Robot Autonomous Fire Location using a Weighted Probability Algorithm

Finding a fire inside of a structure without knowing its conditions poses a dangerous threat to the safety of firefighters. As a result, robots are being explored to increase awareness of the conditions inside structures before having firefighter enter. This thesis presents a method that autonomously guides a robot to the location of a fire inside a structure. The method uses classification of fire, smoke, and other fire environment objects to calculate a weighted probability. Weighted probability is a measurement that indicates the probability that a given region on an infra-red image will lead to fire. This method was tested on large-scale fire videos with a robot moving towards a fire and it is also compared to following the highest temperatures on the image. Sending a robot to find a fire has the potential to save the lives of firefighters.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Engineering

Department dc:contributor.department

Electrical and Computer Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2016

Author dc:creator

• Nogales, Chris Lorena

Chairs dc:contributor.committeechair

• Abbott, A. Lynn
• Lattimer, Brian Y.

Committee member dc:contributor.committeemember

• Tokekar, Pratap

• autonomy
• perception
• Machine learning
• firefighting robot

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

vt_gsexam:8915

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/73360