UAV Trajectory Planning for Static and Dynamic Environments

Ruz, José J.; Arevalo, O.; Pajares, Gonzalo; Cruz, J.M. de la

doi:10.5772/6483

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…The study includes the most comprehensive set of requirements including the ones overlooked in a wide range of studies. This study extends existing literature 1,3,20,21,[32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51] by placing a special importance on aviation rules and utilisation considerations. The model generates suitable paths that address UAV performance limitations, environmental factors, basic aviation rules, flight dynamics, UAV utilisation considerations and user requirements.…”

Section: Introductionsupporting

confidence: 60%

“…In addition, decomposition methods are also used to reduce the number of samples in the generated graph by dividing the world space into regions 30,31 . UAV path planning studies addresses multiple flight objectives under several flight criteria 12,20,21,[32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51] . In this study, we try to address an extensive set of criteria (see Table 1) in online path planning by implementing multiple constraints to provide more effective and safer UAV paths.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A complex dynamic environment is the one that includes many constraints with different characteristics and various mission, flight, and environment related requirements. Even though, studies in autonomous path planning 1,3,20,21,[32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51] address many challenges, domainspecific operational issues, such as utilisation considerations and aviation rules, did not receive adequate attention. This is important if the UAV under study is a medium altitude high endurance (MALE) UAV, because these types of UAVs are subject to aviation rules in addition to other criteria.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of 3D Versus 4D Path Planning for Unmanned Aerial Vehicles

2016

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This research compares 3D versus 4D (three spatial dimensions and the time dimension) multi-objective and multi-criteria path-planning for unmanned aerial vehicles in complex dynamic environments. In this study, we empirically analyse the performances of 3D and 4D path planning approaches. Using the empirical data, we show that the 4D approach is superior over the 3D approach especially in complex dynamic environments. The research model consisting of flight objectives and criteria is developed based on interviews with an experienced military UAV pilot and mission planner to establish realism and relevancy in unmanned aerial vehicle flight planning. Furthermore, this study incorporates one of the most comprehensive set of criteria identified during our literature search. The simulation results clearly show that the 4D path planning approach is able to provide solutions in complex dynamic environments in which the 3D approach could not find a solution.Keywords: Unmanned aerial vehicles, UAV, path planning, modelling, simulation, 3D path planning, 4D path planning Vol. 66, No. 6, November 2016, pp. 651-664, DOI : 10.14429/dsj.66 , VOL. 66, NO. 6, NOVEMbER 2016 652 model used to create flight paths in 4D environment. The simulation model is more applicable and realistic compared to other studies examined during the literature review. The study includes the most comprehensive set of requirements including the ones overlooked in a wide range of studies. This study extends existing literature 1,3,20,21,[32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51] by placing a special importance on aviation rules and utilisation considerations. The model generates suitable paths that address UAV performance limitations, environmental factors, basic aviation rules, flight dynamics, UAV utilisation considerations and user requirements. It helps in online and offline planning of optimal paths based on distance, fuel consumption, or time objectives, while implementing the described flight criteria. To build the simulation model (SM), we first built a conceptual model (CM) to structure the problem 68 . In the simulations, for each objective, various scenarios are created by changing the number of static and dynamic obstacles and target types. In each scenario, the path planning approach found the shortest and least costly flight paths. The path search is performed by A* heuristic algorithm proven to be complete and optimal. Additionally, in the experiments, A* algorithms with different heuristic parameters are compared using various scenarios in static and dynamic environments under different constraints. Since current UAVs have to make predictions and estimations about the possible future locations of mobile objects, the simulations also include path searches in time varying environments represented with a 4D grid. The 4D grid is constructed using a combination of 3D grids. Each 3D grid is a possible configuration of the world space at a specific time. A time-dimensional search space consider...

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Section: Introductionsupporting

confidence: 60%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparison of 3D Versus 4D Path Planning for Unmanned Aerial Vehicles

2016

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Heuristic algorithm and cooperative relay for energy efficient data collection with a UAV and WSN

Grøtli

Johansen

2013

2013 International Conference on Computing, Management and Telecommunications (ComManTel)

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Route planning method design for UAV under radar ECM scenario

Duan

et al. 2014

2014 12th International Conference on Signal Processing (ICSP)

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Aiming at improving the survivability of unmanned aerial vehicle (UAV) in radar threat situation, a method of UAV route planning based on analytic hierarchy process (AHP) is proposed. Compared with the previous model of the route planning, a variety of qualitative factors and quantitative factors, such as the spatial positions of both UAV and radar and the detection probability of the radar, are introduced for providing a more accurate description of radar threat and the jamming effectiveness of UAV. Then the ant colony algorithm is applied to the route planning problem based on the dynamic ECM model. Simulation results show that the proposed model is efficient in solving the route planning problem of UAV.

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UAV Trajectory Planning for Static and Dynamic Environments

Cited by 4 publications

References 14 publications

Comparison of 3D Versus 4D Path Planning for Unmanned Aerial Vehicles

Comparison of 3D Versus 4D Path Planning for Unmanned Aerial Vehicles

Heuristic algorithm and cooperative relay for energy efficient data collection with a UAV and WSN

Route planning method design for UAV under radar ECM scenario

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