Optimal Deployment of Charging Stations for Aerial Surveillance by UAVs with the Assistance of Public Transportation Vehicles

Huang, Hailong; Savkin, Andrey V.

doi:10.3390/s21165320

Cited by 8 publications

(7 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The simulations are carried out on both triangular and square grid configurations by considering small scale datasets (less than 1000 vertices). These datasets consist of different numbers (20,40,60,80, and 100 boats) of randomly generated boats for rescuing. For each simulation, we considered pathfinding with redGreySP heuristic and pathfinding only with a grey edge.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Heuristic Drone Pathfinding Over Optimized Charging Station Grid

Kilic¹,

Mostarda²

2021

IEEE Access

View full text Add to dashboard Cite

We proposed a novel optimisation framework for drone-based operations which consists of the optimised Charging Station (CS) grid and the pathfinding heuristics for the drone. The proposed pathfinding heuristics are assessed for two different (triangular and square) CS grid configurations that are optimised for the drone range. We presented the case study of a boat rescue operation that is carried out in the sea. The minimisation of the "flight distance" and "number of chargings" are the objectives for the drone party and the minimisation of the "average waiting distance" (AWD) is the objective for the boat party. We studied the "single drone with many entities" case which is a form of Travelling Salesman Problem (TSP). We presented mathematical analysis and simulation results for the effectiveness of the pathfinding heuristic which we called the "red-grey path" heuristic. A novel and fast TSP heuristic was also proposed as part of the pathfinding heuristics and its performance was assessed.

show abstract

Section: Resultsmentioning

confidence: 99%

“…The problem of optimally deploying CSs is studied in [19,20]. These studies proposed adjustable CS deployment strategies.…”

Section: Related Workmentioning

confidence: 99%

Heuristic Drone Pathfinding Over Optimized Charging Station Grid

Kilic¹,

Mostarda²

2021

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Another solution in the charging station placement is provided in. 17 The authors present a deployment problem and a proposal of a sub-optimal solution proving the effectiveness of their solution through simulation experiments.…”

Section: Energy Issue In Uavmentioning

confidence: 99%

A green smart station design for a UAV fleet management in precision agriculture

Samaniego Campoverde,

Ganapaza

2024

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IX

View full text Add to dashboard Cite

In recent years, there has been significant interest from the scientific community in the fields of precision agriculture assisted through the use of Unmanned Aerial Vehicles (UAVs). This paper introduces a novel system that addresses the challenge of charging station issues in a UAV network. It proposes a system based on a master/slave model where there is a master station connected to different slave stations that use a lightweight application protocol, such as MQTT, for communicating with each other. Specifically, the paper proposes a smart station design aimed at effectively managing UAV fleets by task allocation and activity scheduling. In this way, the fleet of UAVs can recharge the batteries during the mission guaranteeing the completition of the performed task and facilitating an on-demand energy supply to the UAVs that need recharging during the mission.

show abstract

“…The target surveillance problem based on drones mainly focuses on targets on the ground, and a corresponding heuristic algorithm is proposed [13]. Huang et al [14,15] studied the collaboration with public transportation vehicles (PTVs) and the deployment of charging stations for aerial surveillance by UAVs, and proposed an iterative algorithm to optimize the locations of the charging stations. Yang et al [16] studied the routing problem of multiple drones traveling to multiple targets by using a particle swarm optimization algorithm.…”

Section: Related Workmentioning

confidence: 99%

Cooperatively Routing a Truck and Multiple Drones for Target Surveillance

Tian

Wen

Wei

et al. 2022

Sensors

View full text Add to dashboard Cite

With the development of drone technology, drones have been deployed in civilian and military fields for target surveillance. As the endurance of drones is limited, large-scale target surveillance missions encounter some challenges. Based on this motivation, we proposed a new target surveillance mode via the cooperation of a truck and multiple drones, which enlarges the range of surveillance. This new mode aims to rationally plan the routes of trucks and drones and minimize the total cost. In this mode, the truck, which carries multiple drones, departs from its base, launches small drones along the way, surveils multiple targets, recycles all drones and returns to the base. When a drone is launched from the truck, it surveils multiple targets and flies back to the truck for recycling, and the energy consumption model of the drone is taken into account. To assist the new problem-solving, we developed a new heuristic method, namely, adaptive simulated annealing with large-scale neighborhoods, to optimize truck and drone routes, where a scoring strategy is designed to dynamically adjust the selection weight of destroy operators and repair operators. Additionally, extensive experiments are conducted on several synthetic cases and one real case. The experimental results show that the proposed algorithm can effectively solve the large-scale target surveillance problem. Furthermore, the proposed cooperation of truck and drone mode brings new ideas and solutions to targets surveillance problems.

show abstract

Optimal Deployment of Charging Stations for Aerial Surveillance by UAVs with the Assistance of Public Transportation Vehicles

Cited by 8 publications

References 39 publications

Heuristic Drone Pathfinding Over Optimized Charging Station Grid

Heuristic Drone Pathfinding Over Optimized Charging Station Grid

A green smart station design for a UAV fleet management in precision agriculture

Cooperatively Routing a Truck and Multiple Drones for Target Surveillance

Contact Info

Product

Resources

About