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Self-Aware Swarm Navigation in Autonomous Exploration Missions
Proceedings of the IEEE ( IF 20.6 ) Pub Date : 2020-07-01 , DOI: 10.1109/jproc.2020.2985950
Siwei Zhang , Robert Pohlmann , Thomas Wiedemann , Armin Dammann , Henk Wymeersch , Peter Adam Hoeher

A multitude of autonomous robotic platforms collectively organized as a swarm attracts increasing attention for remote sensing and exploration tasks. A navigation system is essential for the swarm to collectively localize itself as well as external sources. In this article, we propose a self-aware swarm navigation system that is conscious of the causality between its position and the localization uncertainty. This knowledge allows the swarm to move in a way to not only account for external mission objectives but also enhance position information. Position information for classical navigation systems has already been studied with the Fisher information (FI) and Bayesian information (BI) theories. We show how to extend these theories to a self-aware swarm navigation system, particularly emphasizing the collective performance. In this respect, fundamental limits and geometric interpretations of localization with generic observation models are discussed. We further propose a general concept of FI and BI based information seeking swarm control. The weighted position Cramér–Rao bound (CRB) and posterior CRB (PCRB) are employed flexibly as either a control cost function or constraints according to different mission criteria. As a result, the swarm actively adapts its position to enrich position information with different emerging collective behaviors. The proposed concept is illustrated by a case study of a swarm mission for gas exploration on Mars.

中文翻译:

自主探索任务中的自感知群导航

大量的自主机器人平台被集体组织成一个群,越来越受到遥感和探索任务的关注。导航系统对于群体集体定位自身以及外部来源至关重要。在本文中,我们提出了一种自我感知的群导航系统,该系统意识到其位置与定位不确定性之间的因果关系。这种知识允许群体以一种不仅考虑外部任务目标而且增强位置信息的方式移动。已经使用 Fisher 信息 (FI) 和贝叶斯信息 (BI) 理论研究了经典导航系统的位置信息。我们展示了如何将这些理论扩展到具有自我意识的群体导航系统,特别是强调集体性能。在这方面,讨论了具有通用观测模型的定位的基本限制和几何解释。我们进一步提出了基于 FI 和 BI 的信息搜索群控制的一般概念。加权位置 Cramér-Rao 界 (CRB) 和后验 CRB (PCRB) 被灵活地用作控制成本函数或根据不同任务标准的约束。因此,群体主动调整其位置,以通过不同的新兴集体行为来丰富位置信息。提议的概念通过一个在火星上进行气体勘探的群体任务的案例研究来说明。加权位置 Cramér-Rao 界 (CRB) 和后验 CRB (PCRB) 被灵活地用作控制成本函数或根据不同任务标准的约束。因此,群体主动调整其位置,以通过不同的新兴集体行为来丰富位置信息。提议的概念通过一个在火星上进行气体勘探的群体任务的案例研究来说明。加权位置 Cramér-Rao 界 (CRB) 和后验 CRB (PCRB) 被灵活地用作控制成本函数或根据不同任务标准的约束。因此,群体主动调整其位置,以通过不同的新兴集体行为来丰富位置信息。提议的概念通过一个在火星上进行气体勘探的群体任务的案例研究来说明。
更新日期:2020-07-01
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