Drones are becoming increasingly popular in the commercial market for various package delivery services. In this scenario, the mostly adopted drones are quad-rotors (i.e., quadcopters). The energy consumed by a drone may become an issue, since it may affect (i) the delivery deadline (quality of service), (ii) the number of packages that can be delivered (throughput) and (iii) the battery lifetime (number of recharging cycles). It is thus fundamental try to find the proper compromise between the energy used to complete the delivery and the speed at which the quadcopter flies to reach the destination. In order to achieve this, we have to consider that the energy required by the drone for completing a given delivery task does not exactly correspond to the energy requested to the battery, since the latter is a non-ideal power supply that is able to deliver power with different efficiencies depending on its state of charge. In this paper, we demonstrate that the proposed battery-aware delivery scheduling algorithm carries more packages than the traditional delivery model with the same battery capacity. Moreover, the battery-aware delivery model is 17% more accurate than the traditional delivery model for the same delivery scheme, which prevents the unexpected drone landing.
Battery-aware energy model of drone delivery tasks / Baek, Donkyu; Chen, Yukai; Bocca, Alberto; Macii, Alberto; Macii, Enrico; Poncino, Massimo. - ELETTRONICO. - 49:(2018), pp. 1-6. (Intervento presentato al convegno 2018 International Symposium on Low Power Electronics and Design tenutosi a Seattle, WA, USA nel July 23 - 25, 2018) [10.1145/3218603.3218614].
Battery-aware energy model of drone delivery tasks
BAEK, DONKYU;CHEN, YUKAI;Bocca Alberto;Macii Alberto;Macii Enrico;Poncino Massimo
2018
Abstract
Drones are becoming increasingly popular in the commercial market for various package delivery services. In this scenario, the mostly adopted drones are quad-rotors (i.e., quadcopters). The energy consumed by a drone may become an issue, since it may affect (i) the delivery deadline (quality of service), (ii) the number of packages that can be delivered (throughput) and (iii) the battery lifetime (number of recharging cycles). It is thus fundamental try to find the proper compromise between the energy used to complete the delivery and the speed at which the quadcopter flies to reach the destination. In order to achieve this, we have to consider that the energy required by the drone for completing a given delivery task does not exactly correspond to the energy requested to the battery, since the latter is a non-ideal power supply that is able to deliver power with different efficiencies depending on its state of charge. In this paper, we demonstrate that the proposed battery-aware delivery scheduling algorithm carries more packages than the traditional delivery model with the same battery capacity. Moreover, the battery-aware delivery model is 17% more accurate than the traditional delivery model for the same delivery scheme, which prevents the unexpected drone landing.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2713802