2 research outputs found
DroneLight: Drone Draws in the Air using Long Exposure Light Painting and ML
We propose a novel human-drone interaction paradigm where a user directly
interacts with a drone to light-paint predefined patterns or letters through
hand gestures. The user wears a glove which is equipped with an IMU sensor to
draw letters or patterns in the midair. The developed ML algorithm detects the
drawn pattern and the drone light-paints each pattern in midair in the real
time. The proposed classification model correctly predicts all of the input
gestures. The DroneLight system can be applied in drone shows, advertisements,
distant communication through text or pattern, rescue, and etc. To our
knowledge, it would be the world's first human-centric robotic system that
people can use to send messages based on light-painting over distant locations
(drone-based instant messaging). Another unique application of the system would
be the development of vision-driven rescue system that reads light-painting by
person who is in distress and triggers rescue alarm.Comment: Accepted to the 29th IEEE International Conference on Robot and Human
Interactive Communication (RO-MAN 2020), IEEE copyright, 5 pages, 7 figure
DronePick: Object Picking and Delivery Teleoperation with the Drone Controlled by a Wearable Tactile Display
We report on the teleoperation system DronePick which provides remote object
picking and delivery by a human-controlled quadcopter. The main novelty of the
proposed system is that the human user continuously gets the visual and haptic
feedback for accurate teleoperation. DronePick consists of a quadcopter
equipped with a magnetic grabber, a tactile glove with finger motion tracking
sensor, hand tracking system, and the Virtual Reality (VR) application. The
human operator teleoperates the quadcopter by changing the position of the
hand. The proposed vibrotactile patterns representing the location of the
remote object relative to the quadcopter are delivered to the glove. It helps
the operator to determine when the quadcopter is right above the object. When
the "pick" command is sent by clasping the hand in the glove, the quadcopter
decreases its altitude and the magnetic grabber attaches the target object. The
whole scenario is in parallel simulated in VR. The air flow from the quadcopter
and the relative positions of VR objects help the operator to determine the
exact position of the delivered object to be picked. The experiments showed
that the vibrotactile patterns were recognized by the users at the high
recognition rates: the average 99% recognition rate and the average 2.36s
recognition time. The real-life implementation of DronePick featuring object
picking and delivering to the human was developed and tested.Comment: Accepted to the 28th IEEE International Conference on Robot and Human
Interactive Communication (RO-MAN 2019), IEEE copyright, 6 pages, 6 figures,
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