Adaptive Multi-Agent Unmanned Aerial Vehicle Systems with a Potential Field based Leader-Follower Formation Control Method

2015 ◽  
Author(s):  
Jae Chung ◽  
Yushing Cheung
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Potential Field ◽  
Formation Control ◽  
Control Method ◽  
Vehicle Systems ◽  
Aerial Vehicle ◽  
Multi Agent

scholarly journals Formation Control of Multi Unmanned Aerial Vehicle Systems Based on DDS Middleware

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 44211-44218
Author(s):  
Sami El-Ferik ◽  
Basem Almadani ◽  
Siddig Mustafa Elkhider
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Formation Control ◽  
Vehicle Systems ◽  
Aerial Vehicle

scholarly journals UAV formation obstacle avoidance control method based on artificial potential field and consistency

2021 ◽  
Vol 2083 (4) ◽  
pp. 042029
Author(s):  
Boyu Wei
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Formation Control ◽  
Control Method ◽  
Artificial Potential Field ◽  
Time Varying ◽  
Complex Environments ◽  
Control Scheme ◽  
Avoidance Control ◽  
Multi Agent

Abstract As a typical multi-agent formation, UAV formation is playing an increasingly powerful role in the civilian and military fields. Obstacle avoidance, as an important technology in controlling formation, determines the application prospects of UAVs. This paper studies the time-varying formation of UAVs with interactive topology to avoid obstacles, aiming to improve the ability of UAV formations to deal with complex environments while traveling. Firstly, a repulsive force field is reasonably introduced based on the existing control scheme, and an improved distributed time-varying formation control scheme based on artificial potential field is proposed. Then combined with the basic idea of model predictive control, an obstacle avoidance strategy in which UAV obstacle avoidance and formation shaping are carried out simultaneously is proposed. Finally, a time-varying formation simulation experiment containing four UAVs was carried out to verify the validity of the results.

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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