Contaminant Tracking in GPS-Denied Environments

该项目追求一种具有开创性潜力的方法，用于完全自动驾驶车辆的运动控制，该方法允许仅使用污染物浓度的测量来寻找、发现和跟踪污染场的源，而不需要GPS或INS信息。这种方法建立在PI在通过极值搜索控制进行实时优化领域的最新进展的基础上。这项工作的重点是：(A)将提案中的初步发现从移动机器人的2D运动扩展到水下和空中飞行器的3D运动；(B)使用平均和奇异摄动技术对方案进行收敛研究；(C)在湍流(而不仅仅是扩散)流场中对结果进行数值测试；(D)测试方案的“污染物清除”能力，其中通过释放中和剂来暂时降低追踪器所经过的路径上的污染物浓度；(E)将结果从单一污染源和单一跟踪器扩展到多个污染源和多个跟踪器；(F)在光学领域使用移动机器人进行模拟污染场的实验；(G)在环境室内使用浓度传感器(用于烟雾)进行实验。

An approach with ground breaking potential for motion control of completely autonomous vehicles is pursued in this project, which allows to seek, find, and follow a source of a contaminant field using only the measurement of the concentration of the contaminant and not requiring GPS or INS information. This approach builds on recent advances by the PI in the area of real-time optimization via extremum seeking control. The work focuses on the following tasks: (A) extending the initial discovery presented in the proposal from 2D locomotion for mobile robots to 3D locomotion for underwater and aerial vehicles; (B) performing a convergence study for the schemes using averaging and singular perturbation techniques; (C) numerically testing the results in turbulent (rather than merely diffusive) fluid fields; (D) testing of "contaminant cleaning" abilities of the schemes where the contaminant concentration is reduced temporarily along the path traveled by the tracker by releasing an agent that neutralizes the contaminant; (E) extending the results from a single contaminant source and single tracker to multiple contaminant sources and multiple trackers; (F) performing experiments with a mobile robot in an optical field emulating a contaminant field; (G) performing experiments with concentration sensors (for smoke) in an environmental chamber.