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.

Obstacle avoidance in V-shape formation flight of multiple fixed-wing UAVs using variable repulsive circles

2020 ◽  
Vol 124 (1282) ◽  
pp. 1979-2000
Author(s):  
A. Mirzaee Kahagh ◽  
F. Pazooki ◽  
S. Etemadi Haghighi
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Formation Control ◽  
Functional Limitations ◽  
Formation Flight ◽  
Artificial Potential Field ◽  
Aerial Vehicles ◽  
Shape Formation ◽  
Vector Approach

ABSTRACTA formation control and obstacle avoidance algorithm has been introduced in this paper for the V-shape formation flight of fixed-wing UAVs (Unmanned Aerial Vehicles) using the potential functions method. An innovative vector approach has been suggested to fix the conventional challenge in employing the artificial potential field (APF) approach (the creation of local minimums). A method called variable repulsive circles (VRC) has been then presented aimed at designing proper flight paths tailored with functional limitations of fixed-wing UAVs in facing obstacles. Finally, the efficiency of the designed algorithm has been examined and evaluated for different flight scenarios.

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.

Bird Flocking Inspired Formation Control for Unmanned Aerial Vehicles Using Stereo Camera

2019 ◽  
Vol 13 (3) ◽  
pp. 3580-3589 ◽  
Author(s):  
Jonathan Lwowski ◽  
Abhijit Majumdar ◽  
Patrick Benavidez ◽  
John J. Prevost ◽  
Mo Jamshidi
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Formation Control ◽  
Stereo Camera ◽  
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.

Sign in / Sign up

Export Citation Format

Share Document