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Our Technology

Building the world's first self-replicating humanoid robots

We're developing humanoid robots that can build copies of themselves using modular hardware designs and AI planning systems. Our approach focuses on creating robots that can manipulate standard tools, process raw materials, and execute complex assembly sequences autonomously.

Technical Challenges

Self-replicating robots require solving interconnected problems across robotics, AI, and manufacturing:

Dexterous Manipulation

Robots must handle tools and components with precision comparable to human hands, including screwdrivers, 3D printers, and electronic assembly equipment.

Materials Processing

Converting raw materials (metals, polymers, electronics) into functional robot components using available manufacturing tools.

Assembly Planning

AI systems that can decompose complex assembly tasks into hundreds of precise operations while adapting to real-world variations.

Self-Manufacturable Design

Robot architectures specifically designed to be buildable using the robot's own capabilities and available tools.

Our Technical Approach

Hardware Systems

Modular Architecture

Standardized mechanical and electrical interfaces that simplify assembly and enable component reuse across robot generations.

Multi-Modal End Effectors

Hands with force/torque sensing, computer vision, and tool-changing capabilities for handling diverse manufacturing tasks.

Integrated Manufacturing Tools

Built-in 3D printing, basic machining, and electronics assembly capabilities that enable component fabrication.

Quality Control Systems

Sensors and testing protocols to verify component functionality and assembly quality during the replication process.

AI & Software

Task Planning Networks

Neural networks trained to decompose assembly tasks into executable robot actions while handling tool constraints and material properties.

Computer Vision Pipeline

Real-time object detection, pose estimation, and quality assessment for components and assembly progress.

Adaptive Control

Control systems that adjust to variations in materials, tools, and environmental conditions during manufacturing.

Simulation Environment

Physics-based virtual testing where we validate designs and train AI systems before physical implementation.

Development Timeline

Phase 1: Physical Prototypes (2025-2026)

Build first physical humanoid prototypes and validate simulation models with real hardware testing.

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Phase 2: Component Manufacturing (2026-2027)

Demonstrate robots autonomously fabricating individual components like brackets, gears, and simple circuit boards.

Phase 3: Subsystem Assembly (2027-2028)

Robots building complete functional modules like arms, sensors, and control systems for other robots.

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Phase 4: Full Replication (2028-2030)

First complete demonstration of a robot building a functional copy of itself from raw materials.

Phase 5: Optimization & Deployment (2030+)

Multi-robot teams working together to improve replication speed, quality, and adapt to different environments.

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Current Status

We've validated our core concepts in simulation and are now building physical prototypes. We're seeking partners and investors to accelerate development.