San Francisco Circuits
PCB fab & assembly specialist for defense, robotics, and aerospace; ISO 9001, ITAR, CMMC Level 2 certified; San Mateo, CA.
San Francisco Circuits is a US PCB manufacturer specializing in advanced printed circuit board fabrication and assembly for defense, aerospace, medical, and robotics applications. Founded in 2005 and headquartered in San Mateo, California, the company produces complex multilayer PCBs, rigid-flex, HDI, flex, metal core, and mil-grade boards. It holds ISO 9001:2015 and ITAR compliance and achieved CMMC Level 2 certification in 2026.
The company serves system integrators in drone, UAV, UGV, and robotic platforms, and adheres to IPC 6012 Class III standards.
Primary type & automation activities this supplier delivers:
Contact San Francisco Circuits
WEBSITE
https://www.sfcircuits.comPHONE
+1 650-654-7513HEADQUARTERS
United States
Company Facts
Founded
2005
Primary Role
Manufacturer
Company Size
employees 10-50
Primary Region
North America
Annual Sales
$1 – $4.9 Million
Funding Stage
-
Funding Total
-
Certifications & Memberships
Sharpa Launches Three Innovative Products at IROS to Enhance Robotic Precision
On September 28, Sharpa unveiled three innovative products at the International Conference on Intelligent Robots and Systems in Pittsburgh, USA. These include the D01 integrated tactile perception robot, the W02 ultra-compact and lightweight dexterous hand, and the AE01 high-fidelity exoskeleton tactile data glove. Each product targets specific operational needs, providing a complete hardware closed-loop for complex contact operations in real environments. The significance of these products lies in their ability to address the challenges of speed, power, and precision in robotic tasks. The D01 robot is designed for high-speed and high-precision operations, achieving a maximum end-effector speed of over 10.5 meters per second and a repeat positioning accuracy of 0.2 millimeters. The W02 hand integrates 21 active degrees of freedom in a compact structure, while the AE01 glove captures natural hand movements for precise teleoperation, enhancing the overall operational capability of robots. Looking ahead, the combination of D01, W02, and AE01 represents a complete operational capability closed-loop in embodied intelligence. This approach aligns with trends in the industry, where companies are focusing on integrating execution hardware, perception hardware, and data sources to improve robotic dexterity and responsiveness in various applications, including industrial collaboration and home services. No further timeline was disclosed at the time of publication.
Robotic Manipulation Tactile Sensing Haptic Technology Robotic Hands
EPFL and NYU Develop Scalable Robotic Fish for Diverse Aquatic Environments
A team from EPFL and NYU has introduced ScaFi, a scalable robotic fish designed to adapt to various aquatic environments. Unlike traditional propeller-driven vehicles, ScaFi mimics the swimming motion of fish, allowing it to navigate shallow waters and dense vegetation without disturbing wildlife. The significance of ScaFi lies in its ability to maintain swimming efficiency across different sizes, which could reduce the engineering effort required for aquatic robots. The research highlights the importance of adaptable tools for environmental monitoring, as ecosystems vary greatly in size and complexity. Future developments will focus on understanding the energy efficiency of ScaFi as it scales, as initial tests revealed challenges with larger models. The team aims to explore whether the energy performance can be improved alongside the swimming capabilities of the robotic fish.
Chen Pu of Yuan Ke Vision Discusses Transitioning Robot Training Data from 2D to 4D with High Precision
On September 23, Chen Pu, Vice President of Product Development at Yuan Ke Vision, highlighted the importance of high-quality real data for robot training during a seminar in Beijing. He emphasized the need to elevate data from 2D to 4D and improve precision from centimeter to sub-millimeter levels to build a robust 4D data foundation for robotics. This transition is crucial as the industry faces challenges such as weak model generalization and inadequate scene adaptability. Chen noted that current training methods often rely on limited 2D video data, which fails to capture the complexities of three-dimensional space and temporal changes, hindering robots' ability to understand and interact with their environments effectively. Looking ahead, Yuan Ke Vision aims to address these challenges by developing new data collection and training paradigms that enhance dimensionality, enrich modalities, and improve precision. Chen pointed out that while video data serves as a foundation, it is often too simplistic, and the lack of tactile data remains a significant gap in the industry. No further timeline was disclosed at the time of publication.
Robot Training Data 4D Data Collection Industrial Robotics Embodied Intelligence Precision Robotics
Niantic Spatial Introduces Places Library Featuring 100 Real Environments for Robot Training
Niantic Spatial has launched its Places Library, providing robotics developers with a catalog of 100 real environments for training and evaluation. The assets, available as USDZ files, include two representations for each environment: a Gaussian splat for visual appearance and a mesh for collision detection. This initiative aims to enhance embodied AI training by offering realistic settings that align with gravity and support various simulators, including NVIDIA Isaac Sim. The significance of this launch lies in its potential to improve robot training efficiency. By utilizing real-world environments captured with a standard 360-degree camera, Niantic ensures that robots receive accurate visual and collision data, which is crucial for effective navigation and interaction. The library includes diverse settings, such as medical warehouses and urban streets, allowing developers to test their robots in varied scenarios without the need for extensive in-house data collection. Looking ahead, the Places Library could facilitate more advanced evaluations of robotic behavior in different environments. While the library's impact on performance across the 100 environments remains to be seen, it offers a valuable resource for robotics teams aiming to refine navigation tasks and adapt to changing surroundings. No further timeline was disclosed at the time of publication.
Niantic Spatial Flexion
Memo Unveils Physical-WAM to Enhance Embodied Intelligence at Global Digital Trade Expo
At the Global Digital Trade Expo on September 24, Memo introduced the Physical-WAM, the world's first physical-world action model equipped with physical perception capabilities. This innovation aims to address the challenges faced by robots in understanding and interacting with the physical world, which has hindered the widespread adoption of embodied intelligence. The significance of this development lies in its potential to bridge the data gap that currently limits robots' physical interactions. Memo's CEO, Li Minghao, highlighted that the lack of foundational physical understanding in robots stems from insufficient real-world interaction data and inadequate evaluation metrics. The Physical-WAM model is designed to enhance robots' predictive capabilities and real-time adjustments in physical tasks. Looking ahead, the demand for embodied intelligence is surging, with significant investments in the sector. However, challenges remain in aligning order fulfillment with funding growth. As the industry evolves, the effectiveness of solutions like Physical-WAM will be crucial in overcoming existing barriers to practical implementation.
Embodied Intelligence Physical AI Robotics Machine Learning
Robot Dogs Use Insect-Inspired Movements to See Through Obstructions in 17 Milliseconds
A collaborative team from Johannes Kepler University Linz, Free University of Bozen-Bolzano, University of Trento, and University of Sussex has developed a method for robot dogs to mimic insect movements to enhance their visual perception. By performing rhythmic lateral movements, akin to the 'peering' behavior observed in insects like locusts, these robots can effectively see through obstructions such as foliage and debris. This innovation is significant as it addresses a common challenge faced by exploration robots in environments cluttered with obstacles that hinder visual sensors. The research establishes a connection between the peering motion and synthetic aperture sensing, allowing the robots to create a virtual aperture that enhances background signals while blurring out obstructions. Future developments to watch include the potential applications of this technology in various environments, including forests and disaster sites. The research indicates that the synthetic aperture technique is most effective at around 50% obstruction density, suggesting a promising avenue for improving robotic vision in complex terrains. No further timeline was disclosed at the time of publication.
Robotics Computer Vision AI Obstacle Detection
RobotToday Weekly September 21 – 25, 2026
Cognex buys RealSense, Qualcomm acquires PickNik, the IFR counts 5 million factory robots, AGIBOT deploys 300 robots at Chimelong, and Tekever raises $580 million.
Mondo Robotics' Beni: A Tumbling Robot Camera with Significant Obstacle Avoidance Issues
Mondo Robotics has introduced Beni, a small bipedal robot designed to capture and record video while following users. Equipped with a built-in camera and sensors, Beni can perform tricks like flips and roll while tracking specified objects via an app. However, after several weeks of testing, reviewers found Beni's obstacle avoidance capabilities severely lacking. The importance of Beni lies in its potential as a fun companion for personal activities like sports and pet video recording. Despite its interesting features, the robot struggles significantly with obstacle avoidance, often losing track of its target in cluttered environments. Reviewers noted that even in open spaces, Beni failed to navigate around obstacles effectively, which detracts from its overall usability. Moving forward, it will be crucial to monitor Mondo Robotics' efforts to improve Beni's obstacle avoidance technology. Currently priced at $599, the robot's value is questionable given its primary flaw. If Mondo can address these issues, Beni could become a more appealing option for users engaged in various activities, but until then, recommendations are limited.
Robot Cameras Obstacle Avoidance Consumer Robotics Video Technology
Noin Introduces GLOW Architecture for Instant Learning in Robotics
Noin has unveiled the GLOW architecture, a generative learning framework aimed at enhancing robot learning capabilities. This new technology allows robots to learn tasks instantly without the need for extensive data collection or predefined processes, addressing the challenges posed by dynamic real-world environments. GLOW's core innovation lies in its ability to enable robots to learn tasks through a single demonstration, transforming visual input and feedback into actionable tasks. The significance of GLOW is underscored by its potential to revolutionize how robots acquire skills, moving away from traditional methods that require separate strategies for each task. Instead, GLOW aims to equip robots with generalized capabilities that can be applied across various objects, environments, and tasks. This shift could lead to more efficient and adaptable robotic systems, as users will no longer need to break down their requirements into machine instructions. Future developments to watch include Noin's ongoing commitment to advancing the GLOW technology, which integrates visual understanding, spatial reasoning, task planning, and action generation within a unified model. The architecture has already shown promising results in various evaluations, indicating its effectiveness in physical scene understanding and task execution, paving the way for enhanced robotic intelligence and adaptability.
Robotics Generative Learning AI Embodied Intelligence
The Importance of a Comprehensive Network for Robotics: Insights from the 2026 Information Communication Expo
The 2026 China International Information Communication Expo highlighted the necessity of a comprehensive network for robotics, showcasing advancements in embodied intelligence. The expo featured technologies essential for robotic tasks, including perception, decision-making, motion control, and human-robot interaction, emphasizing the integration of these elements for effective operation. This focus on connectivity is crucial as robots must adapt to various environments, ensuring safety and efficiency in tasks ranging from industrial applications to healthcare. The expo demonstrated how robots can be integrated into smart factories and homes, where they must understand human needs and operate safely in shared spaces. The success of robotic systems relies not only on their ability to perform complex actions but also on their operational stability and cost-effectiveness. Looking ahead, the 2026 initiative for humanoid robots and embodied intelligence aims to enhance real-world training and application validation. The emphasis on reliable real-time control, stable connectivity, and effective data utilization will be key to advancing robotic capabilities and ensuring their successful deployment in diverse environments. No further timeline was disclosed at the time of publication.
Embodied Intelligence Robotics Technology Smart Factories Healthcare Robotics
Academician Zheng Nanning Discusses Embodied Intelligence Beyond Humanoid Robots
Academician Zheng Nanning, Director of the Artificial Intelligence and Robotics Institute at Xi'an Jiaotong University, published an article discussing the growth of embodied intelligence in the physical world. He emphasized that a key direction for artificial intelligence is enabling machines to not only process information but also to flexibly perform various tasks in dynamic environments. This includes precise operations on industrial production lines, autonomous navigation in complex terrains, and dynamic movements in exhibition settings. Zheng clarified that embodied intelligence is not synonymous with humanoid robots; rather, it focuses on whether intelligent systems can truly engage with real-world environments, forming a closed loop of perception, cognition, decision-making, action, and feedback. The evaluation of embodied intelligence should be based on its ability to solve real-world problems, not merely its physical form. He likened understanding embodied intelligence to an infant's process of learning about the world through interaction with their environment. To enable machines to act in the world, embodied intelligence requires various capabilities, including the formation of world models, multimodal representation, causal reasoning, and the integration of generation and action. The development of embodied intelligence relies on high-quality multimodal data and realistic simulation environments. Current limitations include the black box problem, computational constraints, and an immature industrial ecosystem. In sectors like industrial manufacturing, healthcare, and urban governance, intelligent systems are evolving from mere tools to proactive systems capable of continuous learning and adaptation.
