Optimal Flight Plan Research Articles

Drone Stations-Aided Beyond-Battery-Lifetime Flight Planning for Parcel Delivery

This paper considers using drones to conduct the last-mile parcel delivery. To enable the beyond-battery-lifetime flight, drone stations are considered to replace or recharge the battery for drones. We focus on the flight planning problem with the goal of minimizing the total travel time from the depot to a customer, a key indicator of the quality of service. We investigate four typical ways for the drone to get extra energy at drone stations: 1) replacing the battery with a fresh one, 2) recharging the battery to the full capacity, 3) recharging the battery to the optimal level, and 4) recharging the battery to the optimal level accounting for the availability of drone stations (i.e., whether a drone station is occupied by other drones). While the first two scenarios can be formulated following the framework of integer linear programming, the last two scenarios turn into mixed-integer nonlinear programming problems. To address the later problems, we present a framework in which discretized state graphs are constructed first and then the optimal paths are found by graph searching algorithms. We propose a dynamic version of Dijkstra’s algorithm to deal with the unavailability issue of drone stations. The algorithm can quickly find the optimal flight path for a drone, and extensive computer-based experimental results have been presented to demonstrate the effectiveness of the proposed method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Multi-rotary unmanned aerial vehicles (UAVs), also known as drones, have been regarded as a promising means to reshape future logistics. To save human labour and reduce cost, many giant logistics companies have been dedicated to developing various drones to deliver light and small parcels during the past decade. However, due to the limitation of payload, the battery capacity is constrained, which prevents drones from long-distance flights. Practitioners have tried the drone-vehicle collaboration method, but this still requires human labour to participate. In this paper, we present a framework where drones autonomously conduct long-distance delivery with the assistance of drone stations. It is worth pointing out that such a framework is not to replace the ground delivery method but to serve as an alternative to the ground counterpart for small and light parcels. A particular focus is on the flight planning from the depot to a destination, which includes not only a sequence of drone stations to stop at but also the corresponding rest time to recharge the battery. Several typical scenarios about battery recharging are discussed, and a dynamic version of Dijkstra’s algorithm is presented to deal with the challenging case where drone station resources are limited. The presented approach is able to find out the optimal flight plan quickly.

Collaborative slot secondary allocation based on flight wave operation

PurposeFlights are often delayed owing to emergencies. This paper proposes a cooperative slot secondary assignment (CSSA) model based on a collaborative decision-making (CDM) mechanism, and the operation mode of flight waves designs an improved intelligent algorithm to solve the optimal flight plan and minimize the total delay of passenger time.Design/methodology/approachTaking passenger delays, transfer delays and flight cancellation delays into account comprehensively, the total delay time is minimized as the objective function. The model is verified by a linear solver and compared with the first come first service (FCFS) method to prove the effectiveness of the method. An improved adaptive partheno-genetic algorithm (IAPGA) using hierarchical serial number coding was designed, combining elite and roulette strategies to find pareto solutions.FindingsComparing and analyzing the experimental results of various scale examples, the optimization model in this paper is greatly optimized compared to the FCFS method in terms of total delay time, and the IAPGA algorithm is better than the algorithm before in terms of solution performance and solution set quality.Originality/valueBased on the actual situation, this paper considers the operation mode of flight waves. In addition, the flight plan solved by the model can be guaranteed in terms of feasibility and effectiveness, which can provide airlines with reasonable decision-making opinions when reassigning slot resources.

Sensitivity analysis of unmanned aerial vehicle-borne 3D point cloud reconstruction from infrared images

