Symbotic’s Post

Robotics Stock's 4D Imaging Radar Can Increase Opportunities, Analyst Says: https://ow.ly/6J1s50R7O6l Arbe Robotics Ltd.'s "4D imaging radar can gain share in the existing multi-billion-dollar automotive radar market and grow in the diversifying non-automotive markets as well," according to a Roth MKM research note. $ARBE #robotics #tech #stocks

How do robots recognize complex parts on conveyor belts? Part recognition by robots on conveyor belts is a fascinating and complex topic. Robots use a variety of special algorithms to identify objects,  and determine their positions and planning their grip position. In the following posts, we will discuss some of them: ☑ AI-based Image processing algorithms such as CNNs, ☑ 3D image processing, ☑ Sensor fusion, ☑ Adaptive algorithms, ☑ Real-time processing, ☑ Intelligent robotic systems. All of these enable robots to precisely detect and handle objects on conveyor belts. These technologies play a critical role in optimizing manufacturing processes, increasing productivity, and improving product quality in a variety of industrial sectors. Which post would you like to read the most? #robots #Imageprocessing #Industrialautomation #AI

Robotic Vision: The Next Evolution in Automation! Exciting advancements are reshaping the landscape of industrial automation, and the future is all about Robotic Vision! Robotic vision refers to the integration of visual perception and interpretation capabilities into robotic systems. It enables robots to "see" and understand their environment through the use of imaging devices, such as cameras and sensors, and to process the visual information to make informed decisions and perform tasks. Key components of robotic vision include: 𝐈𝐦𝐚𝐠𝐢𝐧𝐠 𝐃𝐞𝐯𝐢𝐜𝐞𝐬: Cameras or other optical sensors are employed to capture visual data from the surroundings. These devices serve as the robot's "eyes" and provide the raw visual input for analysis. 𝐈𝐦𝐚𝐠𝐞 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠: The captured images are processed through sophisticated algorithms and computer vision techniques. Image processing involves tasks such as object recognition, pattern detection, and feature extraction, enabling the robot to interpret the visual data. 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐌𝐚𝐤𝐢𝐧𝐠: Based on the processed visual information, the robot makes decisions to perform specific actions or tasks. These decisions can range from simple tasks like object manipulation to complex activities such as navigation through dynamic environments. 𝐅𝐞𝐞𝐝𝐛𝐚𝐜𝐤 𝐋𝐨𝐨𝐩: Robotic vision often involves a feedback loop, where the robot continuously updates its understanding of the environment based on real-time visual data. This allows for adaptability in response to changes or uncertainties in the surroundings. Applications of robotic vision in factory automation and other industries include: 𝐏𝐢𝐜𝐤 𝐚𝐧𝐝 𝐏𝐥𝐚𝐜𝐞 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬: Robots can visually identify and pick up objects from a cluttered environment, placing them in designated locations. 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐚𝐧𝐝 𝐈𝐧𝐬𝐩𝐞𝐜𝐭𝐢𝐨𝐧: Automated visual inspection systems can detect defects or anomalies in products on the production line, ensuring high-quality output. 𝐍𝐚𝐯𝐢𝐠𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐎𝐛𝐬𝐭𝐚𝐜𝐥𝐞 𝐀𝐯𝐨𝐢𝐝𝐚𝐧𝐜𝐞: Vision-enabled robots can navigate through complex environments, avoiding obstacles and adapting to changes in the surroundings. 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐯𝐞 𝐑𝐨𝐛𝐨𝐭𝐢𝐜𝐬: Robotic vision enhances the safety and collaboration between robots and human operators by providing robots with the ability to recognize and respond to human presence. 𝐀𝐬𝐬𝐞𝐦𝐛𝐥𝐲 𝐚𝐧𝐝 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠: Robots equipped with vision systems can perform intricate assembly tasks with precision, even in scenarios where the positions or orientations of components may vary. Robotic vision plays a pivotal role in advancing automation capabilities, offering robots a level of awareness and intelligence that enhances their functionality in diverse applications. #RoboticVision #SmartManufacturing #Automation #machinevision

