AI Motive (prev AdasWorks) (HU)
aiMotive (Hungary) develops automated driving tooling and embedded solutions for L2-L4 ADAS, using radar and camera inputs without HD maps. Products include aiSim 5 neural simulation software, automated data pipelines for ADAS feature development, and automotive NPUs with cloud emulation for CI/CD testing.
RobotToday Initiative
Robotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
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.
WAIC 2026: Embodied Intelligence Enters Industrial Deployment Era
WAIC 2026 in Shanghai (July 17–20) saw 200+ embodied intelligence companies, 300+ live robots, and first confirmed humanoid deployments in logistics and pharmacy. RobotToday engineering analysis.
Inside Guident: How Harald Braun Is Building the Safety Layer Every Autonomous Vehicle Needs
Guident CEO Harald Braun on the RMCC architecture, IRLS risk identification system, and why California’s 2026 AV mandates validate six years of platform development.
The Rise of Force Sensing Technology in China's Robotics Industry
Recent trends in the robotics industry indicate a shift from mere mobility to operational intelligence, particularly in humanoid robots. Companies are now focusing on practical applications such as tool handling and assembly, highlighting the importance of force sensing technology. As robots engage in physical tasks, understanding the force exerted becomes crucial for effective operation. This transition underscores the growing significance of six-dimensional force sensors, which are evolving from optional components in industrial robots to essential infrastructure for next-generation intelligent robots. The recent funding rounds exceeding 100 million yuan reflect a broader interest from both traditional investors and state-owned enterprises, signaling a pivotal moment in the industry's development. Looking ahead, the demand for comprehensive sensing, control, and manufacturing infrastructure will likely increase as the humanoid robotics sector matures. The complexity of enabling robots to perform sustained tasks, such as assembly and material handling, will challenge developers to innovate beyond flashy capabilities and focus on the intricate details that drive commercialization.
Humanoid Robots Force Sensing Technology Industrial Automation Robotics Innovation
Benchmarking Your Development System for Effective Robotics Simulations
The 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 delmia
Gravity Develops Unified Framework for Long-Range Complex Robotic Tasks
Gravity has introduced a unified embodied intelligence framework designed for long-range and complex robotic tasks. This framework, built on a Mixture-of-Transformers (MoT) architecture, integrates visual language models (VLM) for instruction and scene understanding, task reasoning, and world modeling to predict future states and evaluate sub-goals. It also incorporates tactile and force feedback, prior knowledge, and multi-modal supervision to enhance task execution and adaptability. The significance of Gravity's framework lies in its ability to improve the success rate of complex operations that require precise contact and autonomous error correction. By combining AR Transformer and Diffusion Transformer, Gravity enables robots to simulate multiple strategies and assess risks before executing tasks. This advancement shifts robotic capabilities from reactive responses to proactive planning, making it suitable for applications in precision assembly, complex sorting, and flexible manufacturing. Looking ahead, Gravity aims to further develop its complete system, having already implemented components like Gravity VLA and Gravity 4D WAM. The focus will be on enhancing the framework's ability to learn from real-world experiences, thereby creating a continuous feedback loop that improves operational efficiency and adaptability in various industrial contexts. No further timeline was disclosed at the time of publication.
Robotic Frameworks Embodied Intelligence Task Automation Machine Learning Robotics
GS Caltex Completes $135 Million Overhaul at Yeosu Refinery Using Robots and AI
GS Caltex announced the completion of a 200 billion won ($135 million) turnaround at its Yeosu refinery, utilizing robots, artificial intelligence, and digital tools to enhance safety and operational efficiency. This large-scale maintenance operation involved halting production for intensive inspections and replacing aged components, laying the groundwork for safer and more efficient plant operations. The significance of this turnaround lies in GS Caltex's integration of digital and AI solutions, which are part of the company's broader digital transformation strategy. By digitalizing core operational systems, the refinery aims to improve workplace practices and boost overall competitiveness. The deployment of technologies like MOVision and tube-cleaning robots addresses specific operational challenges, such as locating electric motor-operated valves and enhancing thermal efficiency. Looking ahead, GS Caltex plans to continue innovating within the manufacturing sector by leveraging its DAX strategies. The company's commitment to integrating on-site expertise with advanced technologies is expected to further enhance efficiency and safety in future operations. No further timeline was disclosed at the time of publication.
All News
KAIST Unveils Advanced Four-Legged Robot with Autonomous Navigation Technology
KAIST's mechanical engineering team, led by Professor Park Hai-won, announced a breakthrough in robotic technology on July 16. They developed a four-legged robot capable of autonomously selecting and switching between various gaits in real-time, enabling it to navigate complex outdoor environments with speed and stability. This innovation is significant as it integrates a new control architecture called APT-RL (Action Pre-training Reinforcement Learning based on Transformers), which allows the robot to learn movement through computer simulations rather than traditional motion capture. The robot, named KAIST HOUND, demonstrated its capabilities by traversing diverse terrains, achieving peak speeds of 6 meters per second, faster than an average cyclist. Future developments to watch include the potential applications of this technology in disaster response, defense tasks, and industrial inspections. The research was published in the July issue of the journal Science Robotics, highlighting its importance in advancing the field of robotic control and physical AI.
Four-Legged Robots Robotics Technology AI Autonomous Navigation
Control Method Developed for Heavy-Duty Hexapod Robot Navigating Border Terrains Using Simplified Model
A new control method has been developed for a heavy-duty hexapod robot designed to walk on border terrains, as reported in the Journal of Field Robotics. This method utilizes a simplified model to enhance the robot's navigation capabilities in challenging environments. The significance of this development lies in its potential applications in various sectors, including military and disaster response, where navigating difficult terrains is crucial. The heavy-duty hexapod robot's ability to traverse border terrains effectively could improve operational efficiency and safety in these scenarios. Looking ahead, the implications of this control method could lead to further advancements in robotic mobility and control systems. No further timeline was disclosed at the time of publication.
