J Phys Conf S 1011(1):012049ĭelPreto J, Rus D (2020) Plug-and-play gesture control using muscle and motion sensors. Malik H, Darma S, Soekirno S (2018) Quadcopter control using speech recognition. International conference on data intelligence and security (ICDIS) Natarajan K, Nguyen T-HD, Mete M (2018) Hand gesture controlled drones: An open source library. Inst Cont Rob Syst 1291–1294ĭji the future of possible, Dec 2017, Comparison study of potential workload index in a simulated multiple-UAV operation environment. Zimmer D, Rhodes D (2006) Human–machine interfaces. As a result, we expect that the people who have no experience in operating UAVs can operate the UAV with HMI control system using speech and gesture recognition in the simulation. The entire process is simulated using ROS Melodic and gazebo9 in Ubuntu 18.04 environments. Based on our UAV Control System with HMI, we can identify which sensors and which commands are Operator-friendly. In this paper, we have designed a prototype of an Operator-friendly Control System with HMI (Human Machine Interface) capable of simple speech and gesture commands, and proceed with the SITL. Finally, we develop modules to process these commands and do the SITL (Simulation In The Loop). Second, the commands are adopted according to the divided UAV operation steps. First of all, to select speech and gesture commands, we analyze the UAV operation procedure and divided step by step. We have implemented speech recognition techniques using PyAudio and SpeechRecognition, speech recognition open-source libraries, and gesture recognition techniques using YOLOv3, an object-detecting open-source library. We have developed the UAV control system with speech recognition, which is used for AI speakers that are easily seen around us, and gesture recognition, which is used for motion recognition cameras like KINECT, based on the existing control systems. IEEE Indus Appl Mag 12:29–35) that reduces the operator's controlling stress and does not require high-level control capabilities. Therefore, it is necessary to develop an operator-friendly control system with HMI (Human Machine Interface) (Zimmer D, Rhodes D (2006) Human–machine interfaces. Especially in emergency situations, simultaneous work can be very burdensome because the ability to respond quickly is required. For beginners, it may be difficult not only to control UAV, but also to handle other tasks such as manipulating a gimbal-camera or starting/pausing missions at the same time as UAV operations. In manual flight, considerable proficiency is required for UAV control, which increases the control fatigue of novice operators. However, these conventional UAV control methods take a long time for beginners to get used to it. Traditional methods of UAV control include manual flight using twin-stick controllers or automatic flight by uploading Waypoint-based missions to the FC (Flight Controller) in advance using GCS (Ground Control System) software. As a result, the number of beginners in UAV control is also increasing. UAVs (Unmanned Aerial Vehicles) and drones have been used in various fields such as delivery of goods, fire suppression, and traffic monitoring.
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