- Herrera, Antonio, Ozen, Emre, Llacsa, Karen, and Rivera, Ernie
- Unmanned Aerial Systems (UASs) can be cost effective and efficiently used for indoor search and rescue missions. These environments pose dangerous and risky scenarios for rescue personnel. UASs can locate and assist victims that are in need during the event of natural disaster with increased safety and low response time, without posing any danger to the rescuers. However, the lack of GPS signal in the indoor environments poses many difficulties for the use and navigation of these systems. A team from Cal Poly Pomona is using two small unmanned aerial systems, one for search and another for rescue, that can help mitigate this problem. The search UAS, a quadcopter, uses a front-facing camera for the detection of victims, a Pixhawk flight controller, and ultrasonic sensors for collision detection. Using computer vision and machine learning, the search quadcopter navigates through the indoor environments and identifies survivors of disaster, and then relays this information to the rescue UAS, also a quadcopter, via a ground control station (GCS). The rescue quadcopter then navigates to the location of the victim and releases the payload. The use of multiple unmanned aerial systems, allow for smaller, lighter, and more agile vehicles to perform better distribution of tasks. This presentation will discuss how the UASs will be able to fly autonomously within GPS-denied environments while detecting victims using artificial neural networks.
- Resource Type:
- Student Research, Presentation, Poster, and Abstract
- Campus Tesim: