Path Planning for UAVs for Maximum Information Collection

2013-01-01
Path planning considers the problem of designing the path a vehicle is supposed to follow. Along the designed path the objectives are to maximize the collected information (CI) from desired regions (DR), while avoiding flying over forbidden regions (FR) and reaching the destination. The path planning problem for a single unmanned air vehicle (UAV) is studied with the proposal of novel evolutionary operators: pull-to-desired-region (PTDR), push-from-forbidden-region (PFFR), and pull-to-final-point (PTFP). In addition to these newly proposed operators, standard mutation and crossover operators are used. The initial population seed-path is obtained by both utilizing the pattern search method and solving the traveling salesman problem (TSP). Using this seed-path the initial population of paths is generated by randomly selected heading angles. It should be emphasized that all of the paths in population in any generation of the genetic algorithm (GA) are constructed using the dynamical mathematical model of a UAV equipped with the autopilot and guidance algorithms. Simulations are realized in the MATLAB/Simulink environment. The path planning algorithm is tested with different scenarios, and the results are presented in Section VI. Although there are previous studies in this field, the focus here is on maximizing the CI instead of minimizing the total mission time. In addition it is observed that the proposed operators generate better paths than classical evolutionary operators.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS

Suggestions

3D path planning for unmanned aerial vehicles
Halit, Ergezer; Leblebicioğlu, Mehmet Kemal (2013-05-31)
Path planning considers the problem of designing the path a vehicle is supposed to follow. Along the designed path, the objectives are to maximize the collected information from Desired Regions (DR) while avoiding flying over Forbidden Regions (FR) and reaching the destination. In this paper, the path planning problem for a multiple Unmanned Air Vehicles (UAVs) is studied with the proposal of novel evolutionary operators. The initial populations seed-path for each UAV have been obtained both by utilizing th...
Planning unmanned aerial vehicle's path for maximum information collection using evolutionary algorithms
Ergezer, Halit; Leblebicioğlu, Mehmet Kemal (2011-01-01)
Path planning is a problem of designing the path the vehicle is supposed to follow in such a way that a certain objective is optimized. In our study the objective is to maximize collected amount of information from Desired Regions (DR), meanwhile flying over the Forbidden Regions is avoided. In this paper, the path planning problem for single unmanned air vehicle (UAV) is studied with the proposal of novel evolutionary operators; Pull-to-Desired-Region (PTDR), Push-From-Forbidden-Region (PFFR), Pull-to-Fini...
Strategy creation, decomposition and distribution in particle navigation: Memory module
Beldek, Ulas; Leblebicioğlu, Mehmet Kemal (2005-01-01)
in particle navigation problem strategy development is crucial. The difficulties encountered by the particles during their navigation tasks require different approaches in problem solving. One way to overcome the difficulties is to divide the problem into simple modules and develop solutions for these modules separately. Basically, two different modules are sufficient in addition to the main body to develop a successful solver. The first module (conflict module), which is developed by genetic programming, i...
Safe and Efficient Path Planning for Omni-directional Robots using an Inflated Voronoi Boundary
Aldahhan, Mohammed Rabeea Hashim; Schmidt, Klaus Verner (2019-11-01)
Path planning algorithms for mobile robots are concerned with finding a feasible path between a start and goal location in a given environment without hitting obstacles. In the existing literature, important performance metrics for path planning algorithms are the path length, computation time and path safety, which is quantified by the minimum distance of a path from obstacles. The subject of this paper is the development of path planning algorithms for omni-directional robots, which have the ability ...
Autonomous and manual driving of a multiple turret system in extreme environment
Yerlikaya, Ümit; Balkan, Raif Tuna; Department of Mechanical Engineering (2021-6)
In this thesis, firstly two methods are developed to obtain multi-dimensional configuration space for path planning problems. In typical cases, the path planning problems are solved directly in the 3-D workspace. However, this method is inefficient in handling the robots with various geometrical and mechanical restrictions. To overcome these difficulties, path planning may be formalized and solved in a new space which is called configuration space. In the first method, the point clouds of all the bodies of ...
Citation Formats
H. Ergezer and M. K. Leblebicioğlu, “Path Planning for UAVs for Maximum Information Collection,” IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, pp. 502–520, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36088.