This paper addresses the problem of decentralized, collaborative state estimation in robotic teams. In particular, this paper considers problems where individual robots estimate similar physical quantities, such as each other's position relative to themselves. The use of \emph{pseudomeasurements} is introduced as a means of modelling such relationships between robots' state estimates, and is shown to be a tractable way to approach the decentralized state estimation problem. Moreover, this formulation easily leads to a general-purpose observability test that simultaneously accounts for measurements that robots collect from their own sensors, as well as the communication structure within the team. Finally, input preintegration is proposed as a communication-efficient way of sharing odometry information between robots, and the entire theory is appropriate for both vector-space and Lie-group state definitions. The proposed framework is evaluated on three different simulated problems, and one experiment involving three quadcopters.

翻译：本文研究了机器人团队中协作式分布式状态估计问题。特别地，本文关注单个机器人估计同类物理量（如彼此相对位置）的场景。引入伪测量概念作为建模机器人状态估计之间关系的手段，并证明其是解决分布式状态估计问题的可行方法。此外，该公式化方法能便捷地导出通用可观测性测试，该测试可同时考虑机器人自身传感器采集的观测数据及团队内的通信结构。最后，提出采用输入预积分作为在机器人间共享里程计信息的通信高效方式，该理论框架同时适用于向量空间和李群状态定义。所提出的框架在三个仿真问题及一个四旋翼飞行器三机实验中得到验证。