Date of Award
2024
Degree Type
Thesis
Degree Name
Master of Science in Electrical Engineering (MSEE)
Specialization
Robotics
Department
Electrical, Computer, and Biomedical Engineering
First Advisor
Paolo Stegagno
Abstract
This work presents Range of Communication Swarm SLAM (RCS-SLAM) as a novel approach to simultaneous localization and mapping (SLAM) that is better suited for swarm robotic systems. RCS-SLAM introduces a novel SLAM front-end that leverages the effective range of an inter-robot communication medium to add inequality constraints between nodes in a pose graph whenever two robots communicate or relay communications. The centralized SLAM back-end then converts the inequality constrained pose graph into an unconstrained optimization problem using the penalty method to enforce the maximum possible range between communicating nodes. Converting to an unconstrained problem allows for the estimate to optimized efficiently using state of the art solvers. This approach leverages the range of the communication medium to reduce dependence on complex exteroceptive sensors typically found in collaborative multi-robot SLAM systems, making the RCS-SLAM approach more applicable to the lightweight economical agents found in swarm systems. The approach is tested in a ROS Gazebo simulation of twenty differential drive robots and evaluated under three swarm control strategies to identify the operating and communication conditions that maximize its effectiveness. The performance of RCS-SLAM is compared to recent approaches where direct inter-robot ranging methods are used to improve the pose graph estimate. It is shown that RCS-SLAM performs comparably at reducing pose estimate error while reducing system complexity and sensor requirements.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Hoburg, Adam J., "RCS-SLAM: RANGE OF COMMUNICATION SWARM SLAM" (2024). Open Access Master's Theses. Paper 2479.
https://digitalcommons.uri.edu/theses/2479