At Standard Bots, we are transforming how robots learn, adapt, and operate through the power of artificial intelligence. By integrating NVIDIA technologies, we are leveraging cutting-edge technologies to push the boundaries of what's possible in AI-driven robotics, accelerating our mission to make human-robot interaction more intuitive and versatile.
Our team is focused on developing AI models for training through demonstration—including utilizing our handheld devices, which are designed in-house. By leveraging NVIDIA accelerated computing, we're not only training our models more efficiently but also deploying them directly inside our robotic arm controllers, enabling smooth and responsive AI operations in real-world scenarios.
Standard Bots is building a platform that integrates data collection, organization, and labeling for training AI models, as well as creating and deploying applications based on these models. NVIDIA’s technologies have been crucial in making this process seamless, helping us efficiently train complex models and get them from the lab to our customers in record time.
For our next-generation RO3 robot, we're pushing the envelope even further. We’re integrating NVIDIA cuMotion, a CUDA-accelerated motion planning library, to provide advanced obstacle avoidance—an essential safety layer for AI-driven robotics. Just as autonomous vehicles need robust safety systems to prevent collisions, our robotic arms also require an intelligent, reliable way to adapt to their environment. cuMotion enables our RO3 robots to be the first of their kind that can rapidly scan, identify, and avoid obstacles. Before cuMotion, such capabilities were a significant challenge due to the limitations in open-source alternatives and the inherent unpredictability of black-box neural networks.
We’re also taking full advantage of NVIDIA Isaac Sim, a reference application for robot simulation built on the NVIDIA Omniverse platform, to build comprehensive test suites for the AI models we create. This allows us to rigorously validate our models in simulated environments, running on AWS cloud instances, before deploying them in the field. Additionally, Isaac Sim plays a crucial role in generating synthetic training data for our foundational AI models, helping us achieve a level of data diversity and volume that would be impractical through real-world collection alone.
Furthermore, we recognize the importance of community-driven innovation. That's why we’re planning to open-source our drivers, enabling our customers to easily integrate their workflows with Omniverse. By doing so, we aim to empower our clients to build upon our work, helping ensure they have the flexibility and tools they need to innovate on their own terms.
By integrating NVIDIA’s technologies across our entire development pipeline—from data generation to AI training, followed by workflow evaluation in simulation, and ultimately progressing to real-time deployment—we’re accelerating our vision of what AI-powered robotics can accomplish. The collaboration has allowed us to simplify and strengthen our workflows, resulting in robotics that are safer, smarter, and easier to train.
We look forward to continuing this journey, pushing forward the boundaries of what our robotic systems can do, and reshaping the future of intelligent automation.