#snsinstitution #snsdesignthinkers #designthing Robotic arms have revolutionized various industries, including manufacturing, healthcare, and space exploration. These versatile machines are designed to replicate the functionality and dexterity of human arms, enabling precise and repetitive tasks with high efficiency and accuracy.Historical BackgroundThe concept of robotic arms dates back to the mid-20th century. The first industrial robot, Unimate, was installed at a General Motors plant in 1961. Created by George Devol and Joseph Engelberger, Unimate was designed to handle tasks such as welding and material handling, which were hazardous or monotonous for human workers.Technological AdvancementsOver the decades, robotic arms have undergone significant technological advancements:Sensors and Actuators: Modern robotic arms are equipped with advanced sensors and actuators that enhance their precision and adaptability. These components enable robots to perceive their environment and adjust their actions accordingly.Artificial Intelligence: AI and machine learning algorithms have enabled robotic arms to learn from their experiences, improving their performance over time. This is particularly useful in complex tasks such as surgery or delicate assembly processes.End Effectors: The end effector, or the "hand" of the robotic arm, has seen innovations allowing for a variety of interchangeable tools. These tools can perform specific functions like gripping, welding, or painting.

The Importance of Image Processing in Autonomous Robotics and Factories In modern manufacturing, image processing in autonomous robotics is a game-changer, especially in the housing industry. This advanced technology drives significant economic benefits, enhancing precision, efficiency, and productivity. 1. Enhanced Efficiency and Productivity: Real-time technology in robotic controllers processes data in just 2 milliseconds per cycle. Our image processing software operates at 1000 frames per second (fps) in HD format (1920 × 1000), significantly boosting productivity by reducing inspection and quality control time. 2. Cost Reduction: High-speed image processing minimizes manual intervention, leading to substantial labor cost savings. This technology ensures consistent output in the housing industry, reducing waste and rework costs. 3. Improved Quality Control: The ability to measure volumes from 70 x 50 mm to 5100 x 4200 mm with high accuracy ensures every component meets exact specifications. With additional hardware, we can accommodate larger components and more extensive projects. 4. Real-Time Monitoring and Adaptation: Image processing allows for real-time monitoring and defect correction, ensuring only high-quality products proceed to the next stage. This reduces downtime and increases overall factory efficiency. Applications in the Housing Industry: Precision Cutting and Assembly: Autonomous robots perform precise cuts and assemblies, creating high-quality wooden panels and housing components. This accuracy enhances the durability and aesthetic appeal of the final product. Automated Quality Inspection: High-speed image processing ensures thorough and rapid inspection of materials, maintaining high standards of quality and reducing costly returns or repairs. Optimized Material Usage: Accurate measurement and analysis optimize raw material usage, minimizing waste and maximizing yield, crucial in the housing industry. At ARRTSM, we have developed proprietary image-processing software that exceeds industry standards. By integrating our software with autonomous robotics, we provide a robust, all-inclusive solution tailored to the housing industry's specific needs. #Robotics #Manufacturing #Innovation #Sustainability Lisa Terk Vincent Brunori Ken Semler Dean Lewis Atul Bhatt Steven D. Bennett Emilie Lachance #Technology #Efficiency #AI #FutureOfConstruction Gary Shamshoian #Automation #Industry40 Dan Goldin Steve Dubin Jennifer Castenson Trey S. Audree Grubesic Gary Fleisher Paul Richards Jannik Mayer Tobias Adamczyk Thomas Solle #HousingIndustry Gilbert Meier Dennis Michaud #AutonomousRobots #modularconstruction #ConstructionTech #offsiteconstruction #masstimber

