2019/08/06 by Roman İbrahimov, Ibrahimov, Roman, Evgeny Tsykunov +7 · 1 citation
Computer Science · Engineering · Neuroscience · #FOS: Computer and information sciences #Gaze Tracking and Assistive Technology #Human-Computer Interaction (cs.HC) #Robotics (cs.RO) #Tactile and Sensory Interactions #Teleoperation and Haptic Systems
paper · pdf · doi:10.48550/arxiv.1908.02432
openalex publication_date 2019/08/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We report on the teleoperation system DronePick which provides remote object\npicking and delivery by a human-controlled quadcopter. The main novelty of the\nproposed system is that the human user continuously gets the visual and haptic\nfeedback for accurate teleoperation. DronePick consists of a quadcopter\nequipped with a magnetic grabber, a tactile glove with finger motion tracking\nsensor, hand tracking system, and the Virtual Reality (VR) application. The\nhuman operator teleoperates the quadcopter by changing the position of the\nhand. The proposed vibrotactile patterns representing the location of the\nremote object relative to the quadcopter are delivered to the glove. It helps\nthe operator to determine when the quadcopter is right above the object. When\nthe "pick" command is sent by clasping the hand in the glove, the quadcopter\ndecreases its altitude and the magnetic grabber attaches the target object. The\nwhole scenario is in parallel simulated in VR. The air flow from the quadcopter\nand the relative positions of VR objects help the operator to determine the\nexact position of the delivered object to be picked. The experiments showed\nthat the vibrotactile patterns were recognized by the users at the high\nrecognition rates: the average 99% recognition rate and the average 2.36s\nrecognition time. The real-life implementation of DronePick featuring object\npicking and delivering to the human was developed and tested.\n