Autonomous Mobility Adv Tech
Abstract
This Project matures and demonstrates Artificial Intelligence and Machine Learning (AI/ML) technologies to increase autonomy and mobility to perform teamed operations with manned and unmanned air and ground vehicles in a military relevant environment through data collection on relevant platforms. Data collection will involve both simulation and live collection. Simulation will provide a baseline to correctly collect, clean, and analyze data that meets the need for improving algorithms for both formation control and unmanned aerial vehicle map input for unmanned ground vehicle mobility. Live data will start with Surrogate platforms in local areas. This will allow proper collection techniques, tools, and data to maximize embedded autonomy using Machine Learning and other Artificial Intelligent methods before utilizing live data collection. The Project will use AI/ML techniques to mature and demonstrate intelligent formation control to be used on maintained roads and in complex terrain without the need for GPS. Data will be collected from mounted platforms utilizing special internal and external sensors to improve algorithms for exact positioning, undistributed formation control, and increased speeds of unmanned platforms. Also, the Project will use AI/ML techniques to optimize intelligent autonomous ground platform planning through the use of Unmanned Aerial Systems (UAS) mapped areas. Data collected from air vehicle will be converted to maneuverable information for unmanned ground platform with the identification of enemy positions, go/no-go areas, terrain classification, and optimal suggested paths. The cited work is consistent with the Under Secretary of Defense for Research and Engineering priority focus areas and the Army Modernization Strategy . Work in this Project supports the Army Modernization Priority Next Generation Combat Vehicle. Work is performed by the United States (US) Army Futures Command. This Project is coordinated with PE 0602145A (Next Generation Combat Vehicle Technology).
Document Details
- Document Type
- Project
- Publication Date
- Oct 01, 2021
- Source ID
- BK1_0603462A_3_2040_PB_2021
Related Documents
- Root: Next Generation Combat Vehicle Advanced Technology
- Child Accomplishment: Machine Learning Data Collection
- Child Accomplishment: Formation Control
- Child Accomplishment: UAS Mapping
- Child Accomplishment: FY 2020 SBIR/STTR Transfer