Robotics

MATE ROV

An advanced remotely operated underwater vehicle (ROV) built for the MATE ROV competition. Features computer vision-based object detection, autonomous navigation capabilities, and real-time sensor telemetry for marine research tasks.

PythonOpenCVROSArduinoC++Raspberry PiTensorFlow

Problem Statement

Underwater exploration and research require sophisticated vehicles that can operate in challenging environments. Manual control alone is insufficient for complex tasks requiring precision and real-time data analysis.

Solution

Designed and built an ROV with integrated computer vision for underwater object detection and identification. Implemented semi-autonomous navigation with real-time sensor fusion and telemetry streaming.

Key Features

  • Underwater object detection using custom-trained CV models
  • Real-time video streaming with low latency
  • 6-DOF movement control with PID stabilization
  • Sensor fusion for depth, temperature, and orientation
  • Semi-autonomous task execution
  • Custom control interface with real-time telemetry

Challenges

  • Computer vision in turbid underwater conditions
  • Low-latency video transmission through tethered connection
  • Waterproofing electronics for deep-water operation
  • Real-time PID tuning for stable underwater movement

Results & Metrics

Successfully competed in MATE ROV international competition

Achieved reliable object detection in underwater environments

Real-time telemetry with <100ms latency

Stable operation at competition-required depths

Lessons Learned

  • 💡Embedded systems require rigorous testing under real conditions
  • 💡Hardware-software integration benefits from modular architecture
  • 💡Team collaboration and documentation are critical for complex robotics projects

Case Study Overview

Case Study: MATE ROV Robotics Platform

Custom underwater exploration rover with computer vision, telemetry sensors, and automated control algorithms.

Technologies

PythonOpenCVROSArduinoC++Raspberry PiTensorFlow

Gallery

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