Embodied Intelligence Artificial Intelligence Robotics Machine Learning
ROBOTTODAY Weekly July 13 – 17, 2026
This week in robotics: Hyundai takes full ownership of Boston Dynamics, Xpeng targets 1,000 Iron humanoids a month, LimX Dynamics raises $200M pre-IPO, and Agility opens a Silicon Valley physical-AI hub. July 13–17, 2026.
2026H2 Robotics Events Briefing: Tailored Recommendations for Robotics Readers
Discover the ultimate directory of global robotics events in 2026. Tailored briefings for engineers, investors, and founders on humanoid robots, AI, and industrial automation by RobotToday.
Robot.com Launches R-noid Humanoid Robot for Industrial and Service Sectors
Robot.com announces R-noid, a general-purpose humanoid robot deployed via RaaS across five solution categories and six industry verticals. Operational in 8–12 weeks. Debuting at Automate 2026.
ROBOTTODAY Weekly, June 15 – 19, 2026
This week in robotics: Japan commits $65B to physical AI, UBTECH’s U1 humanoid companion robot nears 5,000 pre-orders, XDOF raises $70M for robot foundation model infrastructure, and Waymo recalls ~3,900 robotaxis after construction-zone failures. June 15–19, 2026.
Vietnam Robotics Industry Report 2026
Comprehensive analysis of Vietnam's robotics industry: market size, industrial policy, key companies (Vingroup, Apicoo, Phenikaa-X), geopolitical dynamics, and 2030 growth opportunities.
AGRICULTURAL ROBOTICS SERIES — Company Directory 2026
Access the definitive 2026 directory of 150+ agricultural robotics companies. A comprehensive reference guide covering autonomous tractors, harvest automation, precision weeding, and AI data platforms across the global agtech ecosystem.
ROBOTTODAY Weekly April 13 – 17, 2026
This week in robotics: AGIBOT declares Deployment Year One with 5 platforms and 8 AI models at APC 2026, Physical Intelligence’s π0.7 solves unseen tasks, TARS raises a record $455M, and Siemens deploys humanoids in live factory operations. April 13–17, 2026.
FUTURE WARFARE | Land - Unmanned Ground Vehicles — From Logistics Mules to Front-Line Robots
Ukraine fielded 15,000 unmanned ground vehicles in 2025 — surpassing its own procurement targets by over 100 percent. A single UGV held a front-line position for 45 days. Up to 90 percent of supplies to Pokrovsk now move by robot, not truck. The U.S. Army cancelled its $3 million Robotic Combat Vehicle and is starting over. China is deploying $3,000 robot dogs in PLA urban-warfare exercises. This article maps the emerging UGV battlefield — from Ukraine’s garage-built logistics fleet to the Pentagon’s stalled combat-vehicle ambitions, and from Ghost Robotics’ Vision 60 to the quadruped proliferation problem no treaty has yet addressed.
ROBOTTODAY Weekly Industry Briefing March 30 – April 4, 2026
Your weekly robotics briefing: AGIBOT ships its 10,000th humanoid, UBTech reports a 23-fold revenue surge, Baidu robotaxis freeze in Wuhan, Saronic raises $1.75B, and Generalist’s GEN-1 hits 99% task success. March 30 – April 4, 2026.
