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OUR TECHNOLOGY

Our autonomous space robotics platform integrates modular hardware design with advanced artificial intelligence to enable in-orbit satellite assembly and extraterrestrial infrastructure construction. The core technologies include:

1. Modular Robotic Architecture

Each robot is designed as a modular unit capable of:

  • Multi-functional manipulation using articulated robotic arms with multi-axis degrees of freedom.

  • Docking and assembly using magnetic or mechanical couplers.

  • Mobility in space via micro-thrusters for position control and orientation in zero gravity.

These modules can combine dynamically to form larger construction units or work independently in swarm mode.


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2. Swarm Intelligence and Multi-Agent Collaboration

We use a decentralized swarm robotics approach, allowing multiple robotic units to:

  • Coordinate tasks in real-time.

  • Distribute workloads based on location, energy level, and tool availability.

  • Adapt to failures by reassigning tasks autonomously.

Our coordination algorithm is inspired by ant colony optimization and distributed task scheduling principles.

3. AI-Based Autonomous Decision-Making

Each robot is equipped with:

  • Computer Vision Systems: Using stereo cameras, LIDAR, and IR sensors to perceive the environment, detect parts, and avoid obstacles.

  • Reinforcement Learning Algorithms: For learning optimal assembly sequences and spatial movements over time.

  • Neural Network-Based Controllers: For high-level decision making, error correction, and adaptive planning.

4. Self-Repair and Maintenance Mechanisms

Robots are capable of:

  • Diagnosing internal faults using sensor feedback and AI diagnostics.

  • Performing self-repair using spare parts carried in modular storage or sourced from redundant units.

  • Replacing damaged peers in a swarm, ensuring mission continuity.

5. Simulation and Testing Framework

We developed a custom simulation environment using Unity and Blender to:

  • Test construction scenarios under varying gravity and lighting conditions.

  • Train AI models with synthetic data before real-world deployment.

  • Visualize collaborative tasks in a 3D environment for debugging and optimization.

REPRESENTATION

Contact Us :

utkarsh.jain12a@gmail.com

8989177966

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