scholarly journals Three Dimensional UAV Positioning for Dynamic UAV-to-Car Communications

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 356 ◽  
Author(s):  
Seilendria A. Hadiwardoyo ◽  
Carlos T. Calafate ◽  
Juan-Carlos Cano ◽  
Kirill Krinkin ◽  
Dmitry Klionskiy ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Optimization Algorithms ◽  
Three Dimensional ◽  
Path Loss ◽  
Flight Altitude ◽  
Vehicular Communications ◽  
Dynamic Movement ◽  
Aerial Vehicles ◽  
Positioning Technique ◽  
Simulation Results

In areas with limited infrastructure, Unmanned Aerial Vehicles (UAVs) can come in handy as relays for car-to-car communications. Since UAVs are able to fully explore a three-dimensional environment while flying, communications that involve them can be affected by the irregularity of the terrains, that in turn can cause path loss by acting as obstacles. Accounting for this phenomenon, we propose a UAV positioning technique that relies on optimization algorithms to improve the support for vehicular communications. Simulation results show that the best position of the UAV can be timely determined considering the dynamic movement of the cars. Our technique takes into account the current flight altitude, the position of the cars on the ground, and the existing flight restrictions.

Three-dimensional waypoint following for fixed-wing unmanned aerial vehicles in obstacle-filled environments

2019 ◽  
Vol 234 (3) ◽  
pp. 640-654
Author(s):  
Nikhil Kumar Singh ◽  
Sikha Hota
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Optimal Path ◽  
Three Dimensional ◽  
Computation Time ◽  
Two Dimensional ◽  
Aerial Vehicles ◽  
Optimal Paths ◽  
Straight Line ◽  
Different Types ◽  
Simulation Results

The paper computes optimal paths for fixed-wing unmanned aerial vehicles with bounded turn radii to follow a series of waypoints with specified directions in a three-dimensional obstacle-filled environment. In the existing literature, it was proved that the optimal path is of circular turn–straight line–circular turn (CSC) type for two consecutive waypoint configurations, when the points are sufficiently far apart and there is no obstacle in the field. The maximum of all minimum turn radii corresponding to all possible two-dimensional circular maneuvers was used for both the initial and final turns to develop the CSC-type paths. But, this paper considers the minimum turn radii for initial and final turns, corresponding to the maneuvering planes and which produces shorter CSC-type paths. In an obstacle-filled environment the shortest path may collide with obstacles, so a strategy is proposed to switch to the next best path that does not collide with obstacles. Using this technique, a series of waypoints is followed in the presence of obstacles of different types, for example, cylindrical, hemispherical, and spherical in shapes with different sizes. Finally, simulation results are presented to show the efficiency of the algorithm for obstacle avoidance. The computation time listed here indicates the potentiality of this algorithm for implementation in real time.

A method for autonomous collision-free navigation of a quadrotor UAV in unknown tunnel-like environments

Robotica ◽  
2021 ◽  
pp. 1-27
Author(s):  
Taha Elmokadem ◽  
Andrey V. Savkin
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicles ◽  
Practical Implementation ◽  
Challenging Problem ◽  
Quadrotor Uav ◽  
Navigation Algorithm ◽  
Aerial Vehicles ◽  
Quadrotor Uavs

Abstract Unmanned aerial vehicles (UAVs) have become essential tools for exploring, mapping and inspection of unknown three-dimensional (3D) tunnel-like environments which is a very challenging problem. A computationally light navigation algorithm is developed in this paper for quadrotor UAVs to autonomously guide the vehicle through such environments. It uses sensors observations to safely guide the UAV along the tunnel axis while avoiding collisions with its walls. The approach is evaluated using several computer simulations with realistic sensing models and practical implementation with a quadrotor UAV. The proposed method is also applicable to other UAV types and autonomous underwater vehicles.

Intelligent cooperative collision avoidance via fuzzy potential fields

Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
Daegyun Choi ◽  
Anirudh Chhabra ◽  
Donghoon Kim
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Fuzzy Inference ◽  
Potential Fields ◽  
Rule Base ◽  
Local Minima ◽  
Inference System ◽  
Aerial Vehicles ◽  
Different Shapes ◽  
Simulation Results

Summary This paper proposes an intelligent cooperative collision avoidance approach combining the enhanced potential field (EPF) with a fuzzy inference system (FIS) to resolve local minima and goal non-reachable with obstacles nearby issues and provide a near-optimal collision-free trajectory. A genetic algorithm is utilized to optimize parameters of membership function and rule base of the FISs. This work uses a single scenario containing all issues and interactions among unmanned aerial vehicles (UAVs) for training. For validating the performance, two scenarios containing obstacles with different shapes and several UAVs in small airspace are considered. Multiple simulation results show that the proposed approach outperforms the conventional EPF approach statistically.

scholarly journals Vision-Based Target Three-Dimensional Geolocation Using Unmanned Aerial Vehicles

2018 ◽  
Vol 65 (10) ◽  
pp. 8052-8061 ◽  
Author(s):  
Lele Zhang ◽  
Fang Deng ◽  
Jie Chen ◽  
Yingcai Bi ◽  
Swee King Phang ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Three Dimensional ◽  
Aerial Vehicles

Optimized artificial potential field algorithm to multi-unmanned aerial vehicle coordinated trajectory planning and collision avoidance in three-dimensional environment

2019 ◽  
Vol 233 (16) ◽  
pp. 6032-6043 ◽  
Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Unmanned Aerial Vehicle ◽  
Trajectory Planning ◽  
Potential Field ◽  
Three Dimensional ◽  
Artificial Potential Field ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Vehicle Trajectory

Multi-unmanned aerial vehicle trajectory planning is one of the most complex global optimum problems in multi-unmanned aerial vehicle coordinated control. Results of recent research works on trajectory planning reveal persisting theoretical and practical problems. To mitigate them, this paper proposes a novel optimized artificial potential field algorithm for multi-unmanned aerial vehicle operations in a three-dimensional dynamic space. For all purposes, this study considers the unmanned aerial vehicles and obstacles as spheres and cylinders with negative electricity, respectively, while the targets are considered spheres with positive electricity. However, the conventional artificial potential field algorithm is restricted to a single unmanned aerial vehicle trajectory planning in two-dimensional space and usually fails to ensure collision avoidance. To deal with this challenge, we propose a method with a distance factor and jump strategy to resolve common problems such as unreachable targets and ensure that the unmanned aerial vehicle does not collide into the obstacles. The method takes companion unmanned aerial vehicles as the dynamic obstacles to realize collaborative trajectory planning. Besides, the method solves jitter problems using the dynamic step adjustment method and climb strategy. It is validated in quantitative test simulation models and reasonable results are generated for a three-dimensional simulated urban environment.

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