TY - GEN
T1 - Autonomous mission completion system for disconnected delivery drones in urban area
AU - Chung, Albert Y.
AU - Lee, Joon Yeop
AU - Kim, Hwangnam
N1 - Funding Information:
The first two authors of the paper have contributed equally. This research was supported by Unmanned Vehicles Advanced Core Technology Research and Development Program through the Unmanned Vehicle Advanced Research Center (UVARC) funded by the Ministry of Science, ICT and Future Planning, the Republic of Korea (NRF-2016M1B3A1A01937599).
Publisher Copyright:
© 2017 IEEE.
PY - 2018/3/23
Y1 - 2018/3/23
N2 - Drone delivery system has been a popular research topic and various systems have been tested. However, in the case of providing direct service to human like a drones delivery, it should be able to cope with problems that may arise in a urban area where abundance of obstacles that can affect the communication ability of the drones. The nature of drone delivery system requires the drone to lower it's altitude for it to accomplish the given task. Such characteristic greatly increases the possibility to losing connection with the drone controlling entity in urban areas. Moreover, the autonomous flight is also affected by the deteriorated GPS localization due to the multi-path effect of GPS signals in "urban canyons". This paper presents a drone delivery system designed to complete a given task even when the communication between the drone and the controlling entity is disconnected in urban area. Further, the proposed system is based on image processing and does not get affected by the erroneous GPS signals. The proposed system consist of three modules: optic flow contour module, approaching object detector module, and return to line of control module. Optic flow contour is used to detect safe landing zone, approaching object detector is used to detect obstacles, and return to line of control is used takeoff and ascent the drone after completing the given task. Implementation of the system has been adopted to actual drone. The functionalities of the system have been evaluated thoroughly via experiments and the results are presented throughout the paper.
AB - Drone delivery system has been a popular research topic and various systems have been tested. However, in the case of providing direct service to human like a drones delivery, it should be able to cope with problems that may arise in a urban area where abundance of obstacles that can affect the communication ability of the drones. The nature of drone delivery system requires the drone to lower it's altitude for it to accomplish the given task. Such characteristic greatly increases the possibility to losing connection with the drone controlling entity in urban areas. Moreover, the autonomous flight is also affected by the deteriorated GPS localization due to the multi-path effect of GPS signals in "urban canyons". This paper presents a drone delivery system designed to complete a given task even when the communication between the drone and the controlling entity is disconnected in urban area. Further, the proposed system is based on image processing and does not get affected by the erroneous GPS signals. The proposed system consist of three modules: optic flow contour module, approaching object detector module, and return to line of control module. Optic flow contour is used to detect safe landing zone, approaching object detector is used to detect obstacles, and return to line of control is used takeoff and ascent the drone after completing the given task. Implementation of the system has been adopted to actual drone. The functionalities of the system have been evaluated thoroughly via experiments and the results are presented throughout the paper.
UR - http://www.scopus.com/inward/record.url?scp=85048188961&partnerID=8YFLogxK
U2 - 10.1109/ROBIO.2017.8324394
DO - 10.1109/ROBIO.2017.8324394
M3 - Conference contribution
AN - SCOPUS:85048188961
T3 - 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017
SP - 56
EP - 61
BT - 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017
Y2 - 5 December 2017 through 8 December 2017
ER -