RESEARCH ARTICLE
ETCO Incorporated Launches New Electrical Connectors and Terminals for Robotics and Automation
ETCO Incorporated has unveiled a new range of standard and custom electrical connectors and terminals designed specifically for automation systems and robotics. These products are engineered to endure intense operations, constant motion, and vibration, making them suitable for demanding applications. The introduction of these connectors and terminals is significant as they address the growing need for reliable electrical components in automation and robotics. With the increasing complexity of automated systems, the durability and performance of electrical connections are crucial for operational efficiency and safety. Looking ahead, industry stakeholders should monitor the adoption of ETCO's new products in various applications. The effectiveness of these connectors and terminals in real-world scenarios will be key to their success in the market. No further timeline was disclosed at the time of publication.
Challenges in Scaling Industry 4.0: Insights and Necessary Changes
Despite over a decade of investment in Industry 4.0, significant scaling challenges remain. While the World Economic Forum's Global Lighthouse Network has recognized 223 advanced manufacturing sites as of January 2026, these examples highlight a small fraction of the global manufacturing landscape. Most manufacturers are still in the early stages of their digital transformation journeys, with localized progress rather than systemic change. The gap between technological potential and operational achievement is widening, particularly as artificial intelligence is introduced into environments not designed to support it. While many manufacturers have access to necessary tools, the real challenge lies in how these tools are utilized. Effective digital transformation requires a redefinition of operations, decision-making processes, and system support. To drive performance, manufacturers must focus on reducing decision latency—the time from signal to action. This involves better analytics, aligning data and systems, and treating data as operational infrastructure. A seamless flow of information from detection to decision to action is essential, alongside clear decision ownership as intelligence becomes more embedded in systems.
Factory / Digital Transformation
Manufacturers Must Prioritize Industrial Data Governance Before AI and Analytics
Manufacturers are generating unprecedented amounts of data through automation systems, capturing everything from process values to production metrics. However, many plants face challenges in quickly answering fundamental operational questions, such as equipment status during issues or alarm sequences. The root cause often lies in a lack of structured, contextualized data governance rather than insufficient data itself. As manufacturers increasingly invest in analytics and AI, the importance of a solid data foundation becomes critical. Structured data not only aids in generating meaningful reports but also enhances AI insights. Poorly designed automation systems can lead to disorganized data, resulting in confusion and inefficiencies that erode trust among operators and complicate reporting for engineers and maintenance teams. To address these challenges, manufacturers must focus on establishing effective data governance from the outset of automation system design. Collecting more data does not inherently create value; instead, organizing data around relevant categories is essential for it to be actionable. No further timeline was disclosed at the time of publication.
Factory / Analytics
Midea Group Signs 300 Million RMB Strategic Deal to Expand Industrial Robotics
Midea Group's subsidiary KUKA has signed a strategic cooperation agreement with YINGKE Medical and YINGKE Recycling, valued at over 300 million RMB. This deal includes 1,500 industrial robots, 500 mobile and embodied intelligent robots, and 50 automated storage systems, showcasing Midea's commitment to expanding its industrial robotics capabilities. This partnership signifies a pivotal shift for Midea, transitioning from project-level procurement to a comprehensive group-level strategic collaboration. The collaboration aims to enhance production efficiency through advanced automation solutions, integrating AI visual recognition and adaptive grasping technologies. Looking ahead, Midea's focus on its ToB business model is expected to accelerate, with KUKA playing a crucial role in this transformation. The industry will be watching closely to see how this strategic partnership evolves and contributes to Midea's growth in the industrial automation sector. No further timeline was disclosed at the time of publication.
Industrial Robotics Automation Solutions Smart Manufacturing B2B Technology
ROBOTTODAY Weekly July 6 – 10, 2026
This week in robotics: AI² Robotics raises $735M for wheeled humanoids, Unitree G1 performs first live surgery, Dexmal launches DexOS platform, Agility Robotics announces SPAC, and Ondas acquires DZYNE for $875.8M. July 6–10, 2026.
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.
Piaggio Fast Forward Brings kilo® Autonomous Mobile Robot to Automate 2026
Piaggio Fast Forward showcases kilo®, an infrastructure-free collaborative AMR (300 lb payload, 360° LiDAR), at Automate 2026 booth #17054.
LingBot-VLA 2.0: Open-Source Universal Brain for Robots
Robbyant open-sources LingBot-VLA 2.0, a vision-language-action model trained on 60,000 hours of data for cross-morphology, whole-body robot control.
Humanoid Robot Wire Harnesses Emerge as a Critical System Technology
A RobotToday engineering deep dive into humanoid robot wire harnesses: 3D dynamic fatigue, 10-100 Gbps EMI shielding, FPC cost reduction, and global standards.
Space Robot- Building Skyscrapers in Space: ISMA's Industrial Revolution
ISAM technology breaks rocket fairing limits through robotic space manufacturing. Market grows from $3.5B to $14.5B by 2032. See how 3D printing, autonomous assembly, and orbital fabrication are creating off-Earth factories.
RobotToday Weekly Industry Briefing: Feb 9 – 13, 2026
Feb 9-13, 2026: Apptronik raises $520M for humanoid production, GE Aerospace deploys AI robots for jet maintenance, Weave ships first laundry-folding robot, and IFR releases AI in robotics position paper. Physical AI reaches commercial scale across industry and home.
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