, assisting with planting crops, and transporting products in distribution centers. Check out IEEE Spectrum’s Robots Guide for news from the world of robotics.In 1989 Fukuda joined Nagoya University as a professor of mechanical engineering and micro-nano systems engineering. During his 24-year career there, he was director of the university’s Center for Micro-Nano Mechatronics. He developed a long list of technologies at the university, including many for medical applications. He also conducted groundbreaking research into intelligent robotic systems and micro- and nano-robotics.Another technology he is known for is brachiation robots, which he helped develop in 1988. He calls them monkey robots because they’re based on the pendulum-like movement of monkeys swinging from tree to tree. The gravity-based locomotion enables continuous movement.Brachiation robots now are inspecting high-voltage transmission towers and bridges, searching damaged buildings for survivors, and performing maintenance on pipelines and cables.Fukuda retired from the university in 2013 and was named professor emeritus.He didn’t stay retired for long, though. He next held a teaching appointment at Meijo University, in Nagoya, until he left in 2022 to join the Egypt-Japan University.A prominent volunteerHe joined IEEE in 1980 at the encouragement of one of his research advisors, Professor Fumio Harashima, now an IEEE Life Fellow. After attending conferences and reading the organization’s publications, Fukuda says, he looked forward to becoming more involved.“I wanted to know how to organize a conference and how to edit a paper for one of its Transactions,” he says. “I wanted to know what was going on from inside the organization, not just the outside.”In 1988 he was the founding chair and organizer of IROS, in Tokyo. The conference had 330 attendees that year, and was supported by Harashima. Today it is one of the largest and most prestigious conferences on the topic, attracting more than 9,000 people annually. Out of 120,000 conferences, it was the only conference in the Nature Index database for this year, Fukuda says.In 1996 he and other members launched IEEE Transactions on Mechatronics.He was the founding president of the IEEE Nanotechnology Council, which was established in 2002. He is considered a pioneer in nanotechnology research, particularly regarding how it relates to robotics.Over the years, he has held numerous volunteer positions on IEEE editorial boards and committees.He was the 1998–1999 president of the IEEE Robotics and Automation Society, becoming the first non-U.S. member to hold the title.He was director of IEEE Division X (2001–2002 and 2017–2018), which covers intelligent systems, biological engineering, robotics, control systems, and photonic technologies. He served as the 2013–2014 director of IEEE Region 10 (Asia-Pacific).As the 2020 IEEE president, Fukuda saw the organization through the early part of the COVID-19 pandemic. Because of travel restrictions, he realized IEEE should change how it offered its in-person services, specifically educational programs. He encouraged IEEE Educational Activities to develop an online learning platform. The IEEE Learning Network started with just three courses and now offers nearly 2,000 courses, webinars, and learning materials.An award-winning memberThe Emberson Award joins a slew of other recognitions Fukuda has received from IEEE. They include several from the IEEE Robotics and Automation Society: a 2004 Pioneer Award, a 2009 Saridis Leadership Award, and the 2011 Harashima Award for Innovative Technologies. He is also a recipient of the Board-level 2010 IEEE Robotics and Automation Technical Field Award.He says he feels strongly that IEEE should be a diverse organization that is welcoming to all. As IEEE president, he led efforts to devise a diversity, equity, and inclusion program. Several policies, procedures, and bylaws were revised to give members a safe, inclusive place for discourse.“It’s important for IEEE to make everyone feel comfortable,” he says. “DEI programs are important. All people should be equal. IEEE doesn’t care who you are, what you do, what country you are from, or whether you are male or female. IEEE accepts people who have energy and passion.“It accepted me, from the Far East. That’s why I like it.”You can learn more about Fukuda and his career from the oral history conducted by the IEEE History Center.
Robotics Robots Ieee-member-news Type-ti Ieee-awards Toshio-fukuda
Fusion to quantum: 9 projects lined up for US’ new Discovery supercomputer
America's next major exascale supercomputer, named Discovery, is set to tackle its inaugural scientific challenges. This advanced computing system, which represents a significant leap in processing power, is designed to handle complex simulations and data analysis that were previously unattainable. Scheduled to begin operations in the coming months, Discovery will be located at Oak Ridge National Laboratory in Tennessee. The motivation behind developing such a powerful supercomputer stems from the need for enhanced computational capabilities to address pressing scientific questions and accelerate research across various fields, including climate modeling, drug discovery, and materials science. By leveraging its unprecedented speed and efficiency, researchers aim to gain deeper insights and make breakthroughs that could have far-reaching implications for both science and society. The operationalization of Discovery involves collaboration among leading scientists and engineers who will utilize its capabilities to run extensive simulations and analyze large datasets. This initiative not only underscores America's commitment to maintaining leadership in high-performance computing but also highlights the growing importance of advanced technology in solving some of the world's most complex challenges.
