Date of Award
Summer 8-24-2024
Document Type
Masters Thesis
Degree Name
M.S. in Computer Science
Organizational Unit
Daniel Felix Ritchie School of Engineering and Computer Science, Computer Science
First Advisor
Christopher Reardon
Second Advisor
Jason M. Gregory
Third Advisor
Kerstin S. Haring
Fourth Advisor
Naomi Reshotko
Copyright Statement / License for Reuse
All Rights Reserved.
Keywords
Heterogenous robot team, Multi-robot systems, Person following
Abstract
Maintaining visibility of a person requires effective systems. Security cameras or ground robots might be ideal, but they often fail in uncontrolled or unknown environments. A single ground robot struggles to navigate and track an agent at the same time. This work addresses the challenge by developing a multi-robot system with a slow ground robot and an agile aerial robot. Three methods are evaluated: FORWARD-PF, RL-Person Following (RL), and a baseline closed-loop method. FORWARD-PF proved the most reliable, completing all nine paths and reaching targets nearly twice as fast as RL. Despite completing seven paths, RL faltered on complex tasks. The closed-loop method succeeded only 33% of the time, managing just the easiest paths. These findings underscore FORWARD-PF’s efficiency and reveal both the potential and limitations of RL, demonstrating the promise of heterogeneous multi-robot systems for person-following in unpredictable settings.
Copyright Date
8-2024
Publication Statement
Copyright is held by the author. User is responsible for all copyright compliance.
Rights Holder
Ori A. Miller
Provenance
Received from Author
File Format
application/pdf
Language
English (eng)
Extent
87 pgs
File Size
4.8 MB
Recommended Citation
Miller, Ori A., "Heterogeneous Multi-Robot Person-Following in Constrained Environments" (2024). Electronic Theses and Dissertations. 2490.
https://digitalcommons.du.edu/etd/2490
