Autonomous Robot for Disaster Mapping and Victim Localization

TL;DR

This paper presents an autonomous Turtlebot3-based robot system utilizing ROS Noetic for disaster mapping and victim localization, integrating advanced algorithms for efficient exploration and victim detection in unknown environments.

Contribution

It introduces a complete autonomous rescue robot system with novel algorithms like Cubature Kalman Filter and information-theoretic exploration for improved performance.

Findings

Effective mapping and victim localization demonstrated in unknown environments.

Enhanced exploration speed using information-theoretic algorithms.

Reduced localization error with Cubature Kalman Filter.

Abstract

In response to the critical need for effective reconnaissance in disaster scenarios, this research article presents the design and implementation of a complete autonomous robot system using the Turtlebot3 with Robotic Operating System (ROS) Noetic. Upon deployment in closed, initially unknown environments, the system aims to generate a comprehensive map and identify any present 'victims' using AprilTags as stand-ins. We discuss our solution for search and rescue missions, while additionally exploring more advanced algorithms to improve search and rescue functionalities. We introduce a Cubature Kalman Filter to help reduce the mean squared error [m] for AprilTag localization and an information-theoretic exploration algorithm to expedite exploration in unknown environments. Just like turtles, our system takes it slow and steady, but when it's time to save the day, it moves at ninja-like speed! Despite Donatello's shell, he's no slowpoke - he zips through obstacles with the agility of a teenage mutant ninja turtle. So, hang on tight to your shells and get ready for a whirlwind of reconnaissance! Full pipeline code https://github.com/rzhao5659/MRProject/tree/main Exploration code https://github.com/rzhao5659/MRProject/tree/main