Improved Swarm Engineering: Aligning Intuition and Analysis [preprint]

Preprint date

December 8, 2020

Authors

John Harwell (Ph.D. student), Maria Gini (professor)

Abstract

When designing swarm-robotic systems, systematic comparison of swarm control algorithms is necessary to determine which can scale up to handle the target problem size and operating conditions. Qualitative predictions of performance based on algorithm descriptions are often incorrect, and can lead to costly design processes for swarm-robotic systems. We propose a set of quantitative measures for swarm scalability, emergence, flexibility, and robustness which enable swarm control algorithms analysis and comparison, swarm performance of a given control algorithm, collectively enabling quicker and more confident design decisions. We demonstrate the utility of our proposed measurements as modeling and design tools for real-world scenarios by analyzing two common problems, indoor warehouse object transport and search and rescue, and present experimental results obtained in simulation.

Link to full paper

Improved Swarm Engineering: Aligning Intuition and Analysis

Keywords

robotics, intelligent agents