We investigate the automatic design of communication in swarm robotics through two studies. We first introduce Gianduja an automatic design method that generates collective behaviors for robot swarms in which individuals can locally exchange a message whose semantics is not a priori fixed. It is the automatic design process that, on a per-mission basis, defines the conditions under which the message is sent and the effect that it has on the receiving peers. Then, we extend Gianduja to Gianduja2 and Gianduja 3, which target robots that can exchange multiple distinct messages. Also in this case, the semantics of the messages is automatically defined on a per-mission basis by the design process. Gianduja and its variants are based on Chocolate, which does not provide any support for local communication. In the article, we compare Gianduja and its variants with a standard neuro-evolutionary approach. We consider a total of six different swarm robotics missions. We present results based on simulation and tests performed with 20 e-puck robots. Results show that, typically, Gianduja and its variants are able to associate a meaningful semantics to messages.

中文翻译：

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具有本地通信能力的机器人集体行为的模块化自动设计


我们通过两项研究研究了群体机器人中通信的自动设计。我们首先介绍 Gianduja 一种自动设计方法，它为机器人群生成集体行为，其中个体可以在本地交换语义不是先验固定的消息。这是一个自动设计过程，在每个任务的基础上定义发送消息的条件以及它对接收对等方的影响。然后，我们将 Gianduja 扩展到 Gianduja2 和 Gianduja 3，其目标是可以交换多个不同消息的机器人。同样在这种情况下，消息的语义是由设计过程根据每个任务自动定义的。 Gianduja 及其变体基于 Chocolate，不提供任何本地通信支持。在本文中，我们将 Gianduja 及其变体与标准神经进化方法进行了比较。我们总共考虑了六种不同的群体机器人任务。我们展示了基于 20 个 e-puck 机器人进行的模拟和测试的结果。结果表明，Gianduja 及其变体通常能够将有意义的语义与消息相关联。