⏱️ Every second counts on the line. Picture this: a high-volume assembly line where a robot pauses mid-cycle, slowly scanning for a part. Every second of delay ripples through production. You’ve invested millions in automation, but you still lose time to searching, aligning, and hoping the robot gets it right. What if your robots could skip the guesswork and think for themselves? That’s exactly what we’re building at Inbolt. Our AI-powered 3D vision system mounts directly on the robot’s gripper, instantly locating and orienting parts with human-like understanding. No scanning, no waiting. When Stellantis deployed this at their Detroit Assembly Complex, they saw: ⚡ 30% faster cycle times 🎯 10x better repeatability 💸 ROI in months It’s not just automation anymore. It’s intelligent automation. ❓ If your robots could think, what process would you transform first? #SmartManufacturing #Robotics #IntelligentAutomation #3DVision #ArtificialIntelligence #Industry40 #Inbolt #AI

🎉 Mind-blowing AI news! Researchers have developed a new AI model that can design and build functional robots autonomously! This innovative system uses generative algorithms to create robot designs and then employs automated manufacturing techniques to bring those designs to life. Imagine robots building robots – the future is NOW! What tasks do you think AI-designed robots will excel at? Share your thoughts below! 👇 #AI #Robotics #Automation #GenerativeAI #Innovation #FutureTech #MachineLearning

Hanging objects on moving hooks — a common task in manufacturing (like coating) — is surprisingly hard for robots. Why? ✅ The line is constantly moving, so the robot must adapt in real time. ✅ Hooks are thin, objects are reflective — making 3D vision unreliable. With SigmaKit, this challenge becomes routine: ⚙️ Our real-time inference lets robots track and adapt to moving hooks. 👁️ Our vision system accurately detects both hooks and reflective objects. Out of hundreds of demos, we’ve never missed a hook. Not once. #robotics #automation #manufacturing #AI #computerVision #SigmaKit

KUKA robots have long been the muscle of manufacturing. But in the age of AI, muscle alone isn’t enough. That changes today. We’re excited to announce that Inbolt is now officially integrated with KUKA robots, bringing real-time 3D vision and intelligent tracking to one of the world’s most trusted platforms. 👉  What this means for manufacturers: ✔️ Robots that see in 3D and adapt intelligently ✔️ Higher accuracy in fastening, bin picking & more ✔️ Upgrade stations fast, with results from day one If you’re running KUKA robots, the future of smarter, vision-powered automation starts here. 🔗 Read more: https://lnkd.in/eF8vN66z #AI #Automation #Robotics #3DVision #KUKA #SmartManufacturing #Inbolt

How can a single AI model simultaneously drive a humanoid robot, a dual-arm collaborative arm, and an industrial manipulator? One of the greatest challenges in robotics is generalization. Traditionally, each robot form factor and task required extensive fine-tuning and specialized training. But Gemini Robotics 1.5 is breaking this barrier. We've seen that the same base model can now power three distinct robotic platforms, whether performing complex everyday tasks like laundry sorting or high-precision operations like fruit sorting: Apollo Bi-arm Franka ALOHA This means we no longer need to retrain for every new hardware or subtle task change. This "three machines in one, one model" strategy greatly simplifies deployment and accelerates the introduction of physical agents into the real world. This is not only a technological victory but also a significant promise for the future of large-scale robotics. With a unified intelligent core, the cost and time of deploying robots will be significantly reduced, enabling them to solve complex real-world problems more quickly. What does this model generalization capability mean for automation deployment in your industry? How much development and integration time do you think it can save? Share your insights! #GeminiRobotics #AI #Robot #GeneralArtificialIntelligence #Robotics #Generalization #Engineering #InnovationDeployment

A Vision-Language-Action AI Model applied to Industrial Robotics Instead of building separate models for each robot or task, Sereact has created Cortex, a foundation model that can control different robot types (arms, mobile manipulators, humanoids) and adapt to new environments. What makes Cortex interesting? ✅ One model, many robots: arms, mobile manipulators, humanoids ✅ Day-one value: production-ready in hours, no retraining or per-site code ✅ Edge-case resilience: robust to slips, drops, glare, and clutter ✅ Language as interface: operators can set goals in plain English or German ✅ Fleet learning loop: every deployment makes the model smarter ✅ Already deployed across 100+ industrial systems Cortex is one of the first solution to deploy VLA AI model on industrial robotics applications. Already adopted by big actors of the industry, it opens various possibilities for the future of industrial robotics and automation. 🔗 Check the project page to learn more about Cortex! How do you think VLA and LLM will impact the Industrial Robotics industry? Let's connect and share robotics news 🔽 #Robotics #AI

Robots fail all the time. Do we really need a human operator watching every single one? ARMADA is a multi-robot system that combines autonomous failure detection. With scalable human shared control, making large-scale robot deployment possible without full-time supervision. ✅ FLOAT failure detector: plug-and-play module with 95% accuracy on real tasks ✅ Unified communication hub: one operator can oversee many robots, only stepping in when needed ✅ Scalable loop: online failure data feeds back into post-training, boosting robustness in new scenes Results: over 4× higher success rate and more than 2× fewer interventions compared to standard human-in-the-loop methods. Thanks for sharing, Chuan Wen !! 📍Paper: https://lnkd.in/dU7tbQp3 Project: https://lnkd.in/dpKBZzMu Code: https://lnkd.in/dziXFH9y —- Weekly robotics and AI insights. Subscribe free: scalingdeep.tech

𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗮𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲? 𝗔𝗹𝗺𝗼𝘀𝘁 𝘂𝗻𝘁𝗵𝗶𝗻𝗸𝗮𝗯𝗹𝗲 🤖🧠 Human cognition is amazing — things we do automatically can be tricky for robots. Take item picking, for example: a human can reach into a tightly packed container, nudge boxes aside, and grab the right one. A robot, on the other hand, often stops, unsure of what to do. That’s why AI is essential for robotics in logistics. 🎥 To learn more about this exciting topic, watch the full interview with Timo Landener, Körber Supply Chain:  https://lnkd.in/e9_mWfA5 At Andersen, we help businesses bring AI-powered robotics into their logistics operations, improving efficiency, accuracy, and overall performance. #AIInLogistics #Robotics #Automation #DigitalTransformation #TechTalks

Human intuition is hard to replicate, but AI is getting impressively close. Logistics is a perfect playground for these advancements.

This is spot on💯 Without AI, robotics just hit a wall. It’s wild how something simple for us, like grabbing a box - can totally stump a robot. Smart automation is the future, especially in logistics.