Unmanned Aerial Vehicles Evolutional Flight Route Planner Using the Potential Field Approach

2012 ◽  
Vol 9 (3) ◽  
pp. 92-109 ◽  
Author(s):  
Chun-Liang Lin ◽  
Chia-Sung Lee ◽  
Ching-Huei Huang ◽  
Tzu-Chiang Kao
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Potential Field ◽  
Field Approach ◽  
Aerial Vehicles ◽  
Flight Route

scholarly journals Virtual Electric Dipole Field Applied to Autonomous Formation Flight Control of Unmanned Aerial Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4540
Author(s):  
Leszek Ambroziak ◽  
Maciej Ciężkowski
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicles ◽  
Flight Control ◽  
Electric Dipole ◽  
Potential Field ◽  
Control Algorithm ◽  
Formation Flight ◽  
Potential Fields ◽  
Dipole Potential ◽  
Aerial Vehicles

The following paper presents a method for the use of a virtual electric dipole potential field to control a leader-follower formation of autonomous Unmanned Aerial Vehicles (UAVs). The proposed control algorithm uses a virtual electric dipole potential field to determine the desired heading for a UAV follower. This method’s greatest advantage is the ability to rapidly change the potential field function depending on the position of the independent leader. Another advantage is that it ensures formation flight safety regardless of the positions of the initial leader or follower. Moreover, it is also possible to generate additional potential fields which guarantee obstacle and vehicle collision avoidance. The considered control system can easily be adapted to vehicles with different dynamics without the need to retune heading control channel gains and parameters. The paper closely describes and presents in detail the synthesis of the control algorithm based on vector fields obtained using scalar virtual electric dipole potential fields. The proposed control system was tested and its operation was verified through simulations. Generated potential fields as well as leader-follower flight parameters have been presented and thoroughly discussed within the paper. The obtained research results validate the effectiveness of this formation flight control method as well as prove that the described algorithm improves flight formation organization and helps ensure collision-free conditions.

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.

Lyapunov vector-based formation tracking control for unmanned aerial vehicles with obstacle/collision avoidance

2019 ◽  
Vol 42 (5) ◽  
pp. 942-950
Author(s):  
Kai Chang ◽  
Dailiang Ma ◽  
Xingbin Han ◽  
Ning Liu ◽  
Pengpeng Zhao
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Potential Field ◽  
Formation Control ◽  
Control Method ◽  
Spherical Surface ◽  
Moving Target ◽  
Local Optima ◽  
Formation Tracking ◽  
Aerial Vehicles ◽  
Repulsive Forces

This paper presents a formation control method to solve the moving target tracking problem for a swarm of unmanned aerial vehicles (UAVs). The formation is achieved by the artificial potential field with both attractive and repulsive forces, and each UAV in the swarm will be driven into a leader-centered spherical surface. The leader is controlled by the attractive force by the moving target, while the Lyapunov vectors drive the leader UAV to a fly-around circle of the target. Furthermore, the rotational vector-based potential field is applied to achieve the obstacle avoidance of UAVs with smooth trajectories and avoid the local optima problem. The efficiency of the developed control scheme is verified by numerical simulations in four scenarios.

scholarly journals Potential field method for persistent surveillance of multiple unmanned aerial vehicle sensors

2018 ◽  
Vol 14 (1) ◽  
pp. 155014771875506 ◽  
Author(s):  
Changxin Huang ◽  
Wei Li ◽  
Chao Xiao ◽  
Binbin Liang ◽  
Songchen Han
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Potential Field ◽  
Region Of Interest ◽  
Field Method ◽  
Attractive Potential ◽  
Straightforward Application ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
The One ◽  
Vehicle Sensors

Persistent surveillance is one of the major tasks envisioned for unmanned aerial vehicles in that some regions of interest need to be continuously surveyed. This distinction from the one-time coverage/exploration does not allow a straightforward application of the most exploration techniques to address the persistent surveillance problem. This article introduces and demonstrates a method of alterable artificial potential field to control a group of unmanned aerial vehicles to stay over the region of interest. We present attractive potential field to drive the unmanned aerial vehicles to desirable areas, obstacle potential field to move away from obstacles, collision avoidance potential field to control unmanned aerial vehicles not to collide with others, and formation of potential field to make unmanned aerial vehicles gather in a group. The simulation results show that the proposed approach could generate collision-free path for unmanned aerial vehicles staying over the region of interest for a long endurance.

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