The response to synchronization is a phenomenon observed in several firefly species, where male ensembles synchronize their rhythmic flashes by triggering a response from females which ends the courtship process. In this work, we present a robotic implementation of this phenomenon by using a team of static e-puck2 robots that integrate oscillatory dynamics to mimic the flashing rhythm of the fireflies. To this end, robots communicate with each other via infrared (IR) and follow a distributed control law. They are divided into two groups: one representing the male population with bursting dynamics and the other representing females with non-bursting behavior. Our experimental results demonstrate that response to synchronization is robust with respect to the presence of realistic features such as obstacles and information loss. These factors play a significant role in refining the original model and enhancing its applicability in real-world scenarios.

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Implementation of the Response to Synchronization in E-Puck2 Robots

  • Cinzia Tomaselli,
  • Gonzalo Marcelo Ramírez-Ávila,
  • Lucia Valentina Gambuzza,
  • Mattia Frasca,
  • Elio Tuci,
  • Timoteo Carletti

摘要

The response to synchronization is a phenomenon observed in several firefly species, where male ensembles synchronize their rhythmic flashes by triggering a response from females which ends the courtship process. In this work, we present a robotic implementation of this phenomenon by using a team of static e-puck2 robots that integrate oscillatory dynamics to mimic the flashing rhythm of the fireflies. To this end, robots communicate with each other via infrared (IR) and follow a distributed control law. They are divided into two groups: one representing the male population with bursting dynamics and the other representing females with non-bursting behavior. Our experimental results demonstrate that response to synchronization is robust with respect to the presence of realistic features such as obstacles and information loss. These factors play a significant role in refining the original model and enhancing its applicability in real-world scenarios.