Digiflec’s Post

Now That's Not LiDAR... It's been a while so maybe a refresh on the basics of LiDAR is in order. 😃 LiDAR, or Light Detection and Ranging, is a remote sensing technology that uses light pulses to map an environment. While you can find LiDAR in home security systems, bar code scanners, and facial recognition systems, LiDAR may be best known for its role in advancing fully autonomous driving. Unlike its RADAR and SONAR cousins, LiDAR provides high-resolution 3D data, making it an important tool across industries including automotive, geology, and agriculture. LiDAR is made up of three main parts: an emitter to send out the light waves, a receiver to capture the reflected light waves, and a processor to interpret the data. Laser Emission: An emitter sends short pulses of laser light through the air at 186,000 miles per second. Light Detection: When the laser pulses hit an object, a small fraction of the light is reflected back to the receiver. Data Processing: The processor measures the light’s travel time, calculates the distance to the objects, and converts the data into detailed 3D maps and models. In a split second, thousands of pulsating light waves hit an object, bounce back, and provide precise timing data to interpret exactly what is in an environment and what it’s doing. By using multiple laser emitters and pulsing light rapidly (hundreds of thousands of times per second), #LiDAR systems are able to capture measurements from different angles across a wide field of view. The result is 3D maps that provide precise information about location, distance, and movement. Want to learn more? Read the full article here: https://ansys.me/3W51uwF #Optics #Photonics #AnsysZemax #AnsyLumerical #AnsysSpeos

My thoughts on Mobileye giving up on developing FMCW LiDARs ⭐️ I was there at CES last year looking at their awesome LiDAR, and it looked really good. So what happened? Was Elon Musk right about LiDAR? 1️⃣ First, there True Redundancy. True Redundancy is mobileye’s AV system, set to drive using 2 different models: one with vision only, the other using LiDAR/RADAR. If they no longer develop FMCW LiDARs, it doesn’t mean they won’t use third parties, and it’s unlikely they will stop True Redundancy, which means that they will go all in on using Vision + … Imaging RADARs! Which leads us to: 2️⃣ The future system will be a combination of Vision and Imaging RADAR. In that sense, we could imagine that the imaging radar won the « battle of 4D » over the FMCW LiDAR — at least for mobileye. 3️⃣ It’s not that Musk was right about LiDARs, but mobileye did mention their vision going to a new level allowed them to ditch the LiDAR development. In reality, the astonishing progress of Imaging RADARs is what killed the FMCW LiDAR. Imaging RADARs are getting extremely high resolution, and can be a much better solution for autonomous driving. The animation shows their Imaging RADAR in action; and in the comments, I’ll drop my articles and emails on mobileye and imaging RADARs #computervision #radar #lidar #selfdrivingcars #deeplearning #robotics

🚀 New Blog Alert: What is the difference between LiDAR and LiDAR? 🚀   Curious about the nuances of LiDAR technology in logistics and intralogistics? Our latest article dives deep into the applications and distinctions of this cutting-edge tech. Discover how LiDAR: 🔍 Powers autonomous vehicles and creates 3D maps 🔍 Enhances traffic management and warehouse processes 🔍 Differentiates between AMR and LiDAR software solutions   Special kudos to our partner IdentPro - Join the digital intralogistics for pioneering AI-supported warehouse management systems. Their innovative use of LiDAR, combined with Flowcate's DeepHub® middleware, showcases a seamless blend of sensor technology and intelligent control.   Read the full article to learn more about how Flowcate and IdentPro are revolutionizing warehouse operations! 👉 https://lnkd.in/dwqBDWip   #LiDAR #Logistics #Intralogistics #WarehouseManagement #AI #Innovation #IdentPro #DeepHub 

🌟 Debunking Lidar Myths: Lidar Can't Work in the Rain? Think Again! 🌟 When it comes to lidar technology, one persistent myth is that it becomes useless in bad weather, especially rain. But is this really true? Let’s dive in and clear up the confusion. 🧐 The Myth: Lidar Can't Work in Rain ☔ Many believe that lidar systems, which use laser beams to map environments, fail in rainy conditions. The idea is that raindrops scatter the laser beams, leading to inaccurate readings or complete failure. While it's true that weather can pose challenges, modern lidar systems are far more robust than this myth suggests. The Reality: Weather-Resilient Lidar 🌦️ 1. Advanced Signal Processing: Today's lidar systems employ sophisticated algorithms that filter out noise caused by raindrops. They can distinguish between raindrops and actual objects, ensuring accurate readings even during a downpour. 2. Real-World Example: Autonomous Vehicles: Companies like Waymo and Tesla are using lidar in their self-driving cars. These vehicles are tested in all sorts of weather, from heavy rain to fog. The lidar systems in these cars are designed to handle such conditions, allowing the vehicles to navigate safely and accurately. 3. Weather-Resistant Design: Some lidar sensors are designed with features like heated optics to prevent condensation and water droplets from affecting performance. This ensures they remain operational even in adverse weather conditions. 4. Successful Deployments: Lidar is used in various industries that require reliability in all weather. For instance, in coastal areas, lidar is employed for monitoring shorelines and managing erosion, tasks that continue despite the presence of rain or fog. Why It Matters 🌍 Understanding the true capabilities of lidar is crucial as it plays a significant role in various cutting-edge applications, from autonomous driving to environmental monitoring. By debunking myths, we can better appreciate the technology's potential and trust its performance in real-world conditions. Join the Conversation! 🗣️ Have you seen lidar in action during bad weather? Share your experiences and thoughts below! Let's dispel myths and spread knowledge together. 🚀 🔗 #LidarTech #Innovation #MythBusting #AutonomousVehicles #WeatherResistantTech #FutureTech

