Skip to content

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Design and Implementation of an AI-Powered Multi-Sensor Hexapod Robot for Earthquake Search and Rescue

Overview

This project presents the design and implementation of an AI-powered multi-sensor hexapod robot for earthquake search and rescue applications.

The robot is designed to operate in complex and hazardous environments where direct human access may be dangerous. The system integrates computer vision, audio intelligence, vibration monitoring, wireless communication, FPV monitoring, and autonomous navigation through a multi-sensor fusion architecture.

By combining artificial intelligence, embedded systems, wireless communication, and a six-legged locomotion platform, the robot assists rescue teams in locating potential victims, monitoring disaster areas, and improving situational awareness during emergency operations.

This project was developed as a Graduation Thesis at Ho Chi Minh City University of Technology (HCMUT), Vietnam National University Ho Chi Minh City.


Project Objectives

  • Develop a hexapod robot capable of traversing rough terrain.
  • Detect humans and animals using AI-based image recognition.
  • Detect human and animal sounds using AI-based audio classification.
  • Monitor post-earthquake vibrations and aftershocks.
  • Support both manual and autonomous operation modes.
  • Deploy rescue markers at suspected victim locations.
  • Transmit real-time information to a remote control station.
  • Provide live FPV video streaming and system monitoring dashboard.

System Architecture

Robot Platform

  • Hexapod structure with 18 DOF.
  • Tripod gait locomotion.
  • Manual and autonomous navigation modes.
  • Obstacle avoidance using distance sensors.

AI Vision System

  • Raspberry Pi 5.
  • Raspberry Pi Camera V2.
  • YOLOv8 object detection.
  • Detection classes: Person, Dog and Cat.

AI Audio System

  • INMP441 I2S Microphone.
  • CNN-based audio classification.
  • Detection classes: Human voice, Dog bark and Environmental noise.

Vibration Monitoring

  • MPU6050 Accelerometer.
  • PGA (Peak Ground Acceleration) calculation.
  • MMI (Modified Mercalli Intensity) estimation.
  • Aftershock monitoring.

Wireless Communication

  • LoRa SX1278.
  • nRF24L01.
  • Real-time sensor transmission.
  • Remote command and control.

FPV Monitoring

  • FPV Camera.
  • 5.8 GHz Video Transmission.
  • Real-time video feedback to operator.

Rescue Marker System

  • Marker deployment mechanism.
  • Wireless status reporting.
  • Rescue state monitoring.

Web Dashboard

  • Real-time sensor monitoring.
  • Robot status visualization.
  • Marker tracking.
  • Alert notifications.

Ground Control Station

  • Real-time dashboard.
  • Sensor monitoring.
  • Marker tracking.
  • Audio alerts.
  • Robot telemetry display.

Technologies Used

Main Hardware

  • Raspberry Pi 5 (Main Robot Controller).
  • Raspberry Pi 3 (Ground Control Station).
  • Raspberry Pi Camera V2.
  • INMP441 Microphone.
  • MPU6050.
  • LoRa SX1278.
  • nRF24L01.
  • PCA9685 Servo Driver.
  • MG946R Servo Motors.
  • FPV Camera System.

Software

  • Python.
  • YOLOv8.
  • TensorFlow / Keras.
  • OpenCV.
  • Flask.
  • HTML / CSS / JavaScript.

PCB Design

  • Altium Designer.

Mechanical Design

  • CAD Modeling.
  • 3D Printed Components.

Demo Videos

YouTube Playlist: https://www.youtube.com/playlist?list=PLQ2nYnHPs12wPHYRxYziXRSKi9JFzzbWc

The playlist includes:

  • Hexapod locomotion testing.
  • Manual control mode.
  • Autonomous navigation mode.
  • Obstacle avoidance.
  • Human detection.
  • Audio detection.
  • Marker deployment.
  • Dashboard monitoring.
  • System integration tests.

Results

The developed system successfully demonstrates:

  • Stable hexapod locomotion.
  • Real-time AI-based human and animal detection.
  • AI-based audio recognition.
  • Obstacle avoidance capability.
  • Aftershock monitoring.
  • Wireless communication between robot and control station.
  • Rescue marker deployment.
  • FPV video transmission.
  • Real-time dashboard monitoring.

The integration of AI, embedded systems, wireless communication and multi-sensor fusion improves situational awareness and supports search-and-rescue operations in hazardous environments.


Authors

Ngô Diễm Quỳnh – 2212887

Nguyễn Trọng Tuấn – 2213794

Department of Electronics and Telecommunications Engineering

Ho Chi Minh City University of Technology (HCMUT)

Vietnam National University Ho Chi Minh City

Supervisor: TS. Nguyễn Lý Thiên Trường


License

This repository is published for academic and portfolio purposes. Please contact the authors before using the materials for commercial applications.

About

Design and Implementation of an AI-Powered Multi-Sensor Hexapod Robot for Earthquake Search and Rescue

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages