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.

scholarly journals Formation Control and Obstacle Avoidance Algorithm of a Multi-USV System Based on Virtual Structure and Artificial Potential Field

2021 ◽  
Vol 9 (2) ◽  
pp. 161
Author(s):  
Xun Yan ◽  
Dapeng Jiang ◽  
Runlong Miao ◽  
Yulong Li
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Formation Control ◽  
Shape Change ◽  
Artificial Potential Field ◽  
Generation Algorithm ◽  
Time Performance ◽  
Movement Ability ◽  
Window Approach ◽  
Avoidance Problem

This paper proposes a formation generation algorithm and formation obstacle avoidance strategy for multiple unmanned surface vehicles (USVs). The proposed formation generation algorithm implements an approach combining a virtual structure and artificial potential field (VSAPF), which provides a high accuracy of formation shape keeping and flexibility of formation shape change. To solve the obstacle avoidance problem of the multi-USV system, an improved dynamic window approach is applied to the formation reference point, which considers the movement ability of the USV. By applying this method, the USV formation can avoid obstacles while maintaining its shape. The combination of the virtual structure and artificial potential field has the advantage of less calculations, so that it can ensure the real-time performance of the algorithm and convenience for deployment on an actual USV. Various simulation results for a group of USVs are provided to demonstrate the effectiveness of the proposed algorithms.

Two-dimensional obstacle avoidance control algorithm for snake-like robot in water based on immersed boundary-lattice Boltzmann method and improved artificial potential field method

2020 ◽  
Vol 42 (10) ◽  
pp. 1840-1857
Author(s):  
Dongfang Li ◽  
Zhenhua Pan ◽  
Hongbin Deng
Keyword(s):  
Flow Field ◽  
Obstacle Avoidance ◽  
Lattice Boltzmann ◽  
Potential Field ◽  
Control Algorithm ◽  
Immersed Boundary ◽  
Artificial Potential Field ◽  
Two Dimensional ◽  
Avoidance Control ◽  
Boltzmann Method

In order to study the adaptability of a multi-redundancy and multi-degree-of-freedom snake-like robot to underwater motion, a two-dimensional (2-D) obstacle avoidance control algorithm for a snake-like robot based on immersed boundary-lattice Boltzmann method (IB-LBM) and improved artificial potential field (APF) is proposed in this paper. Firstly, the non-linear flow field model is established under the framework of LBM, and the IB method is introduced to establish a fluid solid coupling of a 2-D soft snake-like robot. Then, the obstacle avoidance of a snake-like robot in a flow field is realized by optimizing the curvature equation of the serpentine curve and eliminating the local minimum in APF method. Finally, the effects by exerted different control parameters on a snake-like robot’s obstacle avoidance capability are analyzed via MATLAB simulation experiment, by which we can find the optimal parameter of the obstacle avoidance and testify the validity of the proposed control algorithm.

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 Formation control of UAVs based on artificial potential field

2018 ◽  
Vol 189 ◽  
pp. 10018
Author(s):  
Yongshen Lv ◽  
Xuerong Yang ◽  
Yajun Yang ◽  
Shengdong Pan ◽  
Chaojun Xin
Keyword(s):  
Kinetic Model ◽  
Potential Field ◽  
Formation Control ◽  
Control Algorithm ◽  
Simulation Experiment ◽  
Control Method ◽  
Artificial Potential Field ◽  
Field Function ◽  
Time Performance ◽  
Matching Rules

The problem of UAVs’ formation control in the process of motion is investigated in this paper. A formation control method based on artificial potential field of UAVs is proposed, established on the collision avoidance, aggregation and speed matching rules of UAVs. First establish the UAVs’ kinetic model in accordance to the motion rules, then design the formation control algorithm based on artificial potential field function, which is used to control the formation during the movement of UAVs. Finally, the results of simulation experiment show that the proposed formation control method in this paper is effective and has the advantages of easy realization, good real-time performance and excellent robustness.

Research on Multi-Agent Formation’s Obstacle Avoidance Problem Based on Three-Dimensional Vectorial Artificial Potential Field Method

2014 ◽  
Vol 596 ◽  
pp. 251-258 ◽  
Author(s):  
Ji Yang Dai ◽  
Lin Fei Yin ◽  
Chen Peng ◽  
Bao Jian Yang ◽  
Cun Song Wang
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Three Dimensional ◽  
Field Method ◽  
Artificial Potential Field ◽  
Potential Field Method ◽  
Pyramid Structure ◽  
Multi Agent ◽  
Artificial Potential Field Method ◽  
Avoidance Problem

In order to solve the obstacle avoidance problem when the Multi-Agent formation get through the area full of obstacles, improved the traditional Artificial Potential Field method, add the vectorial information to the agent’s model, presented the Three-Dimensional Vectorial Artificial Potential Field method (TDVAPF). Firstly, improved the model of agent, obstacle and target; then, improved the Multi-Agent formation motion model, the Multi-Agent formation’s structure is “pyramid” structure; Finally, improved the agent’s force, add the “rotational force” to the agent’s force, it makes agent avoid the “local trouble”. The numerical simulation verified the correctness and effectiveness of the TDVAPF method in Multi-Agent formation’s obstacle avoidance problem.

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