Path planning in GPS-denied environments via collective intelligence of distributed sensor networks
Path planning in GPS-denied environments via collective intelligence of distributed sensor networks
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DOI：
10.1080/00207179.2015.1110754
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发表时间：
2016-05
影响因子：
2.1
通讯作者：
Devesh K. Jha;Pritthi Chattopadhyay;S. Sarkar;A. Ray
中科院分区：
文献类型：
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作者：
Devesh K. Jha;Pritthi Chattopadhyay;S. Sarkar;A. Ray
摘要本文提出了一种在未知动态环境中无全球定位系统的反应式目标导向导航框架。一种移动的传感器网络用于定位自主移动的机器人的路径规划的感兴趣区域。基本的理论是一个广义的八卦算法，最近开发的语言测量理论设置的扩展。该算法已被用来传播本地决策的目标检测在移动的传感器网络，因此，它产生一个信念图检测到的目标在网络上。在这种设置中，自主移动的机器人可以只与其自己附近的几个移动的感测节点进行通信，并且相对于具有有界不确定性的通信节点来定位自己。机器人利用基于移动的传感器的信念的知识来生成一系列路径点，从而导致可能的目标。基于采样的运动规划算法使用估计的路径点来生成机器人的可行轨迹。在一个移动的传感器网络实验台和一个Dubin的小车机器人上进行了数值仿真，验证了所提出的概念。
ABSTRACT This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin’s car-like robot.