German manufacturer of quick-disconnect mono and multi-couplings and robot tool-changing systems with over 500,000 variants, serving industrial robotics and.
WALTHER-PRAEZISION Carl Kurt Walther GmbH & Co. KG, founded in 1931 and headquartered in Haan, Germany, is a global leader in quick-disconnect coupling technology with over 500,000 product variants in stainless steel, brass, aluminium, steel, and plastic. Since 1951, the company has manufactured mono and multi-couplings and automated docking systems for pneumatics, hydraulics, gases, fluids, optical signals, and power current. Its robot tool-changing systems are automated docking solutions enabling fast, high-precision end-of-arm tooling changes on industrial robots.
The company serves automotive, aerospace, chemical, pharmaceutical, medical, and defence industries worldwide.
Primary type & automation activities this supplier delivers:
Automated docking systems for industrial robots enabling fast, high-precision tool changes; supports pneumatics, hydraulics, electrical, and data media in a single coupling.
Simultaneous multi-line connection systems for pneumatics, hydraulics, gases, optical signals, and power current in more than 500,000 variants for industrial and robotic applications.
Contact WALTHER-PRAEZISION Carl Kurt Walther GmbH & Co. KG
WEBSITE
https://walther-praezision.dePHONE
+49 (0) 2129 567-0HEADQUARTERS
Germany
Company Facts
Founded
1931
Primary Role
Manufacturer
Company Size
employees 100-500
Primary Region
Europe
Annual Sales
-
Funding Stage
-
Funding Total
-
Keywords
Nvidia has introduced the Jetson Orin Nano 2, a new robotics computer designed for entry-level edge AI applications. This innovative computer aims to empower millions of developers globally to create robots, drones for delivery and inspection, and vision AI systems tailored for advanced physical AI tasks. The significance of the Jetson Orin Nano 2 lies in its enhanced performance and energy efficiency. It offers double the inference performance of its predecessor while consuming 40% less power, making it an attractive option for developers seeking compact and efficient robotics solutions. With over 3 million developers utilizing the Nvidia robotics stack, early adopters like Cognex, Doosan Bobcat, and Matic are already exploring its capabilities. Looking ahead, Nvidia's Jetson Orin Nano 2 is set to redefine entry-level edge AI by providing frontier-class generative AI performance to a broader audience. As AI models become more efficient, the potential for autonomous edge devices to perform real-time tasks will expand significantly. No further timeline was disclosed at the time of publication.
RoboticsAndAutomationNews.com 12 hours ago Computing News Robotics ai computing Autonomous robots dronesResearchers at Delft University of Technology have developed a whisker-based tactile framework that allows tiny drones to navigate complex environments without relying on visual input. Inspired by the natural whiskers of rodents, this technology equips drones with artificial whiskers that provide real-time feedback as they interact with their surroundings. This innovation addresses a significant challenge in aerial robotics, particularly for micro-drones weighing under 100 grams, which cannot support heavy LiDAR systems. The whisker system enables these drones to operate effectively in low-visibility conditions, such as dust or darkness, where traditional cameras fail. Moving forward, the focus will be on refining this tactile navigation system and exploring its applications in various environments. No further timeline was disclosed at the time of publication.
InterestingEngineering.com 12 hours ago AI and RoboticsResearchers at Delft University of Technology have created a lightweight tactile sensor inspired by animal whiskers, enabling tiny autonomous drones to navigate in low-visibility environments. This innovation allows drones to explore areas filled with darkness, dust, or smoke without relying on heavy sensors. The ability for drones to navigate through challenging environments is significant for various applications, including search and rescue operations, environmental monitoring, and industrial inspections. By mimicking the sensory capabilities of rats and mice, these drones can effectively maneuver in tight spaces and complex terrains. Future developments in this technology could enhance the operational capabilities of drones in various sectors. As research progresses, it will be important to monitor advancements in sensor technology and potential applications in real-world scenarios. No further timeline was disclosed at the time of publication.
TechXplore:Robotics 12 hours ago RoboticsThe CT-Unite team has won the ACM MM 2026 championship, marking their second consecutive victory in international AI competitions. This time, they achieved success with a brain-inspired, cross-modal cognitive neural network designed for robotics, which compresses a 100 TFLOPS model to operate at 38.8 TFLOPS using distributed computing technology. This achievement is significant as it addresses the critical challenge of enabling embodied intelligent robots to transition from perception to cognition. The EgoLink challenge, part of the ACM MM conference, focuses on understanding social relationships and event logic from a first-person perspective, showcasing the highest level of AI capabilities in video social interaction and environmental reasoning. Looking ahead, the integration of the CT-2001A IDPU architecture and the CT-HS01 4D spectral sensor represents a major advancement in robotic cognition. The team's approach aligns multi-source information at the feature and neuron levels, allowing robots to infer social dynamics and emotional causality, thus achieving human-like cognitive abilities. No further timeline was disclosed at the time of publication.
