Abstract
Scalability is a key feature of swarm robotics. Hence, measuring performance depending on swarm size is important to check the validity of the design. Performance diagrams have generic qualities across many different application scenarios. We summarize these findings and condense them in a practical performance analysis guide for swarm robotics. We introduce three general classes of performance: linear increase, saturation, and increase/decrease. As the performance diagrams may contain rich information about underlying processes, such as the degree of collaboration and chains of interference events in crowded situations, we discuss options for quickly devising hypotheses about the underlying robot behaviors. The validity of our performance analysis guide is then made plausible in a number of simple examples based on models and simulations.
Original language | English |
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Title of host publication | ANTS 2020: Swarm Intelligence |
Editors | Marco Dorigo, Thomas Stützle, Maria J. Blesa, Christian Blum, Heiko Hamann, Mary Katherine Heinrich, Volker Strobel |
Number of pages | 14 |
Volume | 12421 LNCS |
Publisher | Springer, Cham |
Publication date | 23.10.2020 |
Pages | 134-147 |
ISBN (Print) | 978-3-030-60375-5 |
ISBN (Electronic) | 978-3-030-60376-2 |
DOIs | |
Publication status | Published - 23.10.2020 |
Event | 12th International Conference on Swarm Intelligence - Barcelona, Spain Duration: 26.10.2020 → 28.10.2020 Conference number: 250669 |