Abstract: | Small Unmanned Aircraft Systems (sUAS) such as multicopters are proving to be increasingly favorable in commercial applications. The range of applications include surveillance, aerial photography, environmental observations, search and rescue, mapping, forestry / agricultural survey, law enforcement among many. Small size unmanned multi-copters are highly capable and cost effective for low altitude operations and have extended access to dangerous and hazardous environments that were previously unavailable. Irrespective of their applications, a reliable navigation capability is necessary to fly the sUAS autonomously, semi-autonomously or manually. The Global Navigation Satellite System (GNSS) has become one of the most dependable solutions navigation outdoors but does not perform well in the indoor environment as the signals are obstructed by the building’s structure (e.g., roof and the walls). Hence, there is a need for non-GNSS indoor navigation methods. Simultaneous Localization and Mapping (SLAM) and feature-based integrated navigation are two approaches that can be considered for this purpose using a wide variety of sensors like ranging sensors, cameras, and inertial measurement units (IMU). This paper will focus on integrating depth imagery and LWIR imagery with an IMU to obtain and estimate of both the position and the map of the environment. In this discussion, the region of operation is restricted to structured environments and will be extended to unstructured environments in the future. The paper will include preliminary flight test results from a small-size Blackout quadcopter operated in a structured indoor environment for maintenance purposes. The quadcopter has been equipped with a 3DR Pixhawk flight controller and an Odroid XU4 onboard computer running Ubuntu. The Robotics Operating System (ROS) is used to interface with and integrate all the sensors and control the flight controller. The optical sensors include a forward-pointing Occipital providing both short-wave infrared (SWIR) imagery and depth information and a Lepton LWIR camera to pick up heat signature image of objects in the environment. The latter is connected to the Odroid via an SPI interface. |
Published in: |
Proceedings of the ION 2017 Pacific PNT Meeting May 1 - 4, 2017 Marriott Waikiki Beach Resort & Spa Honolulu, Hawaii |
Pages: | 1065 - 1076 |
Cite this article: | Bharadwaj, Akshay S., de Haag, Maarten Uijt, "Keynote: Navigating Small-UAS in Tunnels for Maintenance and Surveillance Operations," Proceedings of the ION 2017 Pacific PNT Meeting, Honolulu, Hawaii, May 2017, pp. 1065-1076. https://doi.org/10.33012/2017.15020 |
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