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Autonomous Exploration Guided by Optimisation Metaheuristic

机译:优化元启发式指导的自主勘探

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Autonomous exploration aims to develop mechanisms that enable a robot to navigate through an unknown environment, seeking to collect information that is relevant to its objective, with minimal or no human intervention. This article presents an autonomous exploration strategy based on a multimodal continuous utility function and optimization metaheuristic. The problem of autonomous exploration of mobile robots is formulated as an optimization problem, providing data for a Firefly-based algorithm that is able to search for points in the solution space, representing cells on the map being constructed, that best meet the exploration objectives. Simulations in a Robot Operating System environment showed that the proposed approach is able to guide robot through good trajectories, leading to full mapping, without any human intervention.
机译:自主探索的目的是开发使机器人能够在未知环境中导航的机制,以最少或无需人工干预即可收集与其目标相关的信息。本文提出了一种基于多模式连续效用函数和优化元启发式的自主探索策略。移动机器人的自主探索问题被表述为优化问题,它为基于Firefly的算法提供了数据,该算法能够在解空间中搜索点,代表正在构建的地图上最能满足探索目标的单元。在机器人操作系统环境中的仿真表明,所提出的方法能够引导机器人通过良好的轨迹,从而实现全图绘制,而无需任何人工干预。

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