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间歇性信息驱动多智能体区域受限搜索

Intermittent Information-Driven Multi-Agent Area-Restricted Search.

作者信息

Ristic Branko, Skvortsov Alex

机构信息

School of Engineering, RMIT University, Melbourne, VIC 3000, Australia.

Maritime Division, Defence Science and Technology Group, Fishermans Bend, VIC 3207, Australia.

出版信息

Entropy (Basel). 2020 Jun 8;22(6):635. doi: 10.3390/e22060635.

Abstract

The problem is a two-dimensional area-restricted search for a target using a coordinated team of autonomous mobile sensing platforms (agents). Sensing is characterised by a range-dependent probability of detection, with a non-zero probability of false alarms. The context is underwater surveillance using a swarm of amphibious drones equipped with active sonars. The paper develops an intermittent information-driven search strategy, which alternates between two phases: the fast and non-receptive displacement phase (called the ballistic phase) with a slow displacement and sensing phase (called the diffusive phase). The proposed multi-agent search strategy is carried out in a decentralised manner, which means that all computations (estimation and motion control) are done locally. Coordination of agents is achieved by exchanging the data with the neighbours only, in a manner which does not require global knowledge of the communication network topology.

摘要

问题是利用一组协同的自主移动传感平台(智能体)对目标进行二维区域受限搜索。传感的特点是检测概率与距离有关,且存在非零误报概率。背景是使用一群配备主动声纳的两栖无人机进行水下监视。本文提出了一种间歇式信息驱动搜索策略,该策略在两个阶段之间交替:快速且无感知的位移阶段(称为弹道阶段)和缓慢位移与传感阶段(称为扩散阶段)。所提出的多智能体搜索策略以分散方式执行,这意味着所有计算(估计和运动控制)都在本地完成。智能体之间的协调仅通过与邻居交换数据来实现,这种方式不需要通信网络拓扑的全局知识。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df00/7517170/1c7556458f01/entropy-22-00635-g001.jpg

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