Structural aging or inefficient design affects the energy efficiency of buildings in the United States. Infrared thermography (IRT) in conjunction with unmanned aerial vehicle (UAV) followed by point cloud (PC) reconstruction can be used to generate renderings of structures that highlight areas of excessive heat loss. This work represents the first effort to standardize the procedures for developing a structure from motion (SfM) approach by using only IR images to generate three-dimensional (3D) PC models (i.e., renderings) that can be used to determine from where heat is lost in a structure. Additionally, the appropriate image acquisition parameters are poorly understood and are investigated within this paper to improve the reconstruction of infrared-based point clouds (IR-PCs) for buildings. In particular, the sensitivity of the IR-PC approach for reconstructing 3D models and its accuracy to detect heat loss is quantified as a function of the i) temperature difference between the targeted structure and its surroundings, ii) IR images' overlap, and iii) IR camera's orientation. Results of tests performed to demonstrate that the IR-PC allows reconstructing virtual models of the targeted systems with geometrical accuracy of about 2 cm and for temperature differences as low as 1.3 °C. Overall, this research defines a standard for using only IR images to reconstruct 3D PCs that can be used to detect heat loss by determining the optimal image acquisition and flight plan parameters. This framework can find applications for structural assessment and building inspection but also make energy efficiency assessments more precise and much more widespread than they currently are.

An integrated optimum 3D transition orbit design procedure with guidance for a spacecraft

In this paper, an integrated optimal flight plan with a guidance plan in a general transfer orbit is considered. Due to the need to simultaneously reduce energy consumption and flight time in some space missions, the spacecraft trajectory is optimized based on two criteria to minimize fuel consumption and flight time in the orbital transfer process. For this purpose, the total velocity impulse on both sides of the transition orbit and the elapsed time are defined as the criteria of the objective function which includes the spacecraft’s insertion conditions and orbital parameters related to the shape of the trajectory. The optimal transition (coasting) trajectory is then obtained using the multi-objective genetic algorithm (MOGA) search method. Subsequently, the velocity-to-be-gained guidance steering scheme is integrated to track the trajectory onboard and reach the final orbit. The numerical results of the proposed algorithm are extracted in three case studies and compared with other references that show its ability to find the optimal transfer.

New flight plan optimisation method utilising a set of alternative final point arrival time targets (RTA constraints)

AbstractThis study investigates a new aircraft flight trajectory optimisation method, derived from the Non-dominated Sorting Genetic Algorithm II method used for multi-objective optimisations. The new method determines, in parallel, a set of optimal flight plan solutions for a flight. Each solution is optimal (requires minimum fuel) for a Required Time of Arrival constraint from a set of candidate time constraints selected for the final waypoint of the flight section under optimisation. The set of candidate time constraints is chosen so that their bounds are contiguous, i.e. they completely cover a selected time domain. The proposed flight trajectory optimisation method may be applied in future operational paradigms, such as Trajectory-Based Operations/free flight, where aircraft do not need to follow predetermined routes. The intended application of the proposed method is to support Decision Makers in the planning phase when there is a time constraint or a preferred crossing time at the final point of the flight section under optimisation. The Decision Makers can select, from the set of optimal flight plans, the one that best fits their criteria (minimum fuel burn or observes a selected time constraint). If the Air Traffic Management system rejects the flight plan, then they can choose the next best solution from the set without having to perform another optimisation. The method applies for optimisations performed on lateral and/or vertical flight plan components. Seven proposed method variants were evaluated, and ten test runs were performed for each variant. For five variants, the worst results yielded a fuel burn less than 90kg (0.14%) over the ‘global’ optimum. The worst variant yielded a maximum of 321kg (0.56%) over the ‘global’ optimum.

Models for Drone Go Aerial Disaster Relief Response System

&lt;p&gt;&lt;em&gt;According to the requirement, we established a non-linear programming model and a three-dimensional packing model and designed a Drone&lt;/em&gt;&lt;em&gt; &lt;/em&gt;&lt;em&gt;Go disaster response system meeting the demand of medical supplement and road video reconnaissance. We also determine the optimal location selection, container assembly schemes, as well as the UAV flight routes and flight plans. &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;First of all, we established a coordinate system to fit the topographic map of Puerto Rico through the digital image processing method and collect the road pixels in the topographic map. Then compared it with the detection range of the UAVs to analyze the exploration area and reconnaissance rate of different flight plans. &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Second, we establish a nonlinear programming model with the constraint of the distance between the hospitals and the distribution of the medicine. Using time and exploration area as the target function to determine the optimal location and make a best decision by weighing both factors. &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Third, we establish a model of three-dimensional packaging and using the heuristic algorithm to determine the best package solution of two iso container respectively. The constraint is to take enough medicine and drone to make the two highest utilization rates of the volume of the container, trying to reduce the use of buffer material. &lt;/em&gt;&lt;/p&gt;&lt;em&gt;Finally, the optimal flight plan is determined with the consideration of the highest flight safety and detection efficiency of UAV. In the stability analysis of our model, we prove the reliability of our model from different perspectives. Then we analyzed the advantages and disadvantages of our model.&lt;/em&gt;

