TY - GEN
T1 - Design of Drone Remote-Control System using Human Motion Recognition
AU - Chen, Shyh Wei
AU - Lai, Yu Chun
AU - Liu, Chia Hui
AU - Kuo, Chin Guo
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - At present, the most common and low-cost method to control the drone is to use a mobile phone with an APP. The operator takes his mobile phone screen as a human-machine interface, and at the same time controls and receives the images returned by the drone. The control mode can be divided into two symmetry modes according to how the operator views and knows the location of the drone: exocentric viewing and egocentric viewing mode. In the exocentric viewing mode, the operator directly visually confirms the position of the drone, while in the egocentric viewing mode, the drone is equipped with a camera and transmits the flight image to the operator in real-time. Since the drone cannot be far away from the operator in the exocentric viewing mode, the relative egocentric mode allows the operator to feel immersed in the environment to control the drone more accurately. Therefore, by adapting the egocentric viewing and using human motion recognition, an unmanned vehicle remote-control system is designed. The low-speed, small-scaled, nature-stability UAVs are ideally suited for the proposed system. The system was designed with a PID controller to improve the UAV's handling. The experimental results verified the feasibility of the UVA control system and it could stabilize the posture of the drone.
AB - At present, the most common and low-cost method to control the drone is to use a mobile phone with an APP. The operator takes his mobile phone screen as a human-machine interface, and at the same time controls and receives the images returned by the drone. The control mode can be divided into two symmetry modes according to how the operator views and knows the location of the drone: exocentric viewing and egocentric viewing mode. In the exocentric viewing mode, the operator directly visually confirms the position of the drone, while in the egocentric viewing mode, the drone is equipped with a camera and transmits the flight image to the operator in real-time. Since the drone cannot be far away from the operator in the exocentric viewing mode, the relative egocentric mode allows the operator to feel immersed in the environment to control the drone more accurately. Therefore, by adapting the egocentric viewing and using human motion recognition, an unmanned vehicle remote-control system is designed. The low-speed, small-scaled, nature-stability UAVs are ideally suited for the proposed system. The system was designed with a PID controller to improve the UAV's handling. The experimental results verified the feasibility of the UVA control system and it could stabilize the posture of the drone.
KW - Human motion recognition
KW - PID controller
KW - Remote-control system
KW - Unmanned aerial vehicle
UR - http://www.scopus.com/inward/record.url?scp=85136148810&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85136148810&partnerID=8YFLogxK
U2 - 10.1109/ECEI53102.2022.9829453
DO - 10.1109/ECEI53102.2022.9829453
M3 - Conference contribution
AN - SCOPUS:85136148810
T3 - 5th IEEE Eurasian Conference on Educational Innovation 2022, ECEI 2022
SP - 148
EP - 151
BT - 5th IEEE Eurasian Conference on Educational Innovation 2022, ECEI 2022
A2 - Meen, Teen-Hang
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE Eurasian Conference on Educational Innovation, ECEI 2022
Y2 - 10 February 2022 through 12 February 2022
ER -