scholarly journals On Obtaining Energy-Optimal Trajectories for Landing of UAVs

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 2062
Author(s):  
Dariusz Horla ◽  
Jacek Cieślak
Keyword(s):  
Minimum Principle ◽  
Optimal Path ◽  
Minimum Energy ◽  
Reference Trajectory ◽  
Classical Dynamic ◽  
Optimal Path Planning ◽  
Minimum Energy Consumption ◽  
Programming Techniques ◽  
Aerial Vehicle ◽  
Reference Trajectories

The optimization issues connected to a landing task of an unmanned aerial vehicle are discussed in the paper, based on a model of a mini-class drone. Three landing scenarios are considered, including minimum-time landing, landing with minimum energy consumption, and planned landing. With the use of classical dynamic programming techniques, including the minimum principle of Pontryagin, as well as the calculus of variations, the optimal altitude reference trajectories are found, to form the altitude control system in such a way as to mimic the profile of the reference trajectory by the actual altitude of the UAV. The simulation results conducted with the use of the Simulink Support Package for Parrot Minidrones verify the correctness and effectiveness of the method, and open the research directions for further analysis, especially to tune altitude controller in a way, as to track the reference profile. Up to this point, optimization tasks considered in the literature, with respect to the drones, were connected to swarm formation optimization, optimization of the take-off process or landing process limited to optimal path planning. This paper thus considers a new topic in the field.

scholarly journals PPS: Energy-Aware Grid-Based Coverage Path Planning for UAVs Using Area Partitioning in the Presence of NFZs

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3742
Author(s):  
Alia Ghaddar ◽  
Ahmad Merei ◽  
Enrico Natalizio
Keyword(s):  
Minimum Energy ◽  
Energy Aware ◽  
Coverage Path Planning ◽  
Minimum Energy Consumption ◽  
Aerial Vehicle ◽  
Monitoring And Surveillance ◽  
Area Monitoring ◽  
Grid Based ◽  
Quality Of Coverage

Area monitoring and surveillance are some of the main applications for Unmanned Aerial Vehicle (UAV) networks. The scientific problem that arises from this application concerns the way the area must be covered to fulfill the mission requirements. One of the main challenges is to determine the paths for the UAVs that optimize the usage of resources while minimizing the mission time. Different approaches rely on area partitioning strategies. Depending on the size and complexity of the area to monitor, it is possible to decompose it exactly or approximately. This paper proposes a partitioning method called Parallel Partitioning along a Side (PPS). In the proposed method, grid-mapping and grid-subdivision of the area, as well as area partitioning are performed to plan the UAVs path. An extra challenge, also tackled in this work, is the presence of non-flying zones (NFZs). These zones are areas that UAVs must not cover or pass over it. The proposal is extensively evaluated, in comparison with existing approaches, to show that it enables UAVs to plan paths with minimum energy consumption, number of turns and completion time while at the same time increases the quality of coverage.

Optimal Path Planning of Redundant Cooperative Robots Under Equality and Inequality Constraints

2003 ◽  
Author(s):  
Ali Hosseini ◽  
Mehdi Keshmiri
Keyword(s):  
Path Planning ◽  
Optimization Problem ◽  
Search Algorithm ◽  
Minimum Principle ◽  
Optimal Path ◽  
Inequality Constraints ◽  
Optimal Path Planning ◽  
Nonlinear Inequality ◽  
Nonlinear Inequality Constraints ◽  
Cooperative Manipulators

Using kinematic resolution, the optimal path planning for two redundant cooperative manipulators carrying a solid object on a desired trajectory is studied. The optimization problem is first solved with no constraint. Consequently, the nonlinear inequality constraints, which model obstacles, are added to the problem. The formulation has been derived using Pontryagin Minimum Principle and results in a Two Point Boundary Value Problem (TPBVP). The problem is solved for a cooperative manipulator system consisting of two 3-DOF serial robots jointly carrying an object and the results are compared with those obtained from a search algorithm. Defining the obstacles in workspace as functions of joint space coordinates, the inequality constrained optimization problem is solved for the cooperative manipulators.

scholarly journals Simulation and experimental approach for optimal path planning of UAV using A* and MEA* algorithms

2021 ◽  
Vol 12 ◽  
pp. 24
Author(s):  
Balasubramanian Esakki ◽  
Gayatri Marreddy ◽  
M. Sai Ganesh ◽  
E. Elangovan
Keyword(s):  
Path Planning ◽  
Present Article ◽  
Unmanned Aerial Vehicle ◽  
Execution Time ◽  
Crucial Role ◽  
Experimental Approach ◽  
Optimal Path ◽  
Optimal Path Planning ◽  
The Past ◽  
Aerial Vehicle

Over the past decades, Unmanned Aerial Vehicle (UAV) have been effectively adapted to perform disaster missions, agricultural and various societal applications. The path planning plays a crucial role in bringing autonomy to the UAVs to attain the designated tasks by avoiding collision in the obstacles prone regions. Optimal path planning of UAV is considered to be a challenging issue in real time navigation during obstacle prone environments. The present article focused on implementing a well-known A* and variant of A* namely MEA* algorithm to determine an optimal path in the varied obstacle regions for the UAV applications which is novel. Simulation is performed to investigate the performance of each algorithm with respect to comparing their execution time, total distance travelled and number of turns made to reach the source to target. Further, experimental flight trails are made to examine the performance of these algorithms using a UAV. The desired position, velocity and yaw of UAV is obtained based on the waypoints of optimal path planned data and effective navigation is performed. The simulation and experimental results are compared for confirming the effectiveness of these algorithms.

scholarly journals Analytical Synthesis of Control Acceleration of Unmanned Aerial Vehicle

2021 ◽  
Vol 20 (4) ◽  
pp. 338-344
Author(s):  
A. A. Lobaty ◽  
A. Y. Bumai ◽  
S. S. Prohorovith
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Minimum Energy ◽  
Vertical Plane ◽  
Original Form ◽  
Minimum Energy Consumption ◽  
Initial Stage ◽  
Horizontal Flight ◽  
Aerial Vehicle ◽  
Definition Of ◽  
Analytical Synthesis

. The problem of analytical synthesis of the control acceleration for an unmanned aerial vehicle (UAV) during its flight along a complex trajectory, consisting of sequentially located horizontal flight sections, located at different heights relative to the earth's surface has been solved in the paper. The problem has been solved as an analytical definition of the  optimal control of a linear non-stationary system for a specified minimized quality functional. The mathematical model  of the system is presented in the form of differential equations of UAV motion in the vertical plane of a fixed coordinate  system related to the earth's surface. A feature of the proposed methodology for solving the problem is the substantiation  of the original form of the minimized functional and parameters included in the law of variation of the control acceleration obtained by known methods. As the components of the quality functional, the values of coordinates and velocity of the UAV are considered and they are specified at the corresponding points in space through which the UAV path must pass, in order  to obtain the optimal curvature of the trajectory. The derived mathematical dependences make it possible to implement them on board of an aircraft and, ultimately, solve the problem of ensuring the minimum energy consumption when controlling  an object (UAV). Computer simulation of the analytically obtained results in the form of the UAV flight trajectory and  the processes of changing its acceleration and speed have shown the efficiency of the proposed technique and the prospects  of its use at the initial stage of the synthesis of the UAV control system.

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