Optimizing Urban LiDAR Flight Path Planning Using a Genetic Algorithm and a Dual Parallel Computing Framework

This paper introduces a genetic algorithm (GA) and a beam tracing algorithm incorporated within a dual parallel computing framework to optimize urban aerial laser scanning (ALS) missions to maximize vertical façade data capture, as needed for many three-dimensional reconstruction and modeling workflows. The optimization employs a low-density point cloud from the site of interest as a spatial representation of the urban scene. The GA is suitable for LiDAR flight path optimization due to its capability of handling open-ended problems that have many solutions. However, GAs require evaluating a very large number of candidates. The use of an initial point cloud allows realistic modeling of the urban environment in the optimization at the cost of high data input volumes. To cope with the computational and data demands, a dual parallel computing framework was devised. The parallel computing framework consists of two layers of parallelization. In the upper layer, multiple evaluators work in parallel and in conjunction with a main multi-threading GA optimizer to perform GA operations and evaluate the flight paths. In the lower layer, to evaluate assigned flight paths, each evaluator distributes its data and computation to multiple executors, which can reside on multiple physical nodes of a distributed-memory computing cluster. In addition to parallelism, the data partitioning on the lower layer allows out-of-core computation. Namely, data partitions are efficiently transferred between disks and memory so that only relevant subsets of data are kept in the main memory. The objective of the proposed method is threefold: (1) search for flight paths that yield the highest numbers of vertical points, (2) create a means to explicitly consider the detailed spatial configuration of urban environments, and (3) assure that the proposed optimization strategy is fast and can scale to large problem sizes. Multiple experiments were conducted and demonstrated the success of the proposed method. Converged results were achieved after dozens of generations within two hours. Two flight paths identified by the GA as the most and the least optimal candidates were deployed in real flight missions. The optimal flight path captured 16% more vertical points than the least optimal one, slightly higher than the 13% predicted. Both layers of parallelization were efficient: 13.1/16 for the lower layer and 3.2/4 for the upper layer. The two complementary layers of parallelization allowed flexible and efficient use of distributed computing resources to reduce the runtime. The scalability of the proposed approach was successfully demonstrated up to a data size of 460 million points. The optimization results were realistic and aligned well with the test flight results.

Constructing the models of programmed flight for path calculation in designing tactical and anti-aircraft guided missiles

Several models of programmed flight have been constructed to perform calculations on flight path optimization in designing tactical and anti-aircraft-guided missiles. The developed models are based on the determination of interrelated programmed values of altitude and the flight path angle depending on the range which have a differential relationship. The combination of flight altitude and flight-path angle programs allows the users to simulate the steady flight of a guided missile to the calculated endpoint using the methods of proportional control. Good correspondence of the developed models to the physics of flight was shown by assessing the quality of approximation of the developed models of flight paths of anti-aircraft guided missiles obtained using other known models. The obtained approximation error was less than 5 % which indicates a good correspondence of the developed models to the physics of flight. Compliance of the developed models of programmed flight with the intended purpose and the advantage over the most common known models were proved by optimizing the flight paths of the anti-aircraft-guided missile. In most of the considered calculation cases, the value of the objective function was improved to 2.9 %. The flight path was optimized using a genetic algorithm. The developed models have a simple algebraic form and a small number of control parameters are presented in a ready-to-use form and do not require refinement for a concrete task. This allows them to be implemented in design practice without spending much time to speed up the calculation of optimal design variables and optimal flight paths of tactical and anti-aircraft-guided missiles

Flight path optimization with application to in-flight replanning to changing destinations

Purpose The purpose of this paper is to present a new approach for finding a minimum-length trajectory for an autonomous unmanned air vehicle or a long-range missile from a release point with specified release conditions to a destination with specified approach conditions. The trajectory has to avoid obstacles and no-fly zones and must take into account the kinematic constraints of the air vehicle. Design/methodology/approach A discrete routing model is proposed that represents the airspace by a sophisticated network. The problem is then solved by applying standard shortest-path algorithms. Findings In contrast to the most widely used grids, the generated networks allow arbitrary flight directions and turn angles, as well as maneuvers of different strengths, thus fully exploiting the flight capabilities of the aircraft. Moreover, the networks are resolution-independent and provide high flexibility by the option to adapt density. Practical implications As an application, a concept for in-flight replanning of flight paths to changing destinations is proposed. All computationally intensive tasks are performed in a pre-flight planning prior to the launch of the mission. The in-flight planning is based entirely on precalculated data, which are stored in the onboard computer of the air vehicle. In particular, no path finding algorithms with high or unpredictable running time and uncertain outcome have to be applied during flight. Originality/value The paper presents a new network-based algorithm for flight path optimization that overcomes weaknesses of grid-based approaches and allows high-quality solutions. The method can be applied for quick in-flight replanning of flight paths.

Sizing implications of a regional aircraft for inner-city operations

Purpose The paper aims to assess the potential of aircraft operation from city centres to achieve shortened travel times and the involved aircraft design process. Design/methodology/approach The paper describes the methodical approach and iterative procedure of the design process. An assessment of potential technologies is conducted to provide the required enhancements to fulfil the constraints following an inner-city operation. Operational procedures were analysed to reduce the noise propagation through flight path optimization. Furthermore, a ground-based assisted take-off system was conceived to lower required take-off field length and to prevent engine sizing just for the take-off case. Cabin design optimization for a fast turnaround has been conducted to ensure a wide utilization spectrum. The results prove the feasibility of an aircraft developed for inner city operation. Findings A detailed concept for a 60-passenger single aisle aircraft is proposed for an Entry-Into-Service year 2040 with a design range of 1,500 nautical miles for a load factor of 90 per cent. Although the design for Short Take-off and Landing and low noise operation had to be traded partly with cruise efficiency, a noteworthy reduction in fuel burn per passenger and nautical mile could be achieved against current aircraft. Practical implications The findings will contribute to the evaluation of the feasibility and impact of the Flightpath 2050 goal of a 4-h door-to-door by providing a feasible but ambitious example. Furthermore, it highlights possible bottlenecks and problems faced when realizing this goal. Originality/value The paper draws its value from the consideration of the overall sizing effects at aircraft level and from a holistic view on an inner-city airport/aircraft concept design for a 4-h door-to-door goal.