Comparing YOLOv3, YOLOv4 and YOLOv5 for Autonomous Landing Spot Detection in Faulty UAVs

In-flight system failure is one of the major safety concerns in the operation of unmanned aerial vehicles (UAVs) in urban environments. To address this concern, a safety framework consisting of following three main tasks can be utilized: (1) Monitoring health of the UAV and detecting failures, (2) Finding potential safe landing spots in case a critical failure is detected in step 1, and (3) Steering the UAV to a safe landing spot found in step 2. In this paper, we specifically look at the second task, where we investigate the feasibility of utilizing object detection methods to spot safe landing spots in case the UAV suffers an in-flight failure. Particularly, we investigate different versions of the YOLO objection detection method and compare their performances for the specific application of detecting a safe landing location for a UAV that has suffered an in-flight failure. We compare the performance of YOLOv3, YOLOv4, and YOLOv5l while training them by a large aerial image dataset called DOTA in a Personal Computer (PC) and also a Companion Computer (CC). We plan to use the chosen algorithm on a CC that can be attached to a UAV, and the PC is used to verify the trends that we see between the algorithms on the CC. We confirm the feasibility of utilizing these algorithms for effective emergency landing spot detection and report their accuracy and speed for that specific application. Our investigation also shows that the YOLOv5l algorithm outperforms YOLOv4 and YOLOv3 in terms of accuracy of detection while maintaining a slightly slower inference speed.

Emergency Landing Spot Detection Algorithm for Unmanned Aerial Vehicles

The use and research of Unmanned Aerial Vehicle (UAV) have been increasing over the years due to the applicability in several operations such as search and rescue, delivery, surveillance, and others. Considering the increased presence of these vehicles in the airspace, it becomes necessary to reflect on the safety issues or failures that the UAVs may have and the appropriate action. Moreover, in many missions, the vehicle will not return to its original location. If it fails to arrive at the landing spot, it needs to have the onboard capability to estimate the best area to safely land. This paper addresses the scenario of detecting a safe landing spot during operation. The algorithm classifies the incoming Light Detection and Ranging (LiDAR) data and store the location of suitable areas. The developed method analyses geometric features on point cloud data and detects potential right spots. The algorithm uses the Principal Component Analysis (PCA) to find planes in point cloud clusters. The areas that have a slope less than a threshold are considered potential landing spots. These spots are evaluated regarding ground and vehicle conditions such as the distance to the UAV, the presence of obstacles, the area’s roughness, and the spot’s slope. Finally, the output of the algorithm is the optimum spot to land and can vary during operation. The proposed approach evaluates the algorithm in simulated scenarios and an experimental dataset presenting suitability to be applied in real-time operations.

‘Cell Division’ and ‘O Positive’

‘Cell Division’: This poem is on process, on making as a human endeavour. Wrapped in terminology, language embodies placement where the body wants to land. As language creatures, humans attempt definition without including sensory episodes of navigation, cognitive disassociations of tripped-up aural sensation, i.e. what feels good, i.e. fun. The function of the imagination in language is to question its continual evolution ‐ to grow the 'not-here' from the Self. With purposeful misspellings of text-speak, yr for your, and asking the reader to pronounce hum with extra mmms ‐ the writer interlays mouth with media to reach past the moment of the poem, past the page, to the reader's eyes, skin and body lingo, to share in the process. Titled ‘Cell Division’, as tendrils of our collective unsettling, this poem looks at choice and mobility as concurrent quadrants in the act of doing.‘O Positive’: As the unfolding of each moment presents itself, the question becomes, how much to hold onto what passes by? This poem, in its restraint and jangled incompletion, uses rhythm and meter inside the sentence form, to look at how communication travels inside the syntax of grammar. The sound of the breath as it moves through the lines, connects to the human flow referenced in the title ‐ which then connects to the ending neologism infantic, itself, a landing spot without origin.