Swarm of Unmanned Aerial Vehicles using Emergence (SUAVE) efficiently creates a map in GPS-denied locations using Simultaneous Localization and Mapping (SLAM). Each drone is outfitted with a Lidar and an Intel Realsense Camera, which will be used to develop a high-fidelity infrared 3D map of an area without the need for GPS. Upon completion of each flight, the point clouds made through photogrammetry on each drone will be recorded and fused, creating a map with higher precision and accuracy. The use of the swarm is to generate this map from multiple points of view so that shadow effects can be negated and a more populated, dense map can be produced in respect to one drone’s map. To address localization with no GPS, the onboard IMU suite will be used to track relative position, while the onboard camera will track the local position. These two forms of localization, when coupled, allow for autonomous flights in lieu of GPS localization. This manuscript demonstrates the differences between one, three, and five fused maps during autonomous test flights on an Unmanned Aerial System (UAS) with a lack of GPS.
ISAAC is a 3D-printed pneumatic spacecraft for attitude control system development in a 3-axis gimbal ring. This allows for simulated free-space movement of a cold gas thruster-controlled probe in a controlled test environment. The purpose of this open-sourced control platform is to allow students, professors, and researchers to test their control algorithms on real hardware in real-time. The end goal is to have a website allowing anyone to upload their code and watch it run via live stream. The spacecraft uses a pneumatic system to mimic cold gas thrusters by using compressed air as a means of propulsion. The delivery system uses solenoids to control the thrust, stabilizing the craft. The hardware is simple and consists of custom Arduino Printed Circuit Boards (PCB), a Raspberry Pi, an Inertial Measurement Unit (IMU) for total orientation data, and 2 LiPo batteries. The craft is entirely 3D printed, including the mounts for the components, to be accessible for future research and upgrades. The attitude controller will be integrated into the website easycontrols.org, which will allow anyone interested, both students and researchers alike, to upload their Python control algorithm and watch it run on hardware in real-time. The website will have built-in functions and examples, allowing the user to create their algorithm easily. A proof of concept of this system has been the application of a sliding mode controller in one axis of the gimbal rings. Future work can include the application of more modern control methods for students and facilities to display and follow.
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