Risk-Aware Human-In-The-Loop Multi-Robot Path Planning for Lost Person Search and Rescue

We introduce a framework that would enable using autonomous aerial vehicles in search and rescue scenarios associated with missing person incidents to assist human searchers. We formulate a lost person behavior model and a human searcher model informed by data collected from past search missions. These models are used to generate a probabilistic heatmap of the lost person's position and anticipated searcher trajectories. We use Gaussian processes with a Gibbs' kernel for data fusion to accurately model a limited field-of-view sensor. Our algorithm thereby computes a set of trajectories for a team of aerial vehicles to autonomously navigate, so as to assist and complement human searchers' efforts.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Electrical Engineering

Department dc:contributor.department

Electrical Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2019

Author dc:creator

• Cangan, Barnabas Gavin

Chair dc:contributor.committeechair

• Williams, Ryan K.

Committee members dc:contributor.committeemember

• Abaid, Nicole
• Tokekar, Pratap

• Search and Rescue
• Informative path planning
• Multi-agent path planning
• Gaussian process
• Limited field-of-view
• Gibbs' kernel

Statement dc:rights

• In Copyright

Licence dc:rights.uri

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

Dc Identifier Other

vt_gsexam:21785

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/91444