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

该动力学、控制和系统诊断项目将支持实现多机器人系统大规模、分布式协调的研究，促进科学进步，促进国家繁荣。在监视、安全和灾难响应等应用中，移动自主机器人网络可以在广泛的区域内共同跟踪目标。当主体和机器人进出观察和通信范围时，网络中的每个机器人都需要传播基于噪声测量的自身和主体的位置、速度和方向估计。第一个任务被称为“定位”，第二个任务被称为“跟踪”。通信的限制意味着依靠中央控制器通常是不可行的，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单个机器人之间协调信息的问题，使每个机器人都能做出最好的决定。该项目的成果将有利于涉及多机器人系统的许多应用，如监视和安全、灾难响应和环境监测。教育和外联活动将扩大代表性不足的群体对研究的参与。本项目旨在解决移动机器人网络分布式协同传感中由于传感间隙、局部通信和缺乏绝对姿态测量而引起的基本理论和实践问题。第一个重点是推导出一个统一的框架，通过局部合作实现全分布式联合定位和目标跟踪。第二个重点是对具有现实问题的框架进行严格的理论分析，即稀疏和变化的传感和通信以及不确定的目标模型。第三个重点是具有物理约束的移动机器人网络的实验演示。该研究将对分布式估计的理论和应用产生重要的推动作用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.