Day: 2025-08-25

Tokyo and Kawasaki, Japan, August 25, 2025 - (JCN Newswire via SeaPRwire.com) - Shibaura Institute of Technology (Associate Professor Takuya Otani, Faculty of System Science and Engineering [Human Robot System Laboratory]), Waseda University (Professor Atsuo Takanishi, Faculty of Science and Engineering), and Fujitsu Limited today announced the development of an innovative method for efficiently controlling robot posture using quantum computing technology. This new approach facilitates the efficient and accurate calculation of inverse kinematics, i.e., determining joint angles from a target end-effector position, for multi-joint robots by leveraging qubit-based position representation and quantum entanglement. Verification using Fujitsu's quantum simulator achieved up to a 43% error reduction with fewer calculations compared to conventional methods. The effectiveness of quantum entanglement was also confirmed through an experiment carried out on the 64-qubit quantum computer jointly developed by RIKEN and Fujitsu.By expressing the orientation and position of each robot link as a qubit, and by replicating the structural influence of parent joint movements on child joints through quantum entanglement, the number of necessary calculations was significantly reduced compared to conventional classical methods. As quantum computing advances towards practical application, this development is expected to contribute substantially to the creation of next-generation robots that demand real-time control and complex operational capabilities.Quantum technology breakthrough for complex robot posture calculationIn robot posture control, calculating inverse kinematics is crucial. For robots with multiple joints, the possible angle combinations are numerous, requiring iterative calculations to minimize the discrepancy from the target position and resulting in a high computational load. For a full-body multi-joint model with 17 joints, equivalent to the number of joints in the human body, the number of possible calculations required are too vast to be solved directly. A common approach has been to perform motion calculations with an approximated 7 joints, but this limits the smoothness of movement.In this research, a new method leveraging the power of quantum computing has been proposed to address these challenges. The orientation and position of each robot part (link) are represented by qubits, and forward kinematics, i.e., calculation of end-effector position from joint angles, is carried out using quantum circuits. Inverse kinematics calculations are performed on classical computers, achieving efficient posture control through a hybrid quantum-classical approach.Improved convergence speed and accuracy with quantum entanglementFurthermore, by introducing quantum entanglement, the structure where the movement of parent joints naturally influences child joints is reproduced on the quantum circuit. This significantly improved the convergence speed and accuracy of inverse kinematics calculations. In addition, a trial calculation showed that motion calculations for a full-body multi-joint model with 17 joints can be executed in approximately 30 minutes.Expected applications in humanoid and multi-joint robotsThis method can express the posture of multi-joint robots with a small number of qubits, making it implementable even in current noise intermediate-scale quantum (NISQ) computers. In the future, this technology could be applied to real-time control of humanoid robots and multi-joint manipulators, obstacle avoidance, and energy optimization. Further performance improvements are also anticipated through combination with advanced quantum algorithms such as quantum Fourier transform.Research paper detailsAuthors:- Takuya Otani, Shibaura Institute of Technology, Faculty of System Science and Engineering- Atsuo Takanishi, Waseda University, Faculty of Science and Engineering- Nobuyuki Hara, Fujitsu Limited- Yutaka Takita, Fujitsu Limited- Koichi Kimura, Fujitsu LimitedTitle: Quantum computation for robot posture optimizationJournal: Scientific Reports, Nature PortfolioDOI:10.1038/s41598-025-12109-0About Shibaura Institute of Technology (SIT), JapanShibaura Institute of Technology (SIT) is a private university with campuses in Tokyo and Saitama. Since the establishment of its predecessor, Tokyo Higher School of Industry and Commerce, in 1927, it has maintained “learning through practice” as its philosophy in the education of engineers. SIT was the only private science and engineering university selected for the Top Global University Project sponsored by the Ministry of Education, Culture, Sports, Science and Technology and had received support from the ministry for 10 years starting from the 2014 academic year. Its motto, “Nurturing engineers who learn from society and contribute to society,” reflects its mission of fostering scientists and engineers who can contribute to the sustainable growth of the world by exposing their over 9,500 students to culturally diverse environments, where they learn to cope, collaborate, and relate with fellow students from around the world. Find out more: https://www.shibaura-it.ac.jp/en/About Waseda UniversityWaseda University was founded in 1882 with the founding principles of “Independence of Scholarship,” “Practical Application of Scholarship,” and the “Fostering of Good Citizens.” It is a private university with 10 faculties, including undergraduate departments, graduate schools, and professional graduate schools. As Waseda University approaches its 150th anniversary in 2032, it is returning to its founding principles and striving to further strengthen its three pillars: research, education, and contribution. Furthermore, under the philosophy, "Do not think only of your own interest, your family's interest, or the interests of your country alone, but be ambitious to contribute to humankind throughout the world," the University aims to evolve into a “university that contributes to humankind throughout the world” by 2050. Find out more: https://www.waseda.jp/top/en/About FujitsuFujitsu’s purpose is to make the world more sustainable by building trust in society through innovation. As the digital transformation partner of choice for customers around the globe, our 113,000 employees work to resolve