CPS: Medium: Information based Control of Cyber-Physical Systems operating in uncertain environments

大多数网络物理系统都运行在相对良好的环境中，通常是为满足系统需求而设计的。例如，在许多环境中，机器人在制造业的封闭环境中运行。然而，随着这些系统部署在越来越孤立的环境中(例如搜救工作、外科手术设备的自动化、协作制造)，这些机器人将需要在对大量不确定性进行推理的同时进行操作。此外，系统采取的行动影响了这种不确定性。这项拟议的工作将开发算法，使网络物理系统能够推理出它必须采取什么行动来管理其不确定性。这方面的一个简单例子是理解在搜索对象时必须向后和向下看。这个项目的目标是自动化管理不确定性的过程，无论它是如何出现的。例如，与人类互动(例如，在帮助某人运动时与她进行身体互动，或在搜索过程中跟踪某人)涉及到对此人将做什么的不确定性。使机器人系统能够主动测试一个人的意图，然后根据她随后的行为采取行动，这是机器人成为有效合作伙伴的能力的关键。这一要点，即网络物理系统部分的行为可以被用来明确地管理其对世界的理解，这是拟议工作的核心目的。拟议工作将利用基于信息的实时非线性控制的最新成果。具体地说，遍历控制(控制轨迹相对于某个参考分布的遍历性)使人们能够使用密度函数来指定目标，以描述轨迹的期望空间特征。在隐马尔可夫模型(HMM)和部分可观测马尔可夫决策过程(POMDP)的背景下，这允许系统主动探测多个状态，同时考虑过程不确定性、测量不确定性和与马尔可夫过程本身相关联的不确定性，即使当HMM由于新的状态或过程被引入环境环境而随时间改变时也是如此。在不确定条件下的反应规划中，遍历控制的有效性的明显原因是它总是在连续统中计算计划，避免了与POMDP相关的组合复杂性。此外，在物理运动过程中，动态系统和网络系统的需求是相互关联的，因此这项工作还将开发保持状态和信息稳定的方法。这种相互依赖在物理行为能力和网络系统上的计算负载之间产生了一种权衡，使网络物理系统能够通过物理行动来减少其网络系统的负载。这项研究将开发能够根据不断变化的数据进行实时信息控制的算法。其中一个激动人心的例子将是空中飞行器在高度遮挡的环境中跟踪地面上未知数量的目标，例如森林或城市环境。此外，已经用于辅助设备研究的机械臂将被用于实施和评估拟议的方法。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Most cyber-physical systems have operated in comparatively benign environments, often engineered to meet the needs of the system. For instance, in many settings robots operate in closed-off environments in manufacturing. However, as these systems are deployed in increasingly isolated environments (such as search and rescue efforts, automation in surgical devices, collaborative manufacturing) these robots will need to operate while reasoning about substantial uncertainty. Moreover, actions taken by the system impact that uncertainty. The proposed work will develop algorithms that enable a cyber-physical system to reason about what actions it must take to manage its uncertainty. A simple example of this is understanding that one must look behind and under things when searching for an object. The goal of this project is to automate the process of managing that uncertainty, however it arises. For instance, interacting with humans (such as physically interacting with a person while assisting her motion, or tracking a person during a search effort) involves uncertainty about what the person is going to do. Enabling a robotic system to actively test a person's intent, and then act according to her subsequent behavior, is key to the robot's ability to be an effective partner. This essential point, that action on the part of a cyber-physical system can be used to explicitly manage its understanding of the world, is the core purpose of the proposed work.The proposed work will leverage recent results in information-based real-time nonlinear control. Specifically, ergodic control (controlling the ergodicity of a trajectory relative to some reference distribution) enables one to specify an objective using a density function to describe the desired spatial characteristics for a trajectory. In the context of Hidden Markov Models (HMMs) and Partially Observable Markov Decision Processes (POMDPs), this allows a system to actively probe multiple states, simultaneously considering process uncertainty, measurement uncertainty, and uncertainty associated with the Markov process itself, even when the HMM is changing over time because of new states or processes being introduced into the ambient environment. The apparent reason for the effectiveness of ergodic control in the context of reactive planning under uncertainty is that it always computes plans in the continuum, avoiding the combinatoric complexity associated with POMDPs. Moreover, the needs of the dynamic system and the cyber system are inter-related during physical motion, so the work will additionally develop methods that maintain stability with respect to both state and information. This inter-dependence creates a trade-off between the physical ability to act and the computational load on the cyber system, enabling a cyber-physical system to reduce the load on its cyber system through physical action. The research will develop algorithms capable of real-time information-based control in response to constantly changing data. One of the motivating examples will be aerial vehicles tracking unknown numbers of targets on the ground in a highly occluded environment such as a forest or an urban setting. Additionally, a robotic arm, already used for assistive device research, will be used to implement and assess the proposed methods.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.