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Autonomous Rescue Drone

Project Description:

The project develops an autonomous drone utilizing Light Detection and Ranging (LIDAR) and Inertial Measurement Unit (IMU) sensors to navigate a complex maze, while a camera is used to locate a hidden target or prize at the very end. This system simulates real-life scenarios encountered during disaster recovery operations, such as searching burning or collapsed buildings for trapped individuals or pets. LIDAR technology provides precise 3D mapping for obstacle detection, while IMU sensors maintain accurate drone stability and orientation. Additionally, limited camera use preserves battery power in the drone, only being used to detect objects and not for navigation purposes. This advanced sensor integration enhances autonomous navigation capabilities, making the drone suitable for efficient, life-saving search and rescue missions in hazardous environments.

Project Photo:

A 3D-rendered maze with tall, white walls arranged on a checkered floor. An autonomous drone hovers near the maze entrance, preparing to navigate through tight passages. The setup simulates disaster recovery scenarios, testing drone capabilities in locating targets or individuals trapped within confined environments using LIDAR and IMU sensors.

Autonomous drone navigating a complex maze using LIDAR and IMU sensors, simulating search and rescue operations in hazardous environments.

Student Team Members

  • Pranhav Sundararajan
  • Sungwoo Kim
  • Wilson Martinez

Course Faculty

  • Andreas Andreou
  • Daniel Mendat

Project Mentors, Sponsors, and Partners

  • JHU ECE