Situational awareness and indoor positioning of firefighters are types of information of paramount importance to the success of search and rescue operations. GPS units are undependable for use in Indoor Positioning Systems due to their associated mar- gins of error in position and their reliance on satellite communication that can be interrupted inside large structures. There are few other techniques like dead reck- oning, Wifi and bluetooth based triangulation, Structure from Motion (SFM) based scene reconstruction for Indoor positioning system. However due to high temper- atures, the rapidly changing environment of fires, and low parallax in the thermal images, the above techniques are not suitable for relaying the necessary information in a fire fighting environment that is needed to increase situational awareness in real time.
In fire fighting environments, thermal imaging cameras are used due to smoke and low visibility, hence obtaining relative orientation from camera information alone be- comes very difficult. We gained a deeper appreciation of the significance of maintain- ing a sense of relative orientation to a first responders ability to successfully navigate
when we first visited first responders training facility for data collection. The follow- ing technique that is the content of this research is two fold; Firstly, we implement a novel, optical flow, gyroscope-based relative orientation estimation and secondly, we implement a velocity estimation technique using data from accelerometer fused with LIDAR. We also provide insight, discuss about the data we are going to use for our implementations.
The Implementation helps first responders to go into unprepared, unknown envi- ronments and still maintain situational awareness like the orientation aid and position of the victim fire fighters. We also discuss and provide proof of concept implemen- tation to apply Deep Q learning algorithm on top of this to present efficient, safest path a firefighter can take in a first responding scenario.
Indoor positioning system(IPS), Video Compass, SIFT, Optical flow, LIDAR, Inertial Measurement Unit (IMU), Infrared Image processing.
Level of Degree
Electrical and Computer Engineering
First Committee Member (Chair)
Manel Martinez Ramon
Second Committee Member
Third Committee Member
Vadlamani, Vamsi Karthik. "A Novel Indoor Positioning System for Firefighters in Unprepared Scenarios." (2018). https://digitalrepository.unm.edu/ece_etds/452