Blue Dot Touch / Link-Touch 蓝点触控
Beijing sensor maker founded in 2019; builds six-axis force/torque and joint-torque sensors for humanoid robots and industrial force control.
Blue Dot Touch (Beijing Blue Dot Touch Technology Co., Ltd.), operating in English as Link-Touch, is a Chinese sensor manufacturer founded in 2019 and based in Beijing. Its founding team is drawn from the China Academy of Space Technology, the University of Science and Technology of China and the Chinese Academy of Sciences, with founder Liu Wuyue having a background in aerospace technology development.
The product range covers six-axis force/torque sensors, joint-torque sensors and tension-compression sensors, organized into a humanoid-focused LA (six-axis) and LC (joint-torque) series and an industrial LB, LD and LE series, along with flexible robotic grinding and polishing systems built on the same sensing hardware. The sensors use aerospace-grade aluminum-alloy housings and are specified for repeatability near 0.1 percent of full scale, accuracy near 0.3 percent of full scale and overload capacity up to 500 percent, in form factors sized for robot wrists and joints. Blue Dot Touch has completed a Series B financing round of close to RMB 100 million to expand production of its force-sensing hardware.
Company-reported figures put Blue Dot Touch's share of China's six-axis force-sensor market for humanoid robots near 70 percent and its share of the joint-torque-sensor segment near 95 percent, positioning it as a supplier to multiple domestic humanoid-robot developers.
Primary type & automation activities this supplier delivers:
LA Series Humanoid Six-Axis Force/Torque Sensor
- Model: LA35
- Launch Year: 2024
Compact six-axis force/torque sensor measuring Fx/Fy/Fz and Mx/My/Mz for humanoid robot wrists and joints.
Contact Blue Dot Touch / Link-Touch
WEBSITE
https://www.link-touch.com/HEADQUARTERS
China
Company Facts
Founded
2019
Primary Role
Component Supplier
Company Size
-
Primary Region
Asia-Pacific
Annual Sales
-
Funding Stage
-
Funding Total
-
Odyssey Unveils Odyssey-3, a Groundbreaking World Model for Robotics and AI
Odyssey, an AI research company, has launched Odyssey-3, its most advanced world model to date. This model represents a major leap towards general-purpose intelligence, enabling systems to understand, predict, and interact with both physical and virtual environments. Odyssey-3 can control robots, humanoids, vehicles, and drones, and has already been adopted by companies like Flexion. The significance of Odyssey-3 lies in its ability to provide intelligent systems with a foundational understanding of the world, allowing them to learn new tasks more efficiently. By leveraging a vast dataset of visual observations, the model has developed insights into physics, dynamics, and human behavior, which can be applied across various systems. This capability marks a shift in how AI can adapt and operate in diverse environments with minimal additional training. Looking ahead, the focus will be on how Odyssey-3 can further enhance the capabilities of physical agents in different applications. As Oliver Cameron, co-founder and CEO of Odyssey, stated, the model is a crucial step towards achieving a single intelligence that can seamlessly operate across multiple tasks and environments. No further timeline was disclosed at the time of publication.
New 'SANDO' System Keeps UAVs Safe from Collisions in Wildfire Areas
The 'SANDO' system enhances the safety of uncrewed aerial vehicles (UAVs) by ensuring their flight paths remain collision-free, particularly in hazardous environments like wildfires. This technology is crucial as UAVs are often deployed to gather vital information in such dangerous situations, where they face risks from sudden flare-ups and falling debris. The importance of the 'SANDO' system lies in its ability to protect UAVs from potential damage during operations in uncharted territories. By avoiding collisions with obstacles such as tree branches, the system allows for safer data collection, which is essential for rescuers responding to wildfires. This advancement could significantly improve the effectiveness of UAVs in emergency response scenarios. Looking ahead, the implementation of the 'SANDO' system could lead to broader applications of UAVs in various challenging environments. As the technology develops, stakeholders will be keen to observe its impact on UAV operational safety and efficiency in disaster response efforts. No further timeline was disclosed at the time of publication.
Robotics
Assessing Pose Estimation Uncertainty in Multi-Sensor Robotic Systems via Point Cloud Registration
The study published in the Journal of Field Robotics evaluates the uncertainty in pose estimation arising from automatic point cloud registration in multi-sensor robotic systems. This research is crucial as accurate pose estimation is vital for the effective operation of robotic systems in various applications. Understanding the uncertainty in pose estimation can significantly enhance the reliability and performance of robotic systems, especially in complex environments where multiple sensors are utilized. The findings of this study could lead to improved algorithms and methodologies for better integration of sensor data, ultimately benefiting industries that rely on advanced robotics. Looking ahead, researchers and engineers should monitor developments in pose estimation techniques and their applications in real-world scenarios. No further timeline was disclosed at the time of publication.
