Robots make mistakes. ⛔️ But only the most intelligent systems can make a swift comeback. Modern machine learning algorithms and extensive multimodal datasets are changing the game of classical robotics. Robots with Covariant Brain, Covariant's universal AI platform, can learn from their mistakes and become better. More importantly, these robots can learn from the whole robot fleet. The fleet learning method ensures that knowledge and experiences are shared throughout our entire robot network, allowing real-time improvements. This AI Brain gives robots more human-like reasoning capabilities -- this is what enables the robots to detect and mitigate errors before they happen. As well as recover quickly and determine a solution when presented with an unexpected situation. 🧠 Robots with recovery capabilities are a great tool because no human intervention is required. This ensures increased throughput and reliability of the entire system! Fantastic job Peter Chen & team! 🦾 Also, great to see reliable and proven robot arms from ABB Robotics! ~~~ ♻️ Repost to help 1 robot find a new workplace. 📬 Pssst, when you are done with this video - join +12,347 robotics & AI passionates in my newsletter: https://lnkd.in/dzVGBKSc
Impressive what’s possible, Lukas
#ABBRobotics 👉everything is possible 🤝👏
Robots learning from each other and adapting in real-time is incredible!
People makes more mistakes 😎
Robots that improve themselves. Great stuff Lukas M. Ziegler
Very interesting. 😀
Lukas M. Ziegler - mistakes are inevitable, but they can also be valuable learning experiences that contribute to personal and professional development. And it seems also for robots!
Lukas M. Ziegler Sehr spannend :)
These robots are getting smarter and smarter! Great solution by Covariant.
Proprietário Fundador | NANNOS TECNOLOGIAS AVANÇADAS (Produtos Nanotecnologicos Infrabras)
2moThis robotics for this job of transferring different products of different sizes and weights is not efficient. Misleading mechanism.