Phase 1: Asimov Genesis

Objective: Lay the foundation for an intuitive robot design and training tool.

• Core Features:

  • Language-to-Model Framework: Implement NLP models that translate user inputs into robotic design specifications and training goals.

  • Basic Training Scenarios: Predefined templates for quadrupeds, humanoids, drones, and rovers in simplified virtual environments.

  • Prototype Feedback Loop: Develop a feedback mechanism to refine designs based on user preferences and simulated performance metrics.

• Tech Stack:

  • AI Models: Leveraging transformer-based architectures for natural language understanding.

  • Simulation Platform: Enhanced physics-based environments using custom-built layers on simulation tools like NVIDIA Omniverse.

  • Backend: Modular, containerized microservices for scalability, deployed via Kubernetes on AWS/GCP.