Quartus Engineering provides precision engineering services including optical systems design, metrology solutions, advanced simulation, and prototyping for aerospace, defense, and high-tech applications.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
MoSense, a company specializing in multimodal tactile solutions for robotics, has successfully completed an angel funding round worth several million yuan. Investors include Sequoia China, Hillhouse Capital, and Zhiyuan Robotics. The funds will primarily accelerate research and development, team expansion, computational power investment, and production testing system establishment. Founded in May 2026 and headquartered in Shanghai, with a research center in Shenzhen, MoSense focuses on developing a comprehensive multimodal tactile perception system for robots. The company aims to enhance robots' environmental perception capabilities, which are crucial for their deployment in complex real-world scenarios such as industrial manufacturing and logistics. Looking ahead, MoSense plans to commercialize its multimodal tactile solutions across various industries beyond humanoid robotics. The company is developing a tactile feedback system that integrates multiple sensory modalities, which is essential for improving robots' interaction with their environments. No further timeline was disclosed at the time of publication.
BXI Robotics, a humanoid robot ODM provider, has recently completed a new funding round worth millions, with investment from A-share listed company Suochen Technology. The funds will primarily support the development of next-generation humanoid robots and expansion into overseas markets. Previously, BXI Robotics secured its first round of institutional financing in 2025 from Feirongda. Founded in 2022, BXI Robotics has been developing humanoid robots since 2020. The company focuses on high-dynamic bipedal humanoid robots and is one of the few teams in China capable of full-stack self-research, including machine design, core motors, motion control algorithms, and software delivery. BXI Robotics aims to meet the growing ODM market demand as many companies seek to quickly establish their own humanoid robot brands. Looking ahead, BXI Robotics plans to enhance its capabilities in end-effectors, perception, and computation to improve robots' ability to execute tasks autonomously. The company anticipates significant growth in orders and revenue, projecting monthly order amounts to exceed ten million yuan from July 2026 to July 2027, with a total annual revenue expected to surpass one hundred million yuan. No further timeline was disclosed at the time of publication.
As attention focuses on companies like Tesla and Agility Robotics, a crucial battle is unfolding in the robotics sector: the competition for components. This less visible yet significant struggle highlights that the ultimate beneficiaries may not only be the manufacturers of final products but also the suppliers of essential technologies that power robots across various designs and applications. Morgan Stanley emphasizes this perspective, suggesting that the companies providing critical components for robots will play a pivotal role in the industry's future. Historical economic trends indicate that technological revolutions often favor infrastructure suppliers, as seen during the gold rush and the rise of AI, where companies like NVIDIA and TSMC emerged as key players. Among the vital components, precision bearings are particularly important, as they are necessary for every joint, motor, and rotating mechanism in robots. Advanced humanoid robots can incorporate over 70 bearings, which are essential for ensuring precision, durability, and reduced friction in their movements. No further timeline was disclosed at the time of publication.
À la une IA Industrie Robotique actionneurs robotiques caméras industriellesEnterprise AI agents are transitioning from laboratory environments to corporate systems, enabling them to track workflows, generate reports, and make decisions across various applications. This shift enhances operational speed and service quality but also places significant demands on existing technical infrastructures. The importance of robust AI agent infrastructure cannot be overstated, as it must accommodate fluctuating workloads, ensure secure access, and maintain data integrity. Without a solid foundation, AI agents may excel in pilot programs but struggle with reliability when integrated into live systems with larger datasets and user bases. Looking ahead, organizations must prioritize capacity planning guided by reporting and internal deadlines. As AI agents require organized and accurate data access to function effectively, businesses must establish clear rules for data retrieval and management. No further timeline was disclosed at the time of publication.
AI agents Infrastructure agentic ai ai agents AI infrastructure API integrationThe development of robotics begins long before physical assembly, relying heavily on simulations to validate designs and refine algorithms. These simulations demand significant computational resources, making system benchmarking crucial to identify hardware limitations early in the process. By measuring workstation performance under demanding workloads, engineers can establish a performance baseline that aids in spotting potential bottlenecks. Understanding how different hardware components affect simulation performance is essential for robotics development. Whether using macOS, Windows, or Linux, benchmarking helps determine if slowdowns are due to software changes or hardware limitations. Key components such as the processor, graphics card, memory, and storage play varying roles in performance, and the weakest link can dictate the overall experience. As robotics projects grow in complexity, the need for robust hardware becomes increasingly important. Engineers should focus on comprehensive benchmarking to ensure their systems can handle the demands of their simulations. No further timeline was disclosed at the time of publication.
