The problem of cooperative navigation for a team of platforms employing inter-platform observations is investigated. A decentralised solution in the framework of an information filter with delayed states is presented. In this structure, each platform first estimates its motion using only local sensor data, then shares its information across the network using an algorithm that employs a distributed Cholesky modification. The decentralised solution permits each platform to act in the same modular manner, providing robustness to individual platform failure. The solution yields linear minimum mean-square error estimation performance. As such the estimates generated are optimal ; it generates exactly the same estimates as would a conventional extended Kalman filter, if given the same data. Efficient sparse implementation is accomplished without resorting to approximate methods. Simulation experiments employing a team of ten mobile platforms are described and used to evaluate the decentralised estimation performance. The robustness, flexibility and cost of the decentralised approach are analyzed and compared to an existing distributed solution.
We present the implementation and demonstration of a team of two fixed-wing Unmanned Aerial Vehicles whose task is to improve the localization accuracy of a number of ground-based features. The underlying algorithmic paradigm is based on over a decade's worth of work on Decentralized Data Fusion and Control. We present the components of the architecture, including vehicle localization, feature tracking, path planning and cooperative control. The algorithms described are implemented on a complete Unmanned Aerial System. Three demonstrations were performed, with varying levels of cooperation between team members. We present the results of these demonstrations and compare the performance of the team in completing the mission along with a quantitative understanding of the benefits achieved.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.