An energy-aware drone trajectory planning scheme for terrestrial sensors localization

Sahar Kouroshnezhad, Ali Peiravi*, Mohammad Sayad Haghighi, Alireza Jolfaei

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


Employing GPS-equipped drones to act as mobile anchors is a popular solution for terrestrial sensors positioning in a generic environment. Researchers have proposed several approaches, usually to reduce estimated locations error and increase localization coverage, though no efficient solution has been presented for energy conservation of the drone. Drones, such as the commercial quadcopters, have limited power supply and cannot fly long. Any localization algorithm should consider the energy constraints beside the performance indicators. Furthermore, there is no suggested strategy to mitigate the error of Received Signal Strength (RSS)-based distance measurements in the existing solutions. In this paper, we propose a novel scheme to plan the drone trajectory, called the “Weighted Energy-aware Trajectory with Adaptive Radius (WETAR)”. The proposed scheme employs Linear Programming (LP) for trajectory planning in the presence of the sensors with given estimative regions which are acquired in a range-free pre-localization phase. It also specifies candidate waypoints, which are the projection of aerial anchor points on the ground, and assign weights to them based on two criteria: quality of the beacons that the sensors would receive and their coverage ratio. We assume that sensors utilize a range-based localization algorithm on the basis of RSS measurements. Simulation results show that the WETAR as an aerial anchor guiding mechanism, guides the drone effectively and reduces localization time, saves the drone energy, and improves the location error as well as the localization coverage.

Original languageEnglish
Pages (from-to)542-550
Number of pages9
JournalComputer Communications
Publication statusPublished - 15 Mar 2020


  • Drone
  • Energy efficiency
  • Range-based localization
  • RSS measurement
  • Sensor networks
  • Terrestrial sensors
  • Trajectory planning


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