🚗🌧️ Think lidar fails in rain? Think again! 🌟 Discover the truth about weather-resistant lidar tech. #LidarTech #Innovation #FutureTech Read more below! 👇

SiLC Technologies, Inc has developed an innovative 4D FMCW Lidar system called the Eyeonic Vision Sensor, promising a range of over 3,000 feet for detecting and avoiding obstacles. Unlike traditional #lidar systems, this technology continuously varies the frequency of laser light to enhance object detection and provide richer information, including polarization characteristics. Despite its advanced capabilities, the system is compact enough to fit on a single silicon chip, making it easy to integrate into vehicles. While it requires multiple sensors for a full field of view, it holds potential applications beyond autonomous vehicles, such as drones and metrology. Though initially costly, the technology's adoption is expected to increase as production scales up, with partnerships indicating potential for earlier mass production than previously estimated. Follow Amanda Newman to stay up to date with technology. https://lnkd.in/etX27__g

How Self-Driving Cars Work: A Deep Dive Perception is the first step. Sensors like LiDAR, radar, and cameras scan the environment, gathering data about roads, traffic, pedestrians, and other objects. Mapping involves creating a detailed 3D map of the surrounding area. This map is constantly updated with real-time data from sensors. Localization determines the car's precise location on the map. This is crucial for making accurate decisions. Planning involves deciding where to go and how to get there. The car's navigation system and real-time data help it plan its route. Control is the final step, where the car's actuators (like steering, brakes, and throttle) are commanded to execute the plan. Advanced AI algorithms power these processes, enabling self-driving cars to make complex decisions in real-time. #SelfDrivingCars #AutonomousVehicles #Technology #AI #FutureOfTransportation

How Self-Driving Cars Work: A Deep Dive Perception is the first step. Sensors like LiDAR, radar, and cameras scan the environment, gathering data about roads, traffic, pedestrians, and other objects. Mapping involves creating a detailed 3D map of the surrounding area. This map is constantly updated with real-time data from sensors. Localization determines the car's precise location on the map. This is crucial for making accurate decisions. Planning involves deciding where to go and how to get there. The car's navigation system and real-time data help it plan its route. Control is the final step, where the car's actuators (like steering, brakes, and throttle) are commanded to execute the plan. Advanced AI algorithms power these processes, enabling self-driving cars to make complex decisions in real-time. #SelfDrivingCars #AutonomousVehicles #Technology #AI #FutureOfTransportation

🔲 WILL RADAR SOON REPLACE LiDAR? 4D IMAGING RADAR BASED ON TDA4. 👉 When moving from 3D to 4D RADARs, we got a much better resolution, and less noise. What we can note is that LiDAR and Radar sensors got better, and could work as standalone? The vid compares a 4D Radar with the new 4D Radar/TDA4. ◻ LiDAR: The FMCW makes it better with weather conditions and adds the velocity estimation. ◻ RADAR: The overall better resolution removes lots of noise, and makes it easier to find distances, classify, etc... 👉 Altos V2 is probably, the world's first 4D imaging radar product that's based on the TI's TDA4 processor. It is designed for ADAS and full autonomous driving application. 👉 The TDA4VM provides high performance compute for both traditional and deep learning algorithms at industry leading power/ performance ratios with a high level of system integration to enable scalability and lower costs for advanced automotive platforms supporting multiple sensor modalities in centralized ECUs or stand-alone sensors. 👉 Yellow - Lidar points, serving as ground truth in both cases. 👉 Green - stationary points from Radar 👉 Red - approaching points from Radar 👉 Pink - departing points from Radar 👉 The grid is 20m x 20m 👉 Identical setting for both cases left/right ◻ The test location is Beijing Road in Beijing, China. ◻ Founded in January 2023 by experts of leading tech firms including Apple, Pony.ai and Mozilla, Altos Radar secured investments from venture capitalists - ZhenFund 真格基金, Monad Ventures and Hesai CEO, Yifan Li, ◻ In an outstanding company move, former head of next-generation Imaging Radar technology at Bosch (Germany), Dr. Mingkang Li, has been appointed President at Altos Radar, in 2024. video: Altos Radar/globalnetwork #Altos #AltosV2 #AltosRadar #LiDAR #4DImaging #TexasInstruments #sensor #autonomousdriving #ADAS #Bosch Li Niu Michael Wu Mingkang Li Altos Radar Texas Instruments LightWare LiDAR Bosch Mobility

Robots with Super Vision, LiDAR Sensors can See the Unseen😳 Imagine robots that navigate dark caves, saving lives in disaster zones, or flawlessly zipping around warehouses. Think of them as 3D laser eyes. Robots use LiDAR to map their surroundings, "seeing" in darkness and navigating complex environments. The future of robotics is here, and it has superhuman vision. Follow for more Rinor Restelica #LiDAR #Tech #AI #AR #Productivity