Flight phase and altitude-dependent geometrical vertical flight plan optimization minimizing the total number of vertical plan segments

This paper presents a new method for the geometrical construction of an optimal vertical flight plan associated to a provided lateral flight plan defined as a succession of waypoints characterized by their along-the-track distance relative to the first waypoint and their constraints. The principal objective of the proposed method is the minimization of the total number of vertical flight plan segments, whose slope values closest match the values set for their corresponding flight phase and altitude. The main advantage of the proposed method is that it constructs the optimized vertical flight plan employing faster—and less-intensive computations than methods based solely on aircraft performance models. Also, the proposed algorithm has the advantage of generating ground-fixed predicted vertical flight plans which, when flown, are less sensitive to varying wind conditions, thus, smaller trajectory deviations than those computed using solely the model-based algorithms. Two implementations corresponding to different trade-offs between conflicting preferred gradient and minimal segment length constraints were compared. The results show that a vertical flight path segment’s construction and resulting configuration is dependent on the configuration of the vertical flight plan segments that precede it. The results also show that for a majority of the test cases, the resulting flight plans computed using the two implementations were identical. Moreover, even when the flight plans were not completely identical, many of the corresponding segments were identical.

DroneTank: Planning UAVs' Flights and Sensors' Data Transmission under Energy Constraints.

We consider an Unmanned Aerial Vehicle (UAV, also known as drone) as an aerial sink to travel along a natural landscape or rural industrial linear infrastructure to collect data from deployed sensors. We study a joint schedule problem that involves flight planning for the drone and transmission scheduling for sensors, such that the maximum amount of data can be collected with a limited individual energy budget for the UAV and the sensors, respectively. On one hand, the flight planning decides the flight speed and flight path based on sensor locations, energy budgets, and the transmission schedule. On the other hand, the transmission schedule decides for each sensor when to deliver data and what transmission power to use based on the energy budgets and flight plan. By observing three import optimality properties, we decouple the joint problem into two subproblems: drone flight planning and sensor transmission scheduling. For the first problem, we propose a dynamic programming algorithm to produce the optimal flight planning. For the second problem, with a flight plan as input, we introduce a novel technique (water-tank), which together with dynamic programming, is the key to achieve an optimal transmission schedule that maximizes data collection. Simulations show that the separately determined flight plan and transmission schedule are near-optimal for the original joint problem.

Fast Variable Neighborhood Search for Flight Rescheduling After Airport Closure

When an extreme weather event occurs, the temporary closure of airports is inevitable. In this case, airlines need to optimize their flight schedules in short order to reduce losses. However, it is very hard to address a large-scale disruption within a short time using traditional methods. In this paper, FVNS, a fast variable neighborhood search-based algorithm, is proposed to solve this problem. The method can be divided into two stages. The first stage is the construction stage, i.e., postponing the affected flights and constructing a feasible flight plan. The second stage is the improvement stage. In this stage, by searching for and implementing cost-effective flight swap operations, the flight plan is improved, and the optimal flight plan is finally obtained. The results of the test examples show that both the computational results and the computational speed are significantly better than those of the previous methods. Linear programming and local search are the two main algorithms used in flight recovery research. In this paper, we compare and analyze the advantages and disadvantages of each algorithm with examples and note that researchers should develop local search algorithms to form a practical general algorithm framework.

A Route Planning Method Based on the Airspace Divided by Grid Method

As the operations of airspace is becoming more and more complex, the restricted area has become one of the most important threat to flight safety. In order to avoid the conflict between aircraft and restricted area and ensure the route’s distance optimal, an efficient and safe flight plan is determined by route planning.