AI and Robotics
US: Los Alamos lab’s new tool detects hallucinations in machine vision models
Researchers at Los Alamos National Laboratory have unveiled a groundbreaking tool named Prelim Attention, designed to enhance the analysis of complex data sets. This innovative tool, which leverages advanced machine learning techniques, aims to streamline the process of identifying significant patterns and insights within large volumes of information. The development was announced in October 2023, highlighting the laboratory's commitment to advancing data science and its applications in various fields. The motivation behind creating Prelim Attention stems from the increasing demand for efficient data analysis solutions in scientific research, national security, and other sectors that rely heavily on data interpretation. By improving the capability to focus on critical data points, the tool is expected to facilitate more informed decision-making and accelerate research outcomes. The researchers employed a combination of algorithms and user-friendly interfaces to ensure that Prelim Attention can be utilized effectively by both experts and non-experts alike. This approach not only enhances accessibility but also broadens the potential user base, allowing a wider range of professionals to benefit from its capabilities. The introduction of Prelim Attention marks a significant advancement in the field of data analysis, promising to transform how researchers and analysts approach complex data challenges in the future.
AI and Robotics
Can Pepper the robot be a good playmate?
Researchers at the Norwegian University of Science and Technology (NTNU) recently conducted a controlled laboratory experiment to explore the dynamics of playing physical games with a humanoid robot named Pepper. The study aimed to understand how interactions with a robot that mimics human behavior and appearance influence gameplay experiences. By engaging participants in various physical games against Pepper, the researchers sought to assess both the emotional and cognitive responses elicited by the robot's presence. This investigation is part of a broader effort to enhance human-robot interaction, particularly in social and recreational contexts. The findings could have implications for the development of more effective robots in various fields, including education and therapy, by fostering a better understanding of how humans relate to robotic counterparts.
Consumer & Gadgets
RoboChem Flex: democratisation of the autonomous synthesis robot
Researchers from the University of Amsterdam’s Van ’t Hoff Institute for Molecular Sciences, led by Professor Timothy Noël, have made significant advancements in autonomous laboratory systems aimed at optimizing synthesis processes. Their findings, published in the journal Nature Synthesis, introduce RoboChem Flex, a versatile and modular system that incorporates “human-in-the-loop” analytics. This innovative design allows for enhanced flexibility and efficiency in chemical synthesis, potentially transforming how laboratories conduct research and development. The study highlights the growing importance of automation in scientific research, driven by the need for more efficient and accurate synthesis methods.
UK Dstl develops AIM to unify messaging across military systems
The UK Defence Science and Technology Laboratory (Dstl) has developed a new digital messaging system called Assured Intent Messaging (AIM). This innovative platform aims to enhance communication across various military technologies, ensuring a more cohesive and efficient exchange of information. The initiative reflects the UK's commitment to improving military operations and interoperability among different systems. By integrating diverse communication methods, AIM seeks to address existing challenges in military coordination, ultimately enhancing operational effectiveness. The introduction of this system marks a significant advancement in military communication technology, with potential implications for future defense strategies.
News
Dexterous Robots Move From Labs to Industry With NSF Support
In July, the National Science Foundation (NSF) held the kickoff meeting for phase two of its Convergence Accelerator program in Pittsburgh, where participants engaged in knowledge transfer, strategic discussions, planning, and demonstrations. Researchers from Carnegie Mellon University are spearheading efforts to develop advanced robotic hands aimed at enhancing applications in health, agriculture, and manufacturing. This initiative will receive further backing from the U.S. government, facilitating the transition of these innovative robotic technologies from laboratory settings to real-world industrial use.
Announcements Research
Kshitij Goel Wins 2024 Alan J. Perlis Graduate Student Teaching Award
Kshitij Goel, a Ph.D. student at Carnegie Mellon University's Robotics Institute, has been honored with the 2024 Alan J. Perlis Graduate Teaching Award by the School of Computer Science. This recognition is attributed to his exceptional efforts in redesigning and teaching the Mobile Robot Algorithms Laboratory (MRAL), along with his overall excellence in teaching and student engagement. Goel's commitment to enhancing the educational experience across various courses has further distinguished him in the academic community. The award highlights his significant contributions to the field of robotics education and his dedication to fostering a positive learning environment.
Uncategorized
Single-molecule tracker illuminates workings of cancer-related proteins
A team of researchers has developed advanced microscopy and nanotechnology techniques to monitor the activity of individual proteins in real-time. This innovative approach allows scientists to gain unprecedented insights into protein dynamics, which are crucial for understanding various biological processes and diseases. The research, conducted in a state-of-the-art laboratory, aims to enhance the understanding of cellular mechanisms and potentially lead to breakthroughs in medical treatments. By tagging proteins with custom-built nanotechnology, the team can visualize and track their movements and interactions, providing valuable data that could inform future studies in biochemistry and molecular biology. This work represents a significant advancement in the field, promising to deepen our comprehension of life at the molecular level.
Research Proteins Cells Chemistry Imaging Cancer
How neurons sense bacteria in the gut
A recent study has uncovered significant insights into how neurons interact with bacteria and their effects on animal brains. Researchers focused on nematodes to explore the mechanisms by which a specific neuron detects bacterial signals. This investigation sheds light on the intricate relationship between neural activity and microbial presence, highlighting the potential implications for understanding brain function in various organisms. The findings, which emerged from laboratory experiments conducted in October 2023, aim to deepen our comprehension of the sensory processes involved in neuronal responses to bacterial stimuli. This research could pave the way for future studies on the broader impacts of bacteria on neurological health and behavior.
Research Bacteria Neuroscience Microbiome Brain and cognitive sciences Picower InstituteRobotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
