The task of seeking an unknown source with the measurements of the emitted signal strength is named as the source-exploration problem, whose challenging issues with conducting autonomous source-exploration are the lack of $a~priori$ knowledge about the distribution of the emitted signal and the presence of unignorable noise in both the propagation situation and equipped sensor readings. This paper presents a planner for an autonomous robot engaged in seeking for an odor source. The guidance strategy for the planner is based on a control-theoretic paradigm which incorporates an optimization technique into the structure. The control law is inspired by two prominent behaviors widely observed in biology, namely, chemotaxis and anemotaxis. The two behaviors are formulated in the control development. The derived control law is rigorously analyzed and guarantees the converge of a nonlinear under-actuated robot to reach the unknown source, which provides a case study on using run-time optimization to guide rigorous control algorithm development. Besides theoretical proof, our results are also validated in numerical simulations and physical experiments.

中文翻译：

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欠驱动系统的源探索：控制理论范式

通过发射信号强度的测量来寻找未知源的任务称为源探索问题，其进行自主源探索的挑战性问题是缺乏 $ a〜priori $ 在传播情况和配备的传感器读数中，都了解有关发射信号的分布以及存在不可忽略的噪声的知识。本文介绍了一种用于寻找气味源的自主机器人的计划器。计划者的指导策略基于控制理论范式，该理论将优化技术整合到结构中。控制律的灵感来自于生物学上广泛观察到的两种主要行为，即趋化性和止血性。这两种行为是在控件开发中制定的。严格地分析了导出的控制律，并保证了非线性欠驱动机器人的收敛以到达未知源，这为使用运行时优化指导严格的控制算法开发提供了案例研究。除了理论证明，