Aerial Systems with Micro Sensors: Data Acquisition and Descriptive Reality in Physical and Virtual Environments

Swarm autonomy, coordination and surveillance capabilities for multi-mission multi-functional aerial systems depend on distributed control, sensing and data acquisition. Recently emerged multi-degree-of-freedom microelectronic and MEMS acoustic, electromagnetic, image and inertial sensors empower autonomy, perception of reality, computer vision, augmented reality, situational awareness and other mission-critical tasks. Open problems in system design, complexity and software-hardware co-design motivate authors to focus on fundamental studies and technology developments in sensing and information fusion. Networking and data fusion from multi-mode navigation and image sensors are studied. We examine control and autonomy capabilities emulating tasks and mission environments. The distributed algorithms empower individual-and swarm aerial systems. We report solutions developed in Python, C and MATLAB supporting data processing, data visualization, interactions, interfacing and physical-and-virtual reality. The descriptive reality and information management are demonstrated by performing low-fidelity studies for DJI Phantom with heterogeneous sensors. Augmentation of control and tactical autonomy are studied.