Turning mechanisms for airborne LiDAR and photographic data acquisition

Indian Institute of Technology Kanpur, Department of Civil Engineering, Kanpur 208016, Indiaajayd@iitk.ac.in, ajaydashora@gmail.comAbstract. Flight duration, which consists of strip time and turning time, is an important elementof flight planning of airborne surveys as it affects the cost of data acquisition. The turning timedominatesover thestrip time andthusdictatesthe flightduration. However,the currentpracticesof flight planning assume it as a constant for easier calculations in flight planning. Further, thereis no literature available explicitly on turning mechanisms for airborne surveys. Instead ofassumingaconstantorfollowingthecomplicatedmodelsofturning,thispaperadvocatessimpleheuristic-basedmodelsandturningmechanisms.Themodelsandturningmechanismsaredevel-oped by considering the feasibility of flight operations, experiences of pilots, and the availableapproximate models of turning in the literature. The paper illustrates consecutive and noncon-secutiveturning mechanismsandderivescomprehensivemathematicalformulationstorepresentthese. An algorithmic scheme for selection of an optimal turning mechanism is presented. Thepaper argues that the discussed turning mechanisms and algorithms can be combined with thestrip time for arriving at the optimal flight plan using the genetic and evolutionary algorithms.The developed approach can be easily incorporated into the present knowledge base of flightplanning.

New approach for air traffic management based on control theory

Air traffic management aims to provide solutions to congestion problems in air traffic networks (ATNs) which in turn are mainly generated by the variation in the capacity of air sectors or airports due to adverse weather conditions. Most of the existing approaches to dealing with these problems are based on mathematical programming techniques and inherit its computational difficulty. In this paper, we introduce a control scientist point of view to this topic by proposing an approach to solve the ground-holding problem based on discrete event systems control theory. An ATN can effectively be considered as a timed discrete event system and can be efficiently modelled based on a Time Petri net tool. The main advantage is an explicit representation of the position of each aircraft in the ATN at each time instant. The state space is modelled by a Discrete Time Reachability Graph and the capacity constraints on the air sectors are modelled by time floating general mutual exclusion constraints. Feasible flight plans can be constructed based on control synthesis techniques, while an algorithm to compute the optimal flight plan is proposed assuming a realistic cost function.

Two-step procedure of optimisation for flight planning problem for airborne LiDAR data acquisition

Flight planning for airborne LiDAR data collection determines flight parameters, which in turn control the flight duration. While the former ensures desired quality of captured data the cost of the project is directly affected by the latter. This paper attempts to optimise flight planning problem. The flight duration is expressed as an objective function and the associated data requirements, preferences and limitations of flight planning problem are considered as constraints. Due to the typical characteristics of flight duration and flight parameters, a two-step procedure of optimisation that consists of genetic algorithms (GA) and Hooke and Jeeve’s (HJ) method of optimisation are adopted. The two-step procedure alleviates the pitfalls of both GA and HJ method and successfully determines the optimal flight planning parameters for a fairly complicated problem. Results obtained in this paper demonstrate that the proposed two-step procedure can be used for solving complex engineering problems like flight pla...

Air Traffic Control by Programmed Navigation

This paper proposes that the navigation and control of all airliners should be automated from take-off to landing. Each aircraft will fly according to a prescribed flight plan, to be fulfilled in position, altitude and time within prescribed tolerances. The optimal flight plan is elaborated by a central air traffic control station and transmitted by data link to an airborne computer which monitors the navigation of the aircraft. The navigation itself is based on an integrated Inertial/DME/DME system. Separate airways are proposed for the general aviation. The paper was presented at the 19th Technical Conference of I.A.T.A., Dublin, October 1972.The permanent growth of air traffic demands rigorous regulation. The most efficient form of regulation is the careful elaboration of a flight plan, taking into account the total air traffic in the area and the rigorous fulfilment of this flight plan. The flight plan will be elaborated at a central air traffic control station by computer, taking into account both air traffic and the meteorological conditions, especially wind. This flight plan is transferred by radio to the computer in the aircraft and comprises essentially the three-dimensional coordinates of take-off point, destination and way points as well as the corresponding times; also the precomputed values of ground speed, rate of climb and rate of descent.