Indoor localisation and mapping missions usually require several sensors to correctly calculate the position of the Unmanned Aerial Vehicle (UAV) within the space and detect and localize obstacles. This research paper presents the development of a mapping system for UAVs in unknown indoor environments resorting to ultrasonic sensors. The core of the system is the DJI Ryze Tello UAV, a small 80g Micro Air Vehicle (MAV) with very limited capabilities such as payload and available flight time. A distributed system was developed to ensure the successful execution of the mission without exceeding the capabilities of the MAV. A prototype was developed that consists of two hardware components, one integrated into the MAV and another in a teth-ered configuration. The operation of the system is independent of the environment and supports multiple simultaneous missions. An original autonomous flight and mapping algorithm was created, based on vertical motion patterns, to provide an efficient and effective mapping solution. Data processing procedures were also implemented to complement the initial framing of detected obstacles. The obtained system allows the digital reconstruction of the space. The mapped obstacle distances in the test environment have resulted in more than 90% of accuracy.
Lightweight Micro Aerial Vehicles (MAVs) Application for Indoor Environment Mapping using Ultrasonic Sensors
2023-07-23
6536718 byte
Conference paper
Electronic Resource
English
Design and optimization of Micro Aerial Vehicles.
Design and optimization of MAVs
DSpace@MIT | 2003
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