Many recent advances in autonomy are derived from algorithm optimization and analysis with a large volume of data. The Autonomous Mobility Through Intelligent Collaboration (AMIC) program established a resource to host and access data to accelerate autonomy capability development across the U.S. Army Robotics and Autonomous Systems enterprise. The repository is seeded with high-quality multi-modal Autonomous Ground Vehicle sensor data collected from relevant operating environments. Development of unmanned air-ground teaming capability that extends the perception and planning horizon of an individual ground vehicle exercises and informs the development of the data warehouse. Collected data was also used to train a convolutional neural network to estimate relative vehicle position from camera images for communication-free formation control.