Components Robot simulation ABB RobotStudio automation cpu delmiaBrainCo, based in Hangzhou, has introduced a groundbreaking robot platform that allows users to control robots using only their thoughts through EEG headsets. This advancement signifies a major step forward in embodied AI technology, where artificial intelligence is integrated into physical machines, enabling them to interact with the real world. The significance of this development lies in its potential to revolutionize human-robot interaction. By utilizing electroencephalogram (EEG) headsets, BrainCo's platform captures brain signals and employs AI algorithms to decode these signals, translating user intentions into robotic actions. This capability could enhance various applications across industries, making robots more intuitive and responsive to human commands. Looking ahead, the platform's compatibility with diverse third-party hardware, including humanoid robots and robotic arms, suggests a wide range of potential use cases. As the competition among global technology firms intensifies in the realm of embodied AI, BrainCo's innovation will be crucial to monitor for its impact on the future of robotics and AI integration. No further timeline was disclosed at the time of publication.
During a media briefing on July 15, Digua Robot's CEO, Wang Cong, stated that there are currently no industry standards for the computing power required for embodied intelligence chips. He emphasized the uncertainty surrounding chip performance, data standards, algorithms, and practical applications in the sector. Wang noted that Digua Robot is among the few companies already delivering products, having partnered with over 20 leading clients, including companies like Shizhi Navigation and UBTECH. Their Sun S600 chip is set to be deployed in various scenarios, including humanoid robots and industrial applications, with significant progress reported in the past six months. Looking ahead, Wang believes that the industry is not yet in a phase of intense competition, as many players have yet to produce viable products. He highlighted the importance of refining product quality and responding to customer needs, while also addressing the challenges of cost-effectiveness and system integration in deployment processes. No further timeline was disclosed at the time of publication.
Embodied Intelligence Chip Technology Robot Partnerships Industrial AutomationOn July 16, the Japanese government announced a plan to purchase 27,500 next-generation Rubin architecture AI chips from NVIDIA, totaling approximately $2.4 billion. This initiative aims to build a national AI data center and develop domestic robotics foundational models, marking one of the largest national GPU procurements globally. The project is coordinated by Noetra Corp., a policy-driven AI company set to launch in January 2026, with participation from major Japanese firms like Sony, SoftBank, NEC, and Honda. The Rubin chips will be deployed in a large data center in Sakai City, Osaka, with operations expected to begin in June 2028. Noetra aims to release its first general AI model by March 2027, followed by specialized AI models for robotics applications. Japan's investment reflects its response to ongoing demographic challenges and labor shortages. NVIDIA's CEO emphasized the potential for automation and AI to revitalize the economy. The Japanese government has set a goal to capture over 30% of the global robotics market by 2040, with the Rubin order being part of a broader strategy to reduce reliance on foreign technology and enhance national security.
AI Chips Robotics National AI Strategy Data CentersOn July 16, Japan's Ministry of Economy, Trade and Industry announced a significant investment of 387.3 billion yen (approximately $2.4 billion) to support the AI company Noetra. This funding will be used to procure around 27,500 NVIDIA Rubin GPUs for the establishment of a national AI data center, marking one of the largest single-country chip procurements globally. This initiative is crucial as Japan aims to address its declining population and severe labor shortages. The government has set a clear target to capture over 30% of the global 60 trillion yen robotics market by 2040. Noetra, which was established in January 2026 and includes major companies like Sony, SoftBank, NEC, and Honda, aims to develop advanced multimodal AI models capable of understanding Japanese language and recognizing various forms of media. Looking ahead, Noetra plans to release its first general-purpose AI model by March 2027, followed by continuous iterations and specialized models for robotics applications. The deployment of the Rubin chips in a large data center in Sakai, Osaka, is scheduled for June 2028, positioning Japan to lead in the next era of AI and robotics integration.
AI Technology Robotics NVIDIA Chips Data CentersOn July 16, NVIDIA CEO Jensen Huang announced an expansion of collaboration with Japanese companies in the field of 'physical AI' during an event in Tokyo. This initiative marks a strategic move to integrate NVIDIA's technology into Japan's manufacturing sector, particularly through a partnership with Toyota to develop AI models for the Woven City traffic control system. The collaboration with Toyota is central to NVIDIA's strategy, as the company will provide GPUs and development tools to Toyota's subsidiary, Woven by Toyota. This partnership aims to embed NVIDIA's technology into the city's digital twin platform, Omniverse, enhancing factory production and driving manufacturing robots with the Isaac platform. Additionally, Huang revealed plans to deepen cooperation with major Japanese industrial automation firms, including Fujitsu, Fanuc, Yaskawa Electric, and Kawasaki Heavy Industries, as part of the Cosmos Coalition. This initiative aims to strengthen Japan's position in the global AI robotics market, with a government goal of achieving a 30% market share by 2040. No further timeline was disclosed at the time of publication.
Physical AI Robotics Industrial Automation AI Technology
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