Publication Date

2018

Document Type

Dissertation/Thesis

First Advisor

Butail, Sachit

Degree Name

M.S. (Master of Science)

Department

Department of Mechanical Engineering

LCSH

Mechanical engineering||Robotics

Abstract

Robotic swarms are well suited for missions that involve covering large areas such as environmental monitoring, search-and-rescue operations, as well as those that require fusing information from multiple sources such as target tracking and machine inspection. However, navigating a swarm of robots effectively requires performing higher-level functions that are typically executed by humans such as commanding them to stay close and guiding them along with a preplanned route. In this context, the ability of multiple robots to stay together autonomously significantly reduces the cognitive load on a human operator. The goal of this thesis is to design and build a multi-robot testbed for studying human-swarm interaction. The specific objective of this research is to use methods from simulation-based design to estimate the control parameters required for robust operation of the robots. A consensus algorithm is implemented on simulated unicycle agents to keep them within sight of each other, as they follow a human leader. The algorithm is augmented with features to match a real-world implementation including realistic occlusion of swarm members in the presence of obstacles and collision handling. Search strategies are incorporated to reduce instances where a robot can be lost forever. Following an exhaustive simulation exercise, the control gains that reveal the best performance in terms of swarm connectedness and the ability to reach a goal location are further assessed in terms of their sensitivity to sensor noise. Finally, the approach is implemented and tested on an iRobot Create 2 testbed that consists of six robots monitored using an array of wide-angle web cameras in a large laboratory environment with obstacles. In a true decentralized architecture, the robots are instrumented with a microcontroller and a web camera to follow each other using vision-based cues only without any external reference.

Comments

Committee members: Fonseca, Benedito; Ryu, Ji-Chul.||Advisor: Butail, Sachit.||Includes bibliographical references.

Extent

52 pages

Language

eng

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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