The Lidar Society

We are pleased to announce the signing of a cooperation framework with SAIC VOLKSWAGEN on a new automotive lidar program! Read more about our partnership in the link below 👇

🚀 Exciting Career Transition Ahead! 🚀 After an incredible year at Aeva, I’m seeking my next opportunity in technical sales. My time working with FMCW LiDAR has sharpened my understanding of cutting-edge sensing technologies, complementing my previous 4 years at Velodyne Lidar/Ouster where I specialized in Time of Flight (ToF) LiDAR. With extensive experience across automotive, defense, ITS, farming, robotics, drones, and security sectors, I’ve built a deep technical knowledge and a robust network of industry contacts. I’m passionate about helping companies tackle challenges in perception and sensing and driving innovative solutions. Currently, I’m looking for a technical sales role based in Detroit, where I can leverage my expertise to deliver value in LiDAR applications and beyond. I’d appreciate your support in spreading the word, and if we’ve worked together, a kind recommendation would mean a lot! Thank you all for your ongoing support! 🙏 #Lidar #ADAS #Autonomous #Robotics #Sensors #Sales #Aeva #Ouster #Velodyne

LiDAR vs. Vision-Only: The Dangerous Gamble We’re All Ignoring (Brace yourself, because this might be the most controversial thing you’ll read all day) Using Vision-Only for autonomous driving isn’t just risky—it’s irresponsible. Yes, I said it. In a world where a split-second decision can mean life or death, relying on cameras alone is like driving blindfolded and hoping for the best. LiDAR skeptics will tell you: • Vision mimics human perception. • It’s cheaper. • It’s more scalable. Sure, those are compelling arguments. But let’s get real here—when was the last time your human eyes flawlessly detected obstacles in a blinding snowstorm or pitch darkness? Here’s the hard truth: 1. Vision-Only: Weaknesses: • Struggles in adverse weather. • Poor depth perception. • Requires advanced AI to interpret visual data. Strengths: • Lower cost, • Continuous improvement via updates. 2. LiDAR-Based: Strengths: • Precise 3D mapping. • Reliable in low-light and poor weather. • Easier regulatory approval. Weaknesses: • Higher costs, • Hardware complexity. Now, let’s talk regulatory approval and public trust. Which approach is more likely to be trusted when lives are on the line? It’s not about what’s trendy or cost-effective. It’s about reliability in the most unforgiving conditions. But I’m not here to tell you what to think. What do you believe is the future of autonomous driving? Is Vision-Only the scalable solution the world needs, or are we playing with fire by ignoring the precision and safety of LiDAR? Let’s hear your thoughts—where should the line be drawn? P.S. If you found this perspective challenging, feel free to share it with your network. Because the future of driving is one debate we can’t afford to get wrong. ♻️

Over the past few years, I’ve seen countless OEMs and Tier-1 suppliers struggle to build their own autonomous driving software. Why go through the hassle? At Imagry | Autonomous Driving, we’ve already developed a field-proven, vision-based solution that’s easy to integrate and ready to help you compete with Tesla’s FSD—without the high costs and further delays. Next stop: full autonomy. Are you coming?

Thats tech content done right ✌🏼

Time to start a new lidar business Chen Zach ? ✌🏼🫶

 🚦 Why Your Smart Traffic Sensor Needs the Integrator-AI 🚦 For safer and more efficient roadways, smart traffic sensors alone aren’t enough. To unlock their full potential, you need Integrator-AI—a software platform that enhances traffic control and analysis across the board. Here’s why Integrator-AI is essential for your traffic system: 🚥 1. Data Fusion: Smarter Insights   - Integrator-AI integrates data from all traffic sensors—LiDAR, radar, cameras, and more—into a unified ecosystem. This data fusion provides real-time, high-definition insights, optimizing traffic flow, reducing congestion, and improving safety. 🚥 2. Precision Tracking: True Movement   - Go beyond basic detection. Integrator-AI tracks individual vehicles and pedestrians, understanding exactly where they enter, exit, and interact at intersections. This precision drives smarter traffic decisions and boosts road safety. 🚥 3. Real-Time Analytics and Adaptive Control   - Don’t just gather data—act on it. Integrator-AI processes real-time data, automatically adjusting signals, lane usage, and messaging to respond to changing traffic conditions instantly. This results in optimized traffic flow and reduced delays. 🚥 4. Scalability: Future-Proofing   - As transportation systems evolve with autonomous vehicles and connected infrastructure, Integrator-AI scales seamlessly, integrating new technologies while staying compatible with existing systems. It’s the platform that grows with your needs. 🚥 5. Seamless Communication Across Systems   - No more device silos. Integrator-AI enables seamless communication between traffic sensors, controllers, and signs—ensuring your entire network works together smoothly, maximizing the impact of your smart sensor investments.  🚘 Maximize the Power of Your Sensors with Integrator-AI 💡 Integrator-AI transforms your traffic management by combining data fusion, precision tracking, real-time analytics, and scalability. If you're focused on improving traffic flow, enhancing safety, or future-proofing your infrastructure, Integrator-AI is the solution. Don’t let your smart sensors operate below their potential—elevate your traffic system with Integrator-AI. #TrafficManagement #SmartCities #Transportation #TrafficEngineering #ITS #DataFusion #RealTimeAnalytics #FutureProofing #SafetyInnovation #ConnectedVehicles #Infrastructure #SmartSensor #Video #Lidar #Radar #USDOT #FHWA #TSMO #IntegratorAI #BlueBand #Parsons #ATKINS #AECOM #ITS #Everyone #Anyone

We recently introduced ZERO minimum range through a simple firmware update! We now offer three minimum range configuration options: 50 cm, 30 cm, and 0 cm. With a configuration of 0 cm, you will receive points for objects, all the way up to the window of the sensor. Learn more about zero minimum range and other performance improvements for our REV7 digital lidar sensors here: https://lnkd.in/ggvrzDKC

Which One Grabs Your Attention? Earlier this month, Ouster dropped a raw video showing off their latest LiDAR sensor in action—impressive tech, but the presentation? A bit plain. So, I decided to give it a makeover. In my version, I added context, broke down the key moments, and used some sharp editing to highlight just how groundbreaking this tech really is. Now, I want to hear from you: Which one do you prefer? • Ouster’s original video: Straightforward, but leaves a lot unsaid. • My explainer edit: Clear, engaging, and full of insights. Drop a comment below with your choice and let’s see which approach wins the day!

LiDAR just got a lot closer—down to the last centimeter. Ouster just set a new standard in LiDAR technology. In a recent test, they mounted their sensor on a vehicle and approached a wall. The result? Incredibly accurate readings from as far as half a meter to just a single centimeter away—without the noise or clipping that often plagues other systems. This is a major breakthrough. Most LiDARs leave you guessing within 1-2 meters of the vehicle. Ouster’s tech eliminates that dead zone entirely. Imagine the safety implications: detecting objects at a distance and right up to the vehicle, with absolute precision. Ouster has just redefined what’s possible in LiDAR. What’s your take on this leap in LiDAR tech? Share your thoughts below.