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ISRO ANAV

Overview

ISRO ANAV is an autonomous aerial vehicle designed for precision navigation, mapping, and real-time decision-making in complex environments, including extraterrestrial terrains. The system integrates cutting-edge technologies such as SLAM, Convolutional Neural Networks (CNN), and adaptive landing gear.

Features

  • Autonomous Navigation: Uses sensor fusion, SLAM, and real-time path planning.
  • Landing Spot Detection: AI-driven crater detection and pose estimation for safe landings.
  • Localization & Mapping: LiDAR and stereo vision for detailed environmental awareness.
  • Emergency Response System: Automated failsafe mechanisms for secure landings.
  • High-Precision Hardware: Raspberry Pi 5, Pixhawk flight controller, and IMU for stability and processing.
  • Real-Time Communication: 2.4GHz transmitter and telemetry module for control and monitoring.

System Components

Hardware

  • Aerial Vehicle: Lightweight quadcopter drone (<2kg) with modular architecture.
  • Propulsion: Four 2200KV brushless DC motors, 30A ESCs, and 5200mAh 3S LiPo battery.
  • Navigation Sensors: Optical flow, 3D LiDAR, and IMU for real-time motion tracking.
  • Computation: Raspberry Pi 5 (8GB) for onboard image processing and CNN-based decision-making.
  • Landing Gear: Adaptive design to adjust to sloped surfaces and rough terrain.

Software

  • SLAM (Simultaneous Localization and Mapping): For terrain mapping and real-time localization.
  • CNN-based Image Processing: Hazard detection and terrain recognition.
  • Failsafe Algorithms: Automated return-to-home (RTH) and emergency landing protocols.
  • Sensor Fusion: Kalman filtering for data accuracy and noise reduction.

Installation

  1. Clone the repository: 
    git clone https://github.com/userofmeet/ISRO-ANAV.git
  2. Navigate to the project directory: 
    cd ISRO-ANAV

PDF Documentation

The full project documentation is available in ANAV_Documentation.pdf. To view it, open the file in any PDF viewer.

Contributing

  1. Fork the repository.
  2. Create a new branch: 
    git checkout -b feature-branch
  3. Commit your changes: 
    git commit -m "Added a new feature"
  4. Push to the branch: 
    git push origin feature-branch
  5. Create a pull request.

License

This project is licensed under the MIT License. See LICENSE for details

Contact

For any queries, contact: