Self-triggered coordination of robotic networks

机器人传感器网络目前在许多应用中产生了巨大的影响。例子包括跟踪化学污染物运动的协调水下滑翔机网络，监控忙碌街道的摄像机网络，或提供部队保护的一组自动驾驶车辆。在最基本的层面上，这些网络的协调策略涉及代理反复进行测量，与其他代理进行通信，处理收集到的数据，并采取相应的行动。在这些应用程序中的一个共同的假设是，信息的连续性或周期性的其他代理和环境的状态，这些策略的同步执行代理的可用性。这种同步假设在实践中提出了不平凡的挑战，并导致在处理器使用率，通信带宽和能源方面的效率低下的实现。例如，周期性通信可能导致对可用资源的浪费。当考虑到不确定性时，它通常是以“后验”的方式进行的：只有当代理人的时间表满足确保信息新鲜度的条件时，才能保证。虽然这样的结果是有效的，从分析的角度来看，他们是不满意的，从设计的角度来看，因为确保这样的条件下举行的不是内置的算法synthesis. This建议的目标是设计的自触发的协调策略，占不确定性的状态，其他代理和环境，并能够产生大量的能源节约在网络运行。关键的概念新奇是研究整个网络任务的性能如何受到代理商可用信息质量的影响。这种理解导致工具和触发标准，使他们能够自主决定何时需要新的信息来成功执行所需的任务。自触发策略消除了持续的通信，传感和重新规划的需要，在控制设计阶段纳入不确定性，无缝处理异步执行的计划，并增加代理的自主性和网络efficiency.Intellectual优点：这项建议旨在开发工具，抽象，和技术，帮助设计自主机器人传感器网络的自触发合作策略。我们的最终目标是综合强大而有效的合作策略，处理不确定性和不确定性，并确保机器人网络执行指定的任务，保证服务质量，同时在有限的能源供应，带宽和计算资源。该研究计划是结构沿着以下推力：（一）可靠的模型和抽象，捕捉网络和环境的状态的不确定性的合成;（二）触发标准，允许代理确定的影响，计划与他们的当前信息的网络性能的行动的识别; ㈢开发稳定性和正确性工具，适用于分析自触发协调战略，并准确描述其稳健性和效率特性。我们设想，所提出的范例将导致合成在各种分布式的情况下，新的协调算法，优化性能和实施成本之间的权衡，并具有上级鲁棒性保证比现有的战略。多智能体系统正在越来越多的场景中扩展人类能力的范围，包括海洋研究，灾难恢复，环境监测，和监视该项目的结果将有助于设计强大而有效的合作策略，自然占的不确定性，并能够产生大量的能源节省在网络运行。教育活动被纳入研究计划，包括（i）本科生通过暑期实习，独立学习课程和高级设计项目参与研究。PI属于加州大学圣地亚哥分校Cymer控制系统和动力学中心，并将参与监督行业赞助的控制本科生研究;（ii）提供合作控制和研究生监督的研究生课程;（三）通过加州数学和科学暑期学校计划以及与NSF资助的ComPASS项目的合作，针对高中学生和教师开展外联活动，UCSD;（iv）少数民族学生通过参加UCSD工程学院IDEA学生中心的活动参与;（v）广泛的传播活动（期刊出版物，会议，研讨会演讲和会议组织）。

There are a myriad of current applications in which robotic sensor networks are having an enormous impact. Examples include a network of coordinated underwater gliders tracking the motion of chemical pollutants, a camera network monitoring a busy street, or a group of autonomous vehicles providing force protection. At the most basic level, coordination strategies for these networks involve agents repeatedly taking measurements, communicating with other agents, processing the collected data, and taking actions in response. A common assumption throughout these applications is the continuous or periodic availability of information to the agents about the state of other agents and the environment, and the synchronous execution of these strategies. This synchronization assumption poses nontrivial challenges in practice and leads to inefficient implementations in terms of processor usage, communication bandwidth, and energy. Periodic communication, for instance, may lead to a wasteful use of the available resources. When asynchronism is considered, it is often done in "a posteriori" fashion: guarantees only hold if the agents time schedules satisfy conditions ensuring the freshness of information. While such results are valid from an analysis viewpoint, they are unsatisfactory from a design perspective because ensuring that such conditions hold is not built into the algorithm synthesis.The objective of this proposal is the design of self-triggered coordination strategies that account for uncertainty in the state of other agents and the environment, and are able to produce substantial energy savings in the network operation. The key conceptual novelty is the study of how the performance of the overall network task is affected by the quality of the information available to the agents. This understanding leads to tools and triggering criteria for individual agents that allow them to autonomously decide when they need fresh information to successfully perform the required task. Self-triggered strategies eliminate the need for continuous communication, sensing, and re-planning, incorporate uncertainty at the control design stage, seamlessly handle asynchronous executions of plans, and increase agent autonomy and network efficiency.Intellectual Merit: This proposal seeks to develop tools, abstractions, and techniques that help design self-triggered cooperative strategies for autonomous robotic sensor networks. Our ultimate goal is to synthesize robust and efficient cooperative strategies that handle uncertainty and asynchronism, and ensure that the robotic network performs the assigned task with guaranteed quality of service, while operating with limited energy supplies, bandwidth, and computational resources. The research plan is structured along the following thrusts: (i) the synthesis of reliable models and abstractions that capture the uncertainty about the state of the network and the environment; (ii) the identification of triggering criteria that allow agents to determine the impact that the actions planned with their current information have on the performance of the network; (iii) the development of stability and correctness tools suited for the analysis of self-triggered coordination strategies and the precise characterization of their robustness and efficiency properties. We envision that the proposed paradigm will lead to the synthesis in a variety of distributed scenarios of novel coordination algorithms that optimize the trade-offs between performance and implementation cost and have superior robustness guarantees than existing strategies.Broader Impacts: Multi-agent systems are extending the range of human capabilities in an increasing number of scenarios, including the study of oceans, disaster recovery, environmental monitoring, and surveillance. The results of this project will help design robust and efficient cooperative strategies that naturally account for uncertainty and are able to produce substantial energy savings in the network operation. The educational activities are integrated into the research plan and consist of (i) undergraduate student involvement in research via summer internships, independent study courses, and senior-design projects. The PI belongs to the UCSD Cymer Center for Control Systems and Dynamics and will be involved in the supervision of industry-sponsored undergraduate research in control; (ii) offering of a graduate course on cooperative control and graduate student supervision; (iii) outreach targeted at high school students and teachers through the California State Summer School for Mathematics and Science program and collaboration with the NSFfunded project ComPASS at UCSD; (iv) involvement of minority students through participation in the activities of the UCSD School of Engineering IDEA Student Center; (v) broad dissemination activities (journal publications, conference, workshop presentations, and conference organization).