Guerrilla Performance Analysis for Robot Swarms: Degrees of Collaboration and Chains of Interference Events

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.

Simulate Less, Expect More: Bringing Robot Swarms to Life via Low-Fidelity Simulations

“…The potential benefits are clear as shown in many different simulations [5]- [7], but recreating these simulated behaviors on real robotic swarms is not a trivial extension due to physical limitations on actuation/sensing, imperfect communication, or collisions that are often overlooked or oversimplified in the simulated world. Applying these algorithms to real robots can often result in severe issues or failure not observed in simulation [8], [9]. The issues with the simulation-reality gap and the desire to bridge it is not new [10]- [13].…”