Abstract

In this paper, we propose an emotional model for robots in a multi-robot system, in order to allow emerging behaviors. The emotional model uses four universal emotions: anger, disgust, sadness, and joy, assigned to each robot based on the level of satisfaction of its basic needs. These four universal emotions lie on a spectrum where depending where the emotion of the robot lies, can affect its behavior and of its neighboring robots. The more negative the emotion is, the more individualistic it becomes in its decisions (anger, sadness or disgust). The more positive the robot is in its emotion, the more it will consider the group and global goals (joy). Each robot is able to recognize another robot′s emotion in the system based on their current state, using the AR2P (AR2P for its acronym in Spanish: Algoritmo Recursivo de Reconocimiento de Patrones) recognition algorithm. In this way, it can use this information of the emotions to decide with whom collaborate. Specifically, the paper addresses emotions’ influence on the behavior of the system, at the individual and collective levels, and the emotions’ effects on the emergent behaviors of the multi-robot system. The paper explores the emerging behavior in two multi-robot scenarios; nectar harvesting and object transportation. The results show that the emotions are important to the emergent behavior in a multi-robot system.

摘要

在本文中，我们提出了一种多机器人系统中的机器人情感模型，以允许出现新的行为。情感模型使用四种普遍的情感：愤怒，厌恶，悲伤和喜悦，这些情感是根据其基本需求的满意度分配给每个机器人的。这四种普遍的情绪位于一个频谱上，在该频谱上，机器人的情感所在的位置会影响机器人及其相邻机器人的行为。情绪越消极，其决定（愤怒，悲伤或厌恶）就越具有个人主义色彩。机器人对自己的情绪越积极，就越会考虑群体和全球目标（欢乐）。每个机器人都可以使用AR2P（AR2P为西班牙语的缩写：AR2P）基于其当前状态识别系统中另一个机器人的情绪。Algoritmo Recursivo de Reconocimiento de Patrones）识别算法。这样，它可以使用这种情绪信息来决定与谁合作。具体而言，本文探讨了情绪在个体和集体层面上对系统行为的影响，以及情绪对多机器人系统紧急行为的影响。本文探讨了两种多机器人场景中的新兴行为。花蜜采集和物体运输。结果表明，情绪对于多机器人系统中的突发行为很重要。