Robotic coordination is a crucial issue in the development of many applications in swarm robotics, ranging from mapping unknown and potentially dangerous areas to the synthesis of plans to achieve complex tasks such as moving goods between locations under resource constraints. In this context, stigmergy is a widely employed approach to robotic coordination based on the idea of interacting with the environment by means of markers called pheromones. Pheromones do not need to be "physical marks", and a number of works have investigated the use of digital, virtual pheromones. In this paper, we show how the concept of virtual pheromones can be implemented in Jason, a Java-based interpreter for an extended version of AgentSpeak, providing a high-level modelling and execution environment for multi-agent systems. We also exploit MQTT, a messaging infrastructure for the Internet-of-Things. This allows the implementation of stigmergic algorithms in a high-level declarative language, building on top of low-level infrastructures typically used only for controlling sensors and actuators.

Implementing virtual pheromones in BDI robots using MQTT and Jason (Short Paper)

Palumbo F;
2016

Abstract

Robotic coordination is a crucial issue in the development of many applications in swarm robotics, ranging from mapping unknown and potentially dangerous areas to the synthesis of plans to achieve complex tasks such as moving goods between locations under resource constraints. In this context, stigmergy is a widely employed approach to robotic coordination based on the idea of interacting with the environment by means of markers called pheromones. Pheromones do not need to be "physical marks", and a number of works have investigated the use of digital, virtual pheromones. In this paper, we show how the concept of virtual pheromones can be implemented in Jason, a Java-based interpreter for an extended version of AgentSpeak, providing a high-level modelling and execution environment for multi-agent systems. We also exploit MQTT, a messaging infrastructure for the Internet-of-Things. This allows the implementation of stigmergic algorithms in a high-level declarative language, building on top of low-level infrastructures typically used only for controlling sensors and actuators.
2016
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-1-5090-5093-2
Multi-agent systems
Stigmergy
Cloud robotics
I.2.9 ARTIFICIAL INTELLIGENCE. Robotics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/319838
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