TY - GEN
T1 - Multi-region coverage path planning for heterogeneous unmanned aerial vehicles systems
AU - Chen, Jinchao
AU - Du, Chenglie
AU - Lu, Xu
AU - Chen, Keke
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5/3
Y1 - 2019/5/3
N2 - Recently unmanned aerial vehicles (UAVs) have been widely adopted by military and civilian applications due to their strong autonomies and adaptabilities. Although UAVs can achieve effective cost reduction and flexibility enhancement in the development of systems with search or surveillance missions, they result in a complex path planning problem. Especially in region coverage systems, coverage path planning problem, which seeks a path that covers all regions of interest, has a NP-Hard computational complexity and is difficult to solve. In this paper, we study the coverage path planning problem for heterogeneous UAVs in multiple region systems. First, with the models of UAVs and regions, an exact formulation based on mixed integer linear programming is presented to produce an optimal coverage path. Then taking into account both the scanning time on regions and the flight time between regions, an efficient heuristic is proposed to assign regions and to obtain coverage orders for UAVs. Finally, experiments are conducted to show the reliability and efficiency of the proposed heuristic from several aspects.
AB - Recently unmanned aerial vehicles (UAVs) have been widely adopted by military and civilian applications due to their strong autonomies and adaptabilities. Although UAVs can achieve effective cost reduction and flexibility enhancement in the development of systems with search or surveillance missions, they result in a complex path planning problem. Especially in region coverage systems, coverage path planning problem, which seeks a path that covers all regions of interest, has a NP-Hard computational complexity and is difficult to solve. In this paper, we study the coverage path planning problem for heterogeneous UAVs in multiple region systems. First, with the models of UAVs and regions, an exact formulation based on mixed integer linear programming is presented to produce an optimal coverage path. Then taking into account both the scanning time on regions and the flight time between regions, an efficient heuristic is proposed to assign regions and to obtain coverage orders for UAVs. Finally, experiments are conducted to show the reliability and efficiency of the proposed heuristic from several aspects.
KW - Coverage order
KW - Coverage path planning
KW - Region coverage
KW - Unmanned aerial vehicle
UR - http://www.scopus.com/inward/record.url?scp=85065998445&partnerID=8YFLogxK
U2 - 10.1109/SOSE.2019.00060
DO - 10.1109/SOSE.2019.00060
M3 - 会议稿件
AN - SCOPUS:85065998445
T3 - Proceedings - 13th IEEE International Conference on Service-Oriented System Engineering, SOSE 2019, 10th International Workshop on Joint Cloud Computing, JCC 2019 and 2019 IEEE International Workshop on Cloud Computing in Robotic Systems, CCRS 2019
SP - 356
EP - 361
BT - Proceedings - 13th IEEE International Conference on Service-Oriented System Engineering, SOSE 2019, 10th International Workshop on Joint Cloud Computing, JCC 2019 and 2019 IEEE International Workshop on Cloud Computing in Robotic Systems, CCRS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th IEEE International Conference on Service-Oriented System Engineering, SOSE 2019, 10th International Workshop on Joint Cloud Computing, JCC 2019 and 2019 IEEE International Workshop on Cloud Computing in Robotic Systems, CCRS 2019
Y2 - 4 April 2019 through 9 April 2019
ER -