Enhanced Potential Field-Based Collision Avoidance for Unmanned Aerial Vehicles in a Dynamic Environment

Author(s):  
Daegyun Choi ◽  
Kyuman Lee ◽  
Donghoon Kim
Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao

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.


Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4540
Author(s):  
Leszek Ambroziak ◽  
Maciej Ciężkowski

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.


Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
Daegyun Choi ◽  
Anirudh Chhabra ◽  
Donghoon Kim

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.


Actuators ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
Sunan Huang ◽  
Rodney Swee Huat Teo ◽  
Wenqi Liu

It is well-known that collision-free control is a crucial issue in the path planning of unmanned aerial vehicles (UAVs). In this paper, we explore the collision avoidance scheme in a multi-UAV system. The research is based on the concept of multi-UAV cooperation combined with information fusion. Utilizing the fused information, the velocity obstacle method is adopted to design a decentralized collision avoidance algorithm. Four case studies are presented for the demonstration of the effectiveness of the proposed method. The first two case studies are to verify if UAVs can avoid a static circular or polygonal shape obstacle. The third case is to verify if a UAV can handle a temporary communication failure. The fourth case is to verify if UAVs can avoid other moving UAVs and static obstacles. Finally, hardware-in-the-loop test is given to further illustrate the effectiveness of the proposed method.


Author(s):  
Jialong Zhang ◽  
Bing Xiao ◽  
Maolong Lv ◽  
Qiang Zhang

This article addresses a flight-stability problem for the multiple unmanned aerial vehicles cooperative formation flight in the process of the closed and high-speed flight. The main objective is to design a cooperative formation controller with known external factors, and this controller can keep the consensus of attitude and position and reduce the communication delay between any two unmanned aerial vehicles and increase unmanned aerial vehicles formation cruise time under the known external factors. Known external factors are taken into consideration, and longitude maneuvers using nonlinear thrust vectors were employed with unsteady aerodynamic models, according to the attitude and position of unmanned aerial vehicles, which were employed as corresponding input signals for studying the dynamic characteristics of unmanned aerial vehicles formation flight. In addition, the relative distance between any two unmanned aerial vehicles was not allowed to exceed their safe distance so that the controller could perform collision avoidance. An analysis of formation flight distance error shows that it converged to a fixed value that well ensured unmanned aerial vehicles formation flight stability. The experimental results show that the controller can improve the speed of a closed formation effectively and maintain the stability of formation flight, which provides a method for closed formation flight controller design and collision avoidance for any two unmanned aerial vehicles. Meanwhile, the effectiveness of proposed controller is fully proved by semi-physical simulation platform.


2019 ◽  
Vol 42 (5) ◽  
pp. 942-950
Author(s):  
Kai Chang ◽  
Dailiang Ma ◽  
Xingbin Han ◽  
Ning Liu ◽  
Pengpeng Zhao

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.


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