Distributed Joint Localization and Tracking for Multi-robot Networks Under Local Sensing and Communication Constraints with Theoretical Guarantees

这个动力学、控制和系统诊断项目将支持研究，以实现多机器人系统的大规模、分布式协调，促进科学进步和国家繁荣。在监视、安全和灾难应对等应用中，移动自主机器人网络在广泛的区域内集体跟踪对象。当对象和机器人进入和离开观察和通信范围时，网络中的每个机器人都需要基于噪声测量来传播对自身和对象的位置、速度和方向的估计。第一个任务叫做“本地化”，第二个任务叫做“跟踪”。通信限制意味着依靠中央控制器往往是不可行的，因此每个机器人必须负责做出自己的决定。这个项目将解决如何在各个机器人之间协调信息的问题，使每个机器人都能做出可能的最佳决策。该项目的成果将有利于许多涉及多机器人系统的应用，如监视和安全、灾害应对和环境监测。教育和外联活动将扩大任职人数不足的群体参与研究的范围。本项目的目标是解决在移动机器人网络的分布式协作传感中由于传感间隙、本地通信和缺乏绝对位姿测量而引起的基本理论和实践问题。第一个主旨是通过地方合作，为完全分布式的联合定位和目标跟踪建立一个统一的框架。第二个重点是对该框架进行严格的理论分析，并结合现实问题，即稀疏和变化的感知和通信以及不确定的目标模型。第三个推力是在有物理约束的移动机器人网络上进行实验演示。这项研究将极大地推动分布式评估在理论和应用方面的发展。这一奖项反映了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。

This Dynamics, Control, and System Diagnostics project will support research to enable large-scale, distributed coordination of multi-robot systems, promoting the progress of science and advancing the national prosperity. In applications such as surveillance, security, and disaster response, a network of mobile autonomous robots collectively tracks a subject over a wide area. As the subject and the robots move in and out of observation and communication range, each robot in the network needs to propagate estimates of position, velocity, and orientation for both itself and the subject, based on noisy measurements. The first task is called "localization," and the second task is called "tracking." Communication limitations mean that it is often infeasible to rely on a central controller, so each robot must be responsible for making its own decisions. This project will address the problem of how to coordinate information among the individual robots, to allow each of them to make the best possible decisions. Results from the project will benefit numerous applications involving multi-robot systems such as surveillance and security, disaster response and environmental monitoring. Education and outreach activities will broaden participation of underrepresented groups in research. The objective of this project is to address the fundamental theoretical and practical issues caused by sensing gaps, local communication, and lack of absolute pose measurements in distributed collaborative sensing with mobile robotic networks. The first thrust is to derive a unified framework for fully distributed joint localization and target tracking through local cooperation. The second thrust is rigorous theoretical analysis of the framework with realistic issues, namely, sparse and changing sensing and communication and uncertain target models. The third thrust is experimental demonstration on mobile robotic networks with physical constraints. The research will significantly advance distributed estimation in both theory and applications.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.