Description: The proposed novel program will develop and demonstrate an innovative approach to perform real-time relative vehicle localization within a swarm formation with application to communication-less coordination. These objectives are achieved by using Random Finite Sets statistics theory to solve the multiple object tracking problem. The swarm formation localization problem can be formulated as estimating the local intensity function of targets in the near field and developing probabilistic control strategies to track an expected localization state space configuration. Work will focus on refining estimation and control algorithms that can utilize simple measurements, such as range and bearing angle between units, and determine the local environment using feature measurements. Four major tasks are proposed for the development of swarming space vehicle estimation and control: Random Finite Set Localization and Control Theory and Algorithms, Swarm Scenario Implementations, Swarm Design Control and Simulate Toolset, and Swarm Localization and Control Demonstrations. Algorithms developed and analyzed in Phase I will be extended to a wide range of environmental models and swarm vehicle dynamics, including planetary rovers and orbiting spacecraft. The swarm technology will be implemented for real-time integrated system use, with identification of different formation configurations and sensor combination for hardware integration. A swarm design software tool will be created to allow users to utilize the developed technology in proposed mission analysis. Demonstrations of the benefits of the technology will be presented in software and hardware demonstrations, including small mobile robots used to emulate large swarms. Future demonstration missions identified in the Phase II will show the mission enhancements of the operational system.

Benefits: NASA applications consist of enabling autonomous precision swarm coordination for satellites traveling in Earth orbit or eventually into deep space, including significantly improved precision for multi-vehicle control. The produced swarm formation coordination and control algorithms and software will provide expanded mission planning and analysis capabilities, reduction of communication requirements, and decrease of mission risk. These concepts can equally support a wide range of applications, including small numbered teams and large-element swarms, and can operate during the normal birth and death rates anticipated for homogenous and heterogeneous swarms containing many elements. The system offers significant value in providing or augmenting current navigation and control techniques, as well as reducing support costs and system station-keeping down-time. The system offers precise formation control for assisting multiple spacecraft formation flying anywhere in the solar system, with limited mission control intervention after primary objectives are defined. The proposed system benefits autonomous planetary rover swarms, asteroid and comet exploration, Earth and planetary body orbiting swarms, and unmanned inspection of spacecraft.

Non-NASA applications for this technology include increased coordination and control for units of multiple unmanned aerial systems performing search and rescue operations and disaster relief for the Department of Homeland Security and other government agencies or local municipalities. Robotic or autonomous land, sea, and air vehicle coordination for the Department of Defense, and reduction of communication and relay requirements is an added application. Remote sensing systems, including agronomy and geological surveying applications, will use multiple vehicles for coordinated observations, which these multi-element swarm technologies can significantly aid. Commercial telecommunication satellite providers that desire to transmit large data rate information between multiple vehicles, such as imaging or internet-like inter-satellite networks, could realize the formation control benefits through this enabling technology. Tracking and localizing for medical-based concepts, such as embedded medical agents.