RESEARCH ARTICLE
MIT Develops SANDO: A Collision-Free Navigation System for UAVs in Unknown Environments
MIT researchers have developed an autonomous navigation system named SANDO, designed for uncrewed aerial vehicles (UAVs) to navigate safely in unpredictable environments. This system ensures that UAVs can avoid collisions with unknown moving obstacles, which is crucial in high-risk scenarios like search and rescue missions or disaster response. The significance of SANDO lies in its ability to provide formal safety guarantees in dynamic environments, where traditional navigation systems fall short. Unlike existing planners that only work in static settings or lack formal guarantees, SANDO uses a mathematical approach to ensure collision avoidance, making it particularly valuable for applications requiring real-time adaptability. Looking ahead, the potential applications for SANDO are vast, including emergency medical supply deliveries and exploration in hazardous areas. As the technology matures, it could revolutionize how UAVs operate in complex environments, enhancing safety and efficiency. No further timeline was disclosed at the time of publication.
Research Computer science and technology Algorithms Drones Robotics Autonomous vehicles
TwelveLabs Launches Pegasus 1.6 for Enhanced Video Understanding in Physical AI
TwelveLabs Inc. has unveiled its Pegasus 1.6 model, designed to enhance video understanding for physical AI applications. This model addresses the challenge of transforming complex video footage into actionable insights, enabling robotics and AI teams to train on real human experiences rather than starting from scratch. The significance of Pegasus 1.6 lies in its ability to provide temporal context, spatial reasoning, and task completion judgment, which are crucial for machines to navigate real-world environments. According to Jae Lee, co-founder and CEO of TwelveLabs, the model allows for a more precise understanding of actions and interactions captured in egocentric video, facilitating the development of smarter robotics systems. Looking ahead, TwelveLabs aims to further refine its video intelligence platform, focusing on the video understanding layer to improve training data for robotics teams. The company emphasizes that Pegasus 1.6 can utilize existing video data and analyze still images, making it a versatile tool for various applications in physical AI. No further timeline was disclosed at the time of publication.
Artificial Intelligence Artificial Intelligence / Cognition Assembly Human Robot Interaction / Haptics Manufacturing Microprocessors / SoC
Teledyne FLIR Introduces AI-Driven Air-to-Ground Tracking Software for UAS
Teledyne FLIR OEM has unveiled Prism A-ISR, a cutting-edge software module aimed at enhancing air-to-ground detection and tracking for uncrewed aircraft systems (UAS) and airborne intelligence, surveillance, and reconnaissance (ISR) platforms. Announced on October 6, this software leverages artificial intelligence to detect, classify, and track multiple ground objects in real time, utilizing data from various sensor types including midwave infrared (MWIR) and visible electro-optical (EO) sensors. The significance of Prism A-ISR lies in its ability to perform edge processing, enabling airborne systems to analyze sensor data independently of remote computing resources. This capability is crucial for applications requiring persistent surveillance and defense missions, as it enhances long-range situational awareness while minimizing false alarms. Teledyne FLIR's advanced image processing tools, including patented denoise and super-resolution technology, further improve detection capabilities in challenging conditions. Looking ahead, Teledyne FLIR's AIMMGen synthetic model-training service allows developers to quickly adapt the software for new target classes, streamlining the creation of mission models. The software is compatible with NVIDIA and Qualcomm embedded AI platforms and several Teledyne FLIR camera modules, including the NDAA-compliant Boson+ and Neutrino thermal camera families. No further timeline was disclosed at the time of publication.
AI Applications C-UAS Defense defense Drone News
Overview AI Introduces OV Spark and OV Spark Pro AI Inspection Cameras
Overview AI has launched the OV Spark and OV Spark Pro, a new line of AI inspection cameras featuring an agentic AI layer that communicates in plain English. The cameras come equipped with 10 inspection tools, including seven deep learning AI models and three ready-to-use tools for barcodes, measurements, and color matching. The introduction of the OV Spark cameras is significant as they address the challenges of consistency in inspection processes. Christine Chacko, a technical product marketing manager at Overview AI, highlighted that the cameras adapt to the shifting and rotating parts in a robot cell, ensuring accurate inspections. This innovation aims to enhance defect detection across factory lines. Looking ahead, Overview AI's mission is to ensure that every defect is caught in every factory, with the OV Spark designed to minimize setup work. The cameras are currently available for purchase directly from Overview AI and through distribution partners. No further timeline was disclosed at the time of publication.
Artificial Intelligence Artificial Intelligence / Cognition Cameras / Imaging / Vision Design / Development Manufacturing News
Epson Showcases Color Labeling and Robotic Automation at PACK EXPO 2026
Epson has announced its participation in PACK EXPO International, scheduled from October 18 to 21, 2026, where it will demonstrate its ColorWorks® on-demand color label printers, collaborative robots, and vision technology. These innovations aim to enhance the efficiency of packaging and fulfillment operations. The introduction of ColorWorks printers allows manufacturers to produce high-quality, customized color labels on demand, addressing the growing need for flexibility in labeling processes. Coupled with robotic automation, these solutions are designed to streamline various tasks, including handling, inspection, and packaging, thereby improving overall productivity. As the event approaches, industry professionals should watch for how Epson's integrated solutions can transform labeling and packaging workflows. No further timeline was disclosed at the time of publication.
OpenAI's GPT-6 Astra Dominates SuperCLUE's Robot-Brain Benchmark with Planning Superiority
OpenAI's GPT-6 Astra achieved the highest overall score in SuperCLUE's September 2026 EmbodiedCLUE-VLA evaluation, leading with a score of 85.71 in interaction and planning. This score significantly surpasses the runner-up, Gemini-3.8-Flash, which scored 64.29, highlighting Astra's notable advantage in planning capabilities. The importance of this evaluation lies in its comprehensive assessment of ten models, which includes basic perception, visual reasoning, interaction, planning, and embodied safety. SuperCLUE's report indicates that while Astra leads in overall performance, the evaluation's fixed input/output protocol may limit the generalization of results across different tasks and protocols, making it a useful but narrow comparison of each model's capabilities. Looking ahead, the next critical aspect to observe is how these models perform in real-world scenarios, particularly in executing plans and adapting to unforeseen circumstances. The results from physical trials will be essential to determine the practical applications of these models in robotics, beyond the theoretical scores presented in this benchmark.
OpenAI China
Robotics and Physical AI Addressing Key Physical Security Challenges in 2026
In 2026, over $23 billion has been invested in enhancing the integration of robotics and artificial intelligence for physical security. This investment aims to address the increasing complexity of threats against critical infrastructure, such as data centers and manufacturing plants. The adaptive capabilities of these technologies are essential for organizations to protect their assets effectively. The intersection of cybersecurity and physical protection presents new challenges, as demonstrated by the Jaguar Land Rover incident, where cyber breaches led to significant operational disruptions. Organizations must adapt to a rapidly changing security landscape, where legacy systems can exacerbate vulnerabilities. The need for proactive security measures is more pressing than ever, particularly in critical industries. At GTC Taipei 2025, companies like Foxlink showcased innovations such as the “robot dog,” designed to enhance physical security through adaptive functions and smart sensors. This technology represents a shift towards a more proactive security environment, enabling organizations to respond to complex threats effectively. No further timeline was disclosed at the time of publication.
Artificial Intelligence Artificial Intelligence / Cognition Automotive Autonomous Mobile Robots (AMRs) Cameras / Imaging / Vision Manufacturing
IROS 2026 Closing Briefing — Pittsburgh, Sep 27–Oct 1
IROS 2026 closes in Pittsburgh with 1,900+ papers and 186 exhibitor listings. Humanoids, dexterous hands, tactile sensing and robot data led the show.
PTC Onshape at IMTS 2026: AI That Writes Its Own CAD Tools
PTC's Darren Henry shows Onshape's FeatureScript MCP Server turning a supplier PDF into a parametric CAD tool in 34 minutes, and what it means for robots.
Software, Compute and Interaction at WRC 2026
47 WRC 2026 exhibitors supply robot software, compute or interaction — but only 19 call themselves software companies. Five open artefacts, licence-checked.
WRC 2026 Core Components: 137 Robot Parts Suppliers
The third report in the WRC 2026 series. Report 1 mapped all 248 exhibitors by category and Report 2 covered the 139 that build finished robots. This one covers the 137 that build what goes inside them.
WRC 2026 Robot Systems: 149 Companies That Build Robots
149 of the 248 classified WRC 2026 exhibitors build finished robots. 93 build humanoid or legged machines. The audited humanoid sales number is one unit.
Inside Saga Robotics: UVC Light vs. Crop Disease
Saga Robotics CPO Damian Flynn on the Thorvald platform's UVC treatment system, its jump from UK strawberries to California wine grapes, and why he's “incredibly bullish” on applying automation and robotics into industries “most chaotic environment.”
US Restrictions on Chinese Humanoid Robots: The Full Map
Every US restriction on Chinese humanoid robots — NDAA Sec. 163, GUARD Act, the 1260H list — plus the supply-chain math and a 4-tier map of decoupling.
Physical AI Landscape: From Digital Intelligence to the Embodied Physical World
A comprehensive industry analysis of Physical AI — covering Embodied AI, Field AI, Factory AI, VLM, World Model, VLA, and the VLA vs WAM architecture debate. Includes 20+ companies, 28 references, and the RobotToday Physical AI Landscape diagram. July 2026.
Doosan Robotics Unveils AI Palletizing Solution PalletizHD+ at Automate 2026
Doosan Robotics unveils PalletizHD+ at Automate 2026 — an AI-powered palletizing solution with PalletizOS, SwiftMove technology, and up to 11 boxes per minute throughput for smarter factory automation.
ROBOTTODAY Weekly May 23 – 29, 2026
This week in robotics: the Humanoids Summit debuts in Tokyo, China assigns every humanoid robot a digital ID, Figure signs a Catalyst Brands deployment deal, and Unitree heads to a June 1 IPO hearing. May 23–29, 2026.
