2019 IJCAI IJCAI 2019

Swarm Engineering Through Quantitative Measurement of Swarm Robotic Principles in a 10,000 Robot Swarm

Abstract

When designing swarm-robotic systems, system- atic comparison of algorithms from different do- mains is necessary to determine which is capa- ble of scaling up to handle the target problem size and target operating conditions. We propose a set of quantitative metrics for scalability, flexibility, and emergence which are capable of addressing these needs during the system design process. We demonstrate the applicability of our proposed met- rics as a design tool by solving a large object gath- ering problem in temporally varying operating con- ditions using iterative hypothesis evaluation. We provide experimental results obtained in simulation for swarms of over 10,000 robots.

🧭 Keyword Pioneer — scalability metric
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Reinforcement Learning, Robotics