Optimization of route planning and exploration using multi agent system

Abstract

This research presents an optimization technique for route planning and exploration in unknown environments. It employs the hybrid architecture that implements detection, avoidance and planning using autonomous agents with coordination capabilities. When these agents work for a common objective, they require a robust information interchange module for coordination. They cannot achieve the goal when working independently. The coordination module enhances their performance and efficiency. The multi agent systems can be employed for searching items in unknown environments. The searching of unexploded ordinance such as the land mines is an important application where multi agent systems can be best employed. The hybrid architecture incorporates learning real time A* algorithm for route planning and compares it with A* searching algorithm. Learning real time A* shows better results for multi agent environment and proved to be efficient and robust algorithm. A simulated ant agent system is presented for route planning and optimization and proved to be efficient and robust for large and complex environments.

Human Interface and the Management of Information. Information and Knowledge Design

“…One work utilizing this approach incorporates real time learning using the A* and compares it with the A* searching algorithm (Zafar and Baig 2012). This shows better results for multi-agent environments and proves to be an efficient and robust algorithm.…”

Impact of the variation of the number of agents in the cooperative learning of optimal paths using LRTA-star

“…Sistemas multiagente podem ser utilizados para explorar ambientes desconhecidos e encontrar os caminhos ótimos de maneira eficiente utilizando algoritmos de busca [Zafar and Baig 2012]. O paradigma de resoluc ¸ão de problemas chamado organizational problem solving (resoluc ¸ão de problema organizacional) para sistemas multiagente, introduzido por [Ishida 1998], define a eficiência da soluc ¸ão de um problema cooperativo de acordo com o tipo de organizac ¸ão entre os agentes.…”