some of the greatest challenges facing humanity. Our range of services and solutions draw on five key technologies: AI, Computing, Networks, Data & Security, and Converging Technologies, which we bring together to deliver sustainability transformation. Fujitsu Limited (TSE:6702) reported consolidated revenues of 3.6 trillion yen (US$23 billion) for the fiscal year ended March 31, 2025 and remains the top digital services company in Japan by market share. Find out more: global.fujitsuPress ContactsShibaura Institute of TechnologyAdmissions and Public Relations Department, Planning and Public Relations Division, TateiwaTEL: 03-5859-7070 FAX: 03-5859-7071E-mail: koho@ow.shibaura-it.ac.jpWaseda UniversityOffice of Information and Public RelationsMatsukiTEL: 03-3202-5454E-mail: koho@list.waseda.jpFujitsu LimitedPublic and Investor Relations DivisionInquiries Copyright 2025 JCN Newswire via SeaPRwire.com. All rights reserved. www.jcnnewswire.com

Tokyo, Japan, August 22, 2025 - (JCN Newswire via SeaPRwire.com) — NEC Corporation (NEC; TSE: 6701) today announced the development of an optical fiber sensing technology to monitor road conditions and accurately predict sudden traffic congestion in real time. By collecting data from existing optical fiber communications cables and analyzing real-time traffic flow data using a proprietary AI model, NEC has reduced prediction errors by 80% compared to conventional methods.This technology enables effective traffic control, including the arrangement of detour routes, thereby contributing to the resolution of societal challenges such as logistics issues and CO2 emissions.Technology OverviewTraffic congestion is a significant social issue, threatening safety and causing substantial economic losses. In particular, congestion on expressways—the backbone of many logistics networks—has a significant economic impact. Addressing this issue requires real-time understanding of road conditions for both immediate congestion mitigation and proactive avoidance, as well as highly accurate congestion prediction based on up-to-date data.Current monitoring approaches primarily rely on point-based instruments, including cameras and loop detectors, as well as probe vehicle data (*1). However, both have limitations: the former is costly to install and maintain over entire road networks, and the latter only provides data when equipped vehicles pass by specific receiver points, limiting real-time and continuous coverage. Moreover, existing congestion prediction models heavily rely on long-term historical data, making it difficult to capture the emergence and propagation of sudden, unexpected congestion patterns.To address these challenges, NEC has developed a technology that utilizes optical fiber cables—originally installed for communications purposes alongside roads—as extensive, distributed sensors for collecting real-time, continuous traffic flow data across entire routes. NEC’s unique AI-powered model then provides real-time, high-precision predictions regarding the development and clearance of sudden congestion.Technical FeaturesNEC has developed a data assimilation algorithm that combines advanced model parameter optimization and data adapting techniques, enabling accurate simulations of real-time traffic flow using comprehensive data collected along the entirety of roadways.Model Parameter Optimization AlgorithmNEC has created an algorithm to optimize theoretical model parameters—such as driver behaviors (e.g. inter-vehicle distance adjustment)—so that simulations faithfully reproduce observed traffic flow data for entire road segments.Data Adaptation AlgorithmAn advanced algorithm converts diverse traffic flow data, including "average speed" and individual vehicle "position/speed," into formats compatible with simulation inputs. This makes it possible to set the initial conditions for simulations based on comprehensive traffic flow data obtained on entire routes, significantly enhancing the reliability of simulation outputs.Through these innovations, NEC has confirmed—using real-world data—that travel time prediction errors (a key indicator for congestion forecasting) can be reduced by approximately 80% compared to the existing method that relies on cross-sectional data from point sensors such as cameras. NEC is further advancing the realization of a dynamic road digital twin that enables real-time, network-wide traffic monitoring, the prediction of congestion evolution, and optimization of responsive measures. Real-world trials are currently underway in close collaboration with road authorities, with the goal of practical deployment by fiscal 2026.This technology was developed using data provided by Central Nippon Expressway Company Limited (NEXCO CENTRAL) and was presented at the Transportation Research Board 104th Annual Meeting (*2). NEC will also present a related paper at the 31st ITS World Congress in Atlanta, Georgia, USA, focused on enhancing the accuracy of traffic flow monitoring on expressways (*3).(*1)A system that automatically collects driving data—such as the location and speed of vehicles equipped with onboard units—using roadside sensors installed at intervals ranging from several to tens of kilometers.(*2)Presentation ID TRBAM-25-01491, "A Novel Approach to Real-Time Short-Term Traffic Prediction based on Distributed Fiber-Optic Sensing and Data Assimilation with a Stochastic Cell-Automata Model," presented at the Artificial Intelligence–Based Solutions for Traffic Modeling and Control.(*3)Session ID: PS31 Transportation Systems: Traffic Management and Operations, Next-Generation Traffic Management Approaches Title: TSE (Traffic State Estimation) in Congestion to Extend the Applicability of DFOSAbout NEC CorporationThe NEC Group leverages technology to create social value and promote a more sustainable world where everyone has the chance to reach their full potential. NEC Corporation was established in 1899. Today, the NEC Group’s approximately 110,000 employees utilize world-leading AI, security, and communications technologies to solve the most pressing needs of customers and society. For more information, please visit https://www.nec.com, and follow us on Instagram, Facebook, and LinkedIn. Copyright 2025 JCN Newswire via SeaPRwire.com. All rights reserved. www.jcnnewswire.com