TY - GEN
T1 - On the continuous coverage problem for a swarm of UAVs
AU - Shakhatreh, Hazim
AU - Khreishah, Abdallah
AU - Chakareski, Jacob
AU - Salameh, Haythem Bany
AU - Khalil, Issa
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/2/7
Y1 - 2017/2/7
N2 - Unmanned aerial vehicles (UAVs) can be used to provide wireless network and remote surveillance coverage for disaster-affected areas. During such a situation, the UAVs need to return periodically to a charging station for recharging, due to their limited battery capacity. We study the problem of minimizing the number of UAVs required for a continuous coverage of a given area, given the recharging requirement. We prove that this problem is NP-complete. Due to its intractability, we study partitioning the coverage graph into cycles that start at the charging station. We first characterize the minimum number of UAVs to cover such a cycle based on the charging time, the traveling time, and the number of subareas to be covered by the cycle. Based on this analysis, we then develop an efficient algorithm, the cycles with limited energy algorithm. The straightforward method to continuously cover a given area is to split it into N subareas and cover it by N cycles using N additional UAVs. Our simulation results examine the importance of critical system parameters: the energy capacity of the UAVs, the number of subareas in the covered area, and the UAV charging and traveling times. We demonstrate that the cycles with limited energy algorithm requires 69%-94% fewer additional UAVs relative to the straightforward method, as the energy capacity of the UAVs is increased, and 67%-71% fewer additional UAVs, as the number of subareas is increased.
AB - Unmanned aerial vehicles (UAVs) can be used to provide wireless network and remote surveillance coverage for disaster-affected areas. During such a situation, the UAVs need to return periodically to a charging station for recharging, due to their limited battery capacity. We study the problem of minimizing the number of UAVs required for a continuous coverage of a given area, given the recharging requirement. We prove that this problem is NP-complete. Due to its intractability, we study partitioning the coverage graph into cycles that start at the charging station. We first characterize the minimum number of UAVs to cover such a cycle based on the charging time, the traveling time, and the number of subareas to be covered by the cycle. Based on this analysis, we then develop an efficient algorithm, the cycles with limited energy algorithm. The straightforward method to continuously cover a given area is to split it into N subareas and cover it by N cycles using N additional UAVs. Our simulation results examine the importance of critical system parameters: the energy capacity of the UAVs, the number of subareas in the covered area, and the UAV charging and traveling times. We demonstrate that the cycles with limited energy algorithm requires 69%-94% fewer additional UAVs relative to the straightforward method, as the energy capacity of the UAVs is increased, and 67%-71% fewer additional UAVs, as the number of subareas is increased.
KW - Unmanned aerial vehicles
KW - charging
KW - continuous coverage
UR - http://www.scopus.com/inward/record.url?scp=85015186896&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85015186896&partnerID=8YFLogxK
U2 - 10.1109/SARNOF.2016.7846742
DO - 10.1109/SARNOF.2016.7846742
M3 - Conference contribution
AN - SCOPUS:85015186896
T3 - 37th IEEE Sarnoff Symposium, Sarnoff 2016
SP - 130
EP - 135
BT - 37th IEEE Sarnoff Symposium, Sarnoff 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 37th IEEE Sarnoff Symposium, Sarnoff 2016
Y2 - 19 September 2016 through 21 September 2016
ER -