The State of Robotics Development Today
Imagine you're an expert in a specialized field, such as energy, and you recognize a massive opportunity to automate repetitive yet complex inspection and maintenance tasks. The efficiency gains and ROI are undeniable. Robots exist that could execute these tasks at scale, enhancing safety and preserving human ingenuity.
What’s the next step?
Most organizations form a team of 5-7 robotics engineers—scarce and highly sought-after—covering simulation, field robotics, AI, and software development. These teams juggle data collection, ML model training, fine-tuning, and distillation, and edge deployment. Additionally, they are responsible for establishing robust back-end architecture, testing and evaluation pipelines for robots and sensors, AI/ML ops toolchains, and outlining solution concepts.
The result? Development is slow, talent is stretched thin, and timelines extend. For many robotic enterprises, it takes two years or more of prototyping and field testing to reach a production-grade solution—consuming immense resources along the way.
This is the challenge robotics development faces today.
Lowering the Barrier to Robotics Development
The promise of robotics to transform human labor and function in our built environments, as they exist, has never been greater. AI will fundamentally redefine robotic functionality—enabling robots to perform multiple tasks, collaborate in teams, learn dynamically, and improve efficiency over time.
Yet, robotic development remains hard, slow, and costly. Most solutions still rely on pre-programmed instructions for single-task robots, built on rigid, legacy architectures. Progress in AI for robotics is further hindered by data scarcity, with companies resorting to capital-intensive methods like large-scale teleoperation or vehicle-mounted camera data collection.
Despite these advances, we believe the future of robotics innovation must be open and accessible—not limited to startups, enterprises, and governments, but also academia, researchers, and even hobbyists. The challenge is bridging the gap between high-end robotic AI infrastructure and individual developers eager to build the next generation of intelligent robots.
The Power of Open GRID + Isaac Sim
That’s why today, we’re excited to announce the integration of NVIDIA Isaac Sim, a reference application built on NVIDIA Omniverse for robot simulation, into Scaled Foundations’ Open GRID platform.
GRID is every robot’s AI team, providing developers with seamless access to robot AI models, cutting-edge simulators, and deployment pipelines across various robotic form factors. With GRID, developers can start building robot AI from day one, eliminating months of tedious setup.
GRID supports a continuously growing library of popular robots and sensors and provides simulation scenarios that span a wide range of business and consumer verticals. Furthermore, GRID easily integrates with autonomy stacks via a rich set of APIs.
With Open GRID, we’re bringing together the world’s most advanced robotic AI stack with Isaac Sim via a simple, browser-based development environment—at no cost to individual developers.
No need to spend time configuring and integrating different pieces of software. Simply select your desired robot, environment, and choose from a large variety of AI models to instantly launch the Isaac Sim session you’ve designed. Interact with your robots via python code, LLM, or keyboard to perform perception and control, and start building advanced AI skills for robots in minutes.
Try Isaac Sim in Open GRID now: grid.scaledfoundations.ai
We have curated four sample sessions to get you started:
1. Scene Perception with a Humanoid:
https://grid.scaledfoundations.ai/shared/2d88d24b-d7d0-4951-bc12-0c5ad2d984de
2. Safe Exploration with a Quadruped:
https://grid.scaledfoundations.ai/shared/9c3f0509-7d5b-47e9-af3d-a0aeb485fea8
3. Object Detection for a Manipulator:
https://grid.scaledfoundations.ai/shared/9890f58f-1406-4154-b55b-b5536359b508
4. Generate Data using Isaac Sim:
https://grid.scaledfoundations.ai/shared/14a128b5-f4a1-4c79-bd79-e05e601c8f27
The integration of Open GRID and Isaac Sim lowers technical debt associated with core and advanced robotic development tasks, such as robot simulation, synthetic data generation and augmentation, AI model evaluation, and code generation.
With Open GRID Copilot, developers can even issue natural language commands to generate complex robotic behaviors instantly—further lowering the barrier to entry. Generate code instantly, get to field testing and deployment quickly.
What’s next?
Today, Open GRID is launching with 11 robots for immediate use with Isaac Sim, spanning quadrupeds, humanoids, manipulation arms, and wheeled bases, along with 5 standard Isaac environments. Nvidia and Scaled Foundations will continue to build out this ecosystem of robots, sensors, and environments available within Open GRID, while also introducing new capabilities such as motion planning and more.
For teams requiring deeper customization, expanded data generation, and integration with proprietary models, GRID Enterprise offers full API access and parallelized simulations at scale.
Join us at GTC on March 17 –
We’re hosting a hands-on lab session at NVIDIA GTC on March 17—a chance to dive deep into GRID and Isaac Sim and develop real robotics solutions.
Register here: https://www.nvidia.com/gtc/session-catalog/?search=DLIT74633#/
We can’t wait to see what you build with Open GRID and Isaac Sim!
