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Design Synthesis Exercise Spring 2020 - Helicopter Emergency Medical Service (HEMS) Drone

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Helicopter Emergency Medical Services (HEMS) Drone

HEMS LiDaR Demo
(Top Left) Thir-person view of Unreal Engine 4 & AirSim simulation of imported CATIA V5 drone design 3D model & custom made environment,
(Top Right) LiDAR & Iterative Closest Point (ICP) algorithm based autonomous navigation & environment mapping programmed in Python,
(Bottom Left) First-person on-board optical sensor (camera) view of foggy (85%) & rainy (85%) drone operating environment weather condition,
(Bottom Right) First-person on-board optical sensor (camera) view of post image dehazing preprocessing on the left-side recording


Group Number: 5
Period: Spring 2020
University: Delft University of Technology (TU Delft)
Faculty: Aerospace Engineer
Program/Degree: Bachelors of Aerospace Engineer (BSc AE)


Objective:
To design a drone capable of performing a reconnaissance of the law few hundred meters of an approach (by a HEMS helicopter) to ensure the operation safety of the approach and the landing of a HEMS helicopter operating in Instrument Meteorological Conditions (IMC).

Description:
Drones have evolved significantly in the past years in terms of performance, such as max speed, controllability and sensing capabilities. It seems feasible now to imagine a drone which could be deployed by a helicopter to perform the functionality of a forward observer to aid in the approach and landing at new, unknown and unprepared landing sites. Your task is to design such a system within a HEMS operational environment such that minimal visibility landings become viable. Next to the design of the drone, operational procedures should also be defined in a safe and robust manner.

Context:
Instrument Meteorological Conditions (IMC) often frustrate the operation of helicopters, especially with regards to approach and landing operations at remote, unknown areas. Drones have evolved significantly in the past years in terms of performance, such as max speed, controllability and sensing capabilities. It seems feasible now to imagine a drone which could be deployed by a helicopter to perform the functionality of a forward observer to aid in the approach and landing at new, unknown and unprepared landing sites. Sensors, such as radars used in cars, LIDAR and IR sensors can map the surrounding area in 3D within limited range. Thus, a safe approach path and landing site can be explored, and guidance cues can be organised, for the drone making a safe approach and landing operation possible even with limited visibility for the “mother” helicopter. The key issue is that the criticality of performing such an approach first with a relatively cheap and expendable drone is thus reduced dramatically.


Project Current Phase/Status:
In Research & Development

Third-Party Software, Libraries & Tools Usage:

  • AirSim: "Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research" official documentation page.
  • Open3D: "Open3D is an open-source library that supports rapid development of software that deals with 3D data." main page.
  • Unreal Engine: "Unreal Engine is the world’s most open and advanced real-time 3D creation tool. Continuously evolving to serve not only its original purpose as a state-of-the-art game engine, today it gives creators across industries the freedom and control to deliver cutting-edge content, interactive experiences, and immersive virtual worlds." main page.

Team Members:

  • Jilles Andringa
  • Tijmen Brinkhof
  • Roeland Desmet
  • Paco Frantzen
  • Xavier Goby
  • Ruben Goetstouwers
  • Mariano Ramirez
  • Aung Thu Tun
  • Raphael Ummels
  • Joost Waaijer

Tutor Coaches:

  • Ir. R. Van Gent
  • Dr. J.C. Bijleveld
  • Prof.dr. S.J. Watson

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