leaderobot.com Sep 18, 2026 Cognitive Robotics Neural Networks Multimodal Integration AI TechnologyTreble Technologies has secured $18 million in Series A-2 funding, led by Paladin Capital Group, to enhance auditory capabilities in robots. Founded in 2020 in Reykjavik, Iceland, Treble focuses on transforming sound propagation into simulative data, addressing limitations faced by AI models in complex acoustic environments. The significance of Treble's technology lies in its ability to model sound acoustics based on physical principles, allowing developers to evaluate product performance before creating physical prototypes. This approach differs from traditional audio processing methods, which primarily focus on signal-level enhancements. Treble's simulations can replicate real-world acoustic conditions, providing valuable insights for companies like Amazon and Logitech, who are already testing audio products on Treble's platform. Looking ahead, Treble aims to expand its presence in the U.S. market while increasing investments in physical AI. As sound becomes a critical interface for intelligent machines, the company’s acoustic simulation capabilities could bridge the gap in robotic perception, enabling robots to interpret auditory information alongside visual data. No further timeline was disclosed at the time of publication.
leaderobot.com Sep 18, 2026 Acoustic Modeling Robotics AI Sound SimulationAetina Corporation has announced the general availability of its DeviceEdge AIE-KT78 and AIE-KT68 edge AI systems. These systems support local multimodal generative AI, LLM, VLM, and VLA model execution, enabling seamless integration with high-resolution sensors, motors, joints, and actuators through high-bandwidth interfaces and EtherCAT control. The introduction of these systems is significant as they are powered by NVIDIA Jetson Thor and utilize the NVIDIA Blackwell architecture, providing high-performance AI compute and deterministic industrial control. This makes them ideal for Collaborative Robots (Cobots), humanoid robots, and next-generation autonomous machines, enhancing their ability to perceive, reason, decide, and act in real-world environments. Looking ahead, the focus will be on how developers leverage the capabilities of the AIE-KT78 and AIE-KT68 systems to create more sophisticated robotic applications. No further timeline was disclosed at the time of publication.
RoboticsTomorrow.com Sep 17, 2026Arm Holdings PLC has introduced Arm Total Design for Physical AI, a program that unites over 80 companies involved in the physical AI technology stack. This initiative aims to foster collaboration among participants in the physical AI space, addressing challenges in perception, AI, real-time control, and safety. The significance of this program lies in its potential to streamline the fragmented robotics industry, which often sees companies struggling to collaborate effectively. Dermot O’Driscoll, vice president at Arm, emphasized the need for a cohesive ecosystem where technology and ideas can be shared, enhancing the development of interoperable systems. Looking ahead, Arm's Robotics Capability Framework will categorize robotic systems into six levels of sophistication, from basic reactive robots to advanced systems that learn and self-optimize. Arm is seeking industry feedback to refine these levels, indicating a commitment to evolving the understanding and capabilities of robotics in the market.
RoboticsBusinessReview.com Sep 17, 2026 Artificial Intelligence Artificial Intelligence / Cognition Automotive Design / Development Development Tools / SDKs / Libraries Markets / IndustriesThe Navy is advancing its find, fix, and finish kill chain through the implementation of remote mine hunting technologies. This innovative approach leverages autonomy, artificial intelligence, and advanced sonar systems to effectively locate and neutralize underwater mines, significantly improving operational efficiency. The integration of these technologies is crucial for enhancing maritime safety and operational readiness. By utilizing remote mine hunting, the Navy can clear waterways more quickly and with reduced risk to personnel, addressing the growing need for effective mine countermeasures in complex environments. Looking ahead, the continued development and deployment of remote mine hunting capabilities will be essential for maintaining naval superiority. No further timeline was disclosed at the time of publication.
BreakingDefense Sep 17, 2026 Naval Warfare Sponsored Post Navy networks Presented by Thales SASResearchers from York University have introduced the Convergent Binocular Stereo (CBS) algorithm to improve depth perception in humanoid robots. This innovative approach utilizes the movement of the robot's eyes, allowing them to converge on a target while calculating depth based on camera orientation and disparities in the images. This method significantly outperforms traditional depth learning techniques, especially in complex visual scenarios. The advancement is crucial as humanoid robots increasingly rely on sophisticated vision systems to navigate and interact with their environments. By integrating eye movement into depth calculations, the CBS algorithm addresses a long-standing challenge in robotic vision, enhancing the robots' ability to perceive three-dimensional spaces accurately. Looking ahead, the implementation of the CBS algorithm could lead to more advanced humanoid robots capable of better depth perception and spatial awareness. No further timeline was disclosed at the time of publication.
leaderobot.com Sep 17, 2026 Humanoid Robots Vision Systems Depth Perception Robotics ResearchKAIST's Urban Robotics Lab secured first and second place in two prestigious international robot navigation challenges. The team developed an AI system that enables robots to self-verify their decisions, ensuring they reach the correct destination. This innovative self-checking technology was instrumental in their success at the competitions held in Malmo, Sweden, and Sydney. The significance of this achievement lies in the advancement of embodied artificial intelligence, which allows robots to better understand human instructions and navigate complex environments. By addressing common navigation errors, such as misidentifying destinations, KAIST's technology enhances the reliability of robotic systems in real-world applications. The competitions were part of the European Conference on Computer Vision 2026 and Robotics: Science and Systems 2026, highlighting the importance of AI in robotics. Looking ahead, the focus will be on further refining the CoRe-VLN system, which utilizes AI to analyze visual and textual data for improved navigation accuracy. No further timeline was disclosed at the time of publication.
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