TY - GEN
T1 - A Proactive Approach to Resistant UAV Mission Planning
AU - Radzki, Grzegorz
AU - Nielsen, Peter
AU - Bocewicz, Grzegorz
AU - Banaszak, Zbigniew
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Proactive mission planning for a fleet of Unmanned Aerial Vehicles (UAVs) can be seen as a sequence of routing problems mathematically formalized as 0-1 knapsack problems. Taking into account the fact that weather conditions change during a mission, the time horizon of the planned mission is subdivided into time windows corresponding to periods of stable weather. Also, keeping in mind fuel constraints, each knapsack problem is formulated as follows: Given is the fleet size and a set of spatially dispersed target points specified by the volume of expected deliveries and the coordinates of their location, which allow to determine the amount of fuel consumed during flight along a particular route segment/from one drop-off point to another. Determine a subset of locations so that the total fuel required to cover the total distance traveled by the UAV fleet is less than or equal to the given limit e.g. determined by battery capacity, and the total volume of deliveries is as large as possible. In this context, policies aimed at minimizing the total travel time and/or the total distance traveled are considered. Some potential directions of future research on resistant UAV mission planning are discussed.
AB - Proactive mission planning for a fleet of Unmanned Aerial Vehicles (UAVs) can be seen as a sequence of routing problems mathematically formalized as 0-1 knapsack problems. Taking into account the fact that weather conditions change during a mission, the time horizon of the planned mission is subdivided into time windows corresponding to periods of stable weather. Also, keeping in mind fuel constraints, each knapsack problem is formulated as follows: Given is the fleet size and a set of spatially dispersed target points specified by the volume of expected deliveries and the coordinates of their location, which allow to determine the amount of fuel consumed during flight along a particular route segment/from one drop-off point to another. Determine a subset of locations so that the total fuel required to cover the total distance traveled by the UAV fleet is less than or equal to the given limit e.g. determined by battery capacity, and the total volume of deliveries is as large as possible. In this context, policies aimed at minimizing the total travel time and/or the total distance traveled are considered. Some potential directions of future research on resistant UAV mission planning are discussed.
KW - UAV mission planning
KW - Weather-resistant planning
UR - http://www.scopus.com/inward/record.url?scp=85082997549&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-40971-5_11
DO - 10.1007/978-3-030-40971-5_11
M3 - Article in proceeding
AN - SCOPUS:85082997549
SN - 9783030409708
T3 - Advances in Intelligent Systems and Computing
SP - 112
EP - 124
BT - Automation 2020
A2 - Szewczyk, Roman
A2 - Zielinski, Cezary
A2 - Kaliczynska, Malgorzata
PB - Springer VS
T2 - International Conference on Automation, AUTOMATION 2020
Y2 - 18 March 2020 through 20 March 2020
ER -