'Yuragi'-Based Adaptive Mobile Robot Search With and Without Gradient Sensing: From Bacterial Chemotaxis to a Levy Walk
'Yuragi'-Based Adaptive Mobile Robot Search With and Without Gradient Sensing: From Bacterial Chemotaxis to a Levy Walk
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基于“Yuragi”的自适应移动机器人搜索（带或不带梯度感知）：从细菌趋化性到 Levy Walk
DOI：
10.1163/016918611x590229
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发表时间：
2011
影响因子：
2
通讯作者：
H. Ishiguro
中科院分区：
文献类型：
--
作者：
S. Nurzaman;Y. Matsumoto;Yutaka Nakamura;S. Koizumi;H. Ishiguro
在移动的机器人的研究中，已经研究了许多生物启发的方法，这些方法可以有效地定位诱导梯度信息的目标。在这里，我们专注于实现一个自适应搜索行为的移动的机器人，是简单的，但有效的和不感测的梯度信息。我们感兴趣的两个搜索行为中发现的生物：细菌趋化性（可能是最简单但有效的梯度源搜索行为中发现的生物）和利维行走（一个专门的随机行走分形运动轨迹，优化随机搜索稀疏和随机分布的目标（S））。我们的方法是提出一个统一的框架的基础上'yuragi'（生物波动）实现和联合收割机的两个搜索行为。
Many biologically inspired approaches have been investigated in relation to research on mobile robot(s) that can effectively locate targets that induce gradient information. Here, we concentrate on realizing an adaptive searching behavior in a mobile robot that is simple, yet effective with and without sensing the gradient information. We are interested in two searching behaviors found in biological creatures: bacterial chemotaxis (probably the simplest yet effective gradient sources searching behavior found in living creatures) and Levy walk (a specialized random walk with fractal movement trajectories that optimize random search for sparsely and randomly distributed target(s)). Our approach is to propose a unifying framework based on 'yuragi' (biological fluctuation) to implement and combine the two searching behaviors.
基因网络对环境变化的自适应反应通过健身诱导的吸引子选择。
影响因子：
3.7
作者：
Kashiwagi, Akiko;Urabe, Itaru;Kaneko, Kunihiko;Yomo, Tetsuya
通讯作者：
Yomo, Tetsuya