Navigation of Scalar Fronts With Multirobot Clusters in Simulation and Experiment

被引:4
|
作者
McDonald, Robert T. [1 ]
Condino, Matthew [1 ]
Neumann, Michael Alan [1 ]
Kitts, Christopher A. [1 ]
机构
[1] Santa Clara Univ, Dept Mech Engn, Santa Clara, CA 95053 USA
来源
IEEE SYSTEMS JOURNAL | 2020年 / 14卷 / 03期
关键词
Navigation; Aerospace electronics; Ocean temperature; Robot control; Mobile robots; Adaptation models; Adaptive navigation (AN); adaptive sampling; cluster space control; differential control; formation control; gradient estimation; multirobot formations; TRACKING; NETWORKS;
D O I
10.1109/JSYST.2020.2976756
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Environmental fronts are transition regions characterized by a steep gradient in the value of a scalar field. Finding and spatially characterizing these fronts is critical for a variety of scientific applications; however, such work is challenging and usually performed manually, limited to localized characterization, and/or based on assumptions regarding the structure of the front. In this article, we present an automated multirobot control technique to find and spatially characterize general scalar field fronts. This is achieved with a multirobot system that adaptively sizes, orients, and translates based on data sampled by each robot in order to span the width of the front, and to move longitudinally along the front, reversing direction when the end of the front is reached. This span and scan functionality allows the cluster to spatially characterize the front's full extent and to enable comprehensive scientific study of its associated phenomenon. To our knowledge, this is the first comprehensive, adaptive multirobot front-following control strategy proposed for general front structures, and initial verification of its capability is provided through both simulation of behavior on a large-scale front and experimentation with a simple, small-scale indoor multirobot testbed.
引用
收藏
页码:3755 / 3766
页数:12
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