“自主与自适应控制”:受生物体自适应机制启发的协同群体控制算法

Masatsugu Ogawa, M. Emura, Masumi Ichien, M. Yano
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引用次数: 2

摘要

无人驾驶和自动驾驶汽车(UxV)是许多应用中最具吸引力和最重要的技术之一。在过去的几十年里,许多与多uxv相关的研究都得到了热烈的关注,因为有一种趋势是将这些uxv作为一个群体使用。当算法在uxv中实现实际操作时,算法必须适应现实世界中发生的大量意外环境变化和事件。一般情况下,算法很难兼顾任务的适应性和优化性。在此背景下,我们研究了受生物体启发的自适应机制,并实现了一种新的控制算法,称为“自主和自适应控制”。该算法兼顾了多无人机任务的适应性和优化能力。在本文中,我们将该算法应用于目标跟踪的一个用例。结果表明,该算法在保持较高的检测能力的同时,在运算能耗和防御能力方面均达到了常规算法的最优运算。我们还认为,我们的算法将用于许多其他使用多uxv的用例。
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“Autonomous and Adaptive Control”: Collaborative swarm control algorism inspired by adaptive mechanism of living organisms
Unmanned and autonomous vehicles (UxV) are one of most attractive and important technologies for many kinds of applications. A lot of researches related to multi UxVs have been made enthusiastically for the last several decades because there is a trend to use those UxVs as a swarm. When the algorisms are implemented in UxVs for real operations, the algorism must adapt to a lot of unexpected environmental changes and events occurred in the real world. In general, it is difficult that an algorism reconciles the adaptability and optimization for a mission. In this context, we have been investigated the adaptive mechanism inspired by living organisms and realized a new control algorism called as “Autonomous and adaptive control”. This proposed algorism reconciles adaptability and ability of optimization for a mission of multi UxVs. In this paper, we apply the algorism to a use case of target tracking. It was confirmed that our algorism achieve most optimal operation in comparison of conventional algorisms with respect to energy consumption of the operation and the defense ability while keeping high detection ability. We also think that our algorism will be used for a lot of other use cases with multi UxVs.
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