Abstract

Swarm robotics is a system of multiple robots where a desired collective behavior emerges from the interactions between the robots and with the environment. This paper proposes an emotional model for the robots, 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 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. The more positive the robot is in its emotion, the more it will consider the group and global goals. Each robot is able to recognize another robot's emotion in the system based on their current state, using the AR2P recognition algorithm. 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 analyses two emergent scenarios: nectar harvesting and object transportation, and shows the importance of the emotions into the emergent behavior in a multi-robot system

Highlights

  • Swarm robotics is a set of autonomous robots that work together to accomplish a task

  • The initial value of emotiveness is high (0.8) because the robots can change of emotional states, the emotion types are low (0.35) because this scenario does not use a lot of emotions, and the behavior component is high (0.95) because our system has a behavior component based on our emotional model

  • One of the main characteristics of our emotional model for multi-robot systems is that it allows the recognition of the emotions, in order to generate emergent behaviors, which gives a large flexibility to the system to execute different tasks

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Summary

Introduction

Swarm robotics is a set of autonomous robots that work together to accomplish a task. The effect of the emotions on the emergent behavior of a swarm robotics, or multi-robot system, and their process of recognition, is studied. The authors of [7] define a hybrid approximation for multi-robot systems; work [8] proposes an algorithm based on the human immunological system for the cooperative transportation of objects. In [11], the authors propose an emotional model for robots, which measures the individual cooperative willingness in the problem of multi-robot task allocation. We define two scenarios for testing the emotion recognition in a multi-robot system, to generate emergent behaviors: one inspired in the search of nectar of the bees, and another inspired in the behaviors of ants when transporting an object.

Our emotional model
Formal description of the emotion recognition problem in multi-robot systems
Emotion recognition using the AR2P algorithm
Case 1
Case 2
Emergent behavior analysis based on the MASOES model
Emergent behavior analysis using simulations
Emergent behavior analysis using an entropy metric
Robustness of our model and comparison with other works
Conclusions
Full Text
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