ROBOT Robots are mechanical or virtual devices that are designed to perform tasks autonomously or semi-autonomously. They can be found in various fields, including manufacturing, healthcare, space exploration, and more. ●Intelligence Human intelligence is derived from the elaborate and interconnected network of neurons within the human brain. These neurons form electrical connections with one another, but it remains unclear how exactly they collectively cultivate brain activity like thoughts and reasoning. Nevertheless, innovations in the realms of computation and data mining enable the development of artificially intelligent systems that reflect human intellectual capability. ● Sense Perception The technology that empowers robot senses has fostered our ability to communicate electronically for many years. Electronic communication mechanisms, such as microphones and cameras, help transmit sensory data to computers within simulated nervous systems. Sense is useful, if not fundamental to robots’ interaction with live, natural environments. ●Dexterity Dexterity refers to the functionality of limbs, appendages and extremities, as well as the general range of motor skill and physical capability of a body. In robotics, dexterity is maximized where there is a balance between sophisticated hardware and high-level programming that incorporates environmental sensing capability. Many different organizations are achieving significant milestones in robotic dexterity and physical interactivity. ●Power Robots require an energy source, and there are many factors that go into deciding which form of power provides the most freedom and capability for a robotic body. There are many different ways to generate, transmit and store power. Generators, batteries and fuel cells give power that is locally stored but also temporary, while tethering to a power source naturally limits the device’s freedom and range of functions. ●Independence Intelligence, sense, dexterity and power all converge to enable independence, which in turn could theoretically lead to a nearly personified individualization of robotic bodies. From its origin within a work of speculative fiction, the word “robot” has almost universally referred to artificially intelligent machinery with a certain degree of humanity to its design and concept (however distant). Modern robots have already overcome many of the hardest challenges they faced up until just a few years ago. The robot race is running at an amazingly fast pace, and we can only wonder what machines could achieve in the upcoming future. #snsinstitutions #snsdesignthinkers #designthinking

Intelligent Robotic Vision System Destacks Up To 800 Objects Per Hour

Robotics, a multidisciplinary field combining engineering, computer science, and artificial intelligence, is revolutionizing industries worldwide. From manufacturing and healthcare to space exploration and everyday life, robots are becoming increasingly prevalent and sophisticated. At its core, robotics involves designing, building, and programming machines to perform tasks autonomously or semi-autonomously. These tasks range from simple, repetitive actions on assembly lines to complex surgeries in operating rooms. Robotics has the potential to enhance efficiency, productivity, and safety across various sectors. In manufacturing, robots are streamlining production processes, increasing precision, and reducing human error. In healthcare, they assist surgeons with delicate procedures, provide therapy for patients, and aid in rehabilitation. In space exploration, robots are indispensable for exploring environments that are hazardous or inaccessible to humans. However, the rise of robotics also raises ethical and societal questions. Concerns about job displacement, privacy invasion, and the potential misuse of autonomous systems must be addressed as robotics technology advances. Despite these challenges, the future of robotics is promising. Advancements in machine learning, sensor technology, and human-robot interaction are driving innovation and pushing the boundaries of what robots can accomplish. As robotics continues to evolve, it will play an increasingly vital role in shaping the way we live, work, and interact with the world around us. #snsinstitutions #snsdesignthinkers #designthinking

Using #AI to optimise production processes? Key factors include making integration as simple as possible and shortening training phases. The British start-up Cambrian Robotics meets this need with a solution based on 3D vision technology with AI. Cambrian Vision consists of a module for robot arms, a computer unit with intelligent software and a camera module, each equipped with two uEye+ XCP cameras from IDS. Discover now how it works and learn about the benefits this system brings to the market ➡ click below to find out more. #Automation #Robotics #MachienVision #DeepLearning #IDShasVision

Collaboration between humans and robots is rapidly growing, driving innovation and efficiency in various industries.  🤖 By integrating 3D vision systems from Luxolis AI with collaborative robots (cobots), we are automating Electrostatic Discharge (ESD) testing in the electronics manufacturing sector. Implementing advanced 3D vision systems for object detection, collision detection, and swift tool change mechanisms, enabling cobots to perform precise ESD tests without human intervention. This integration enhances precision, safety, and productivity, setting new industry standards. Discover how our innovative approach is transforming ESD testing and making it more efficient than ever. Learn more about it here: https://bit.ly/3KnX8JT #Automation #Cobots #MachineVision #ElectronicsManufacturing #Innovation #LuxolisAI #ESDTesting