Autonomous Indoor Mapping and Modeling

This project aims to create the Autonomy and Visualization Enhancement for Situational Awareness (AVESA) toolkit. AVESA’s goal is to combine greater autonomy with accurate 3D mapping and visualization capabilities for use on Small Unmanned Ground Vehicles (SUGVs) in urban environments, providing significant benefits to the modern warfighter. Using AVESA, a soldier can command a SUGV to enter a structure, search it, and return to its original location. Upon completion of its mission, the 3D maps are transmitted to the soldiers, who are able to analyze the information prior to entering the structure, if required. Because of AVESA’s capabilities, each soldier knows the basic structural layout, greatly enhancing the team’s situational awareness. The research objectives of this project are to: Develop a video-based Simultaneous Localization and Mapping (SLAM) library for use on SUGV platforms in static, urban environments; Create a visualization toolkit that takes images as input and outputs texture-mapped 3D surfaces; Implement a software package capable of displaying the 3D surfaces created by AVESA; Work with the sponsor to integrate AVESA and open interfaces (e.g., Cursor on Target);Collect real test data using the pre-existing platforms.