General Robotics develops a platform called GRID that provides modular, deploy-ready AI skills for various robot morphologies. This platform enables robots to sense, reason, and act by composing these skills through an agentic architecture. The service facilitates rapid prototyping and scalable deployment of robot intelligence across cloud, on-premise, or edge environments.
Funding
$74.9K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
HSFounders
Product
Problem
Developing robotic systems for real-world applications is challenging because robots must adapt to different forms, be easily programmable, and meet rigorous safety standards. Existing solutions often rely on monolithic models that are data-inefficient, difficult to debug, and lack the modularity needed for diverse scenarios.
Solution
General Robotics is developing general-purpose intelligence for robots by focusing on modular AI skills that enable robots to perceive, plan, and act in the physical world. Their approach centers on composing individual AI skills, such as language comprehension, perception, planning, and action, to create more complex behaviors. The GRID platform provides a development environment with access to a library of AI skills, simulation environments, and robot morphologies, allowing developers to train, test, and deploy AI skills across various robot types. By emphasizing modularity and interpretability, General Robotics aims to create robotic systems that are data-efficient, safe, and adaptable to a wide range of real-world applications.
Target Audience
The primary audience includes robotics developers, researchers, and enterprises seeking to build and deploy adaptable AI solutions for robots across diverse real-world scenarios.
Features
- Modular AI skills for perception, planning, and action, enabling composition of complex behaviors
- GRID development platform with a library of AI skills accessible through a unified API layer
- Support for multiple robots and high-fidelity simulations for zero-shot deployment
- Web-based interface for composing and testing AI skills without hardware dependencies
- Synthetic data collection on the cloud for various form factors and use cases
- Integrative testing through simulation feedback and deployment processes
- Tools for bridging the sim-to-real gap using data augmentation
- Support for integration with custom robots, use cases, and tech stacks
- Options for deploying AI skills on cloud, edge, or both, across different robot types (aerial, wheeled, manipulation, quadruped, humanoid)