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.

Design Research on Vehicle Collision Avoidance Based on Artificial Potential Field

2012 ◽  
Vol 271-272 ◽  
pp. 727-731 ◽  
Author(s):  
Ying Jie Liu ◽  
You Qun Zhao ◽  
Xiao Feng Zhou
Keyword(s):  
Collision Avoidance ◽  
Potential Function ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Design Research ◽  
Driving Safety ◽  
Artificial Potential Field ◽  
The Road ◽  
Vehicle Collision ◽  
Avoidance Problem

Vehicle driving safety is the urgent key problem to be solved of automobile independent development while encountering collision avoidance. It is also the premise and one of the necessary conditions of vehicle active safety. A new technique for vehicle collision avoidance was proposed. Based on the artificial potential field theory, the lane potential, the road potential function and the obstacle potential function as well as the velocity potential function of the vehicle were constructed. Then the potential function of the vehicle obstacle avoidance problem was constructed with the three potential functions above. The vehicle obstacle avoidance problem was then converted into an optimization problem. The trajectory of the vehicle in the obstacle avoidance process was obtained by solving the optimal control problem. The simulation results show that the proposed method can solve the collision avoidance problem and provide the lane keeping and lane change problem with theoretical support

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.

Multi-Robot Obstacle Avoidance Based on the Improved Artificial Potential Field and PID Adaptive Tracking Control Algorithm

Robotica ◽  
2019 ◽  
Vol 37 (11) ◽  
pp. 1883-1903 ◽  
Author(s):  
Zhenhua Pan ◽  
Dongfang Li ◽  
Kun Yang ◽  
Hongbin Deng
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Tracking Control ◽  
Formation Control ◽  
Control Algorithm ◽  
Situational Awareness ◽  
Artificial Potential Field ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking ◽  
Multi Robot

SummaryAs for the obstacle avoidance and formation control for the multi-robot systems, this paper presents an obstacle-avoidance method based on the improved artificial potential field (IAPF) and PID adaptive tracking control algorithm. In order to analyze the dynamics and kinematics of the robot, the mathematical model of the robot is built. Then we construct the motion situational awareness map (MSAM), which can map the environment information around the robot on the MSAM. Based on the MSAM, the IAPF functions are established. We employ the rotating potential field to solve the local minima and oscillations. As for collisions between robots, we build the repulsive potential function and priority model among the robots. Afterwards, the PID adaptive tracking algorithm is utilized to multi-robot formation control. To demonstrate the validity of the proposed method, a series of simulation results confirm that the approaches proposed in this paper can successfully address the obstacle- and collision-avoidance problem while reaching formation.

Multi-Robot Formation Control Based on the Artificial Potential Field Method

2014 ◽  
Vol 519-520 ◽  
pp. 1360-1363 ◽  
Author(s):  
Xi Na Gao ◽  
Li Juan Wu
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Formation Control ◽  
Field Method ◽  
Artificial Potential Field ◽  
Control Methods ◽  
Potential Field Method ◽  
Artificial Potential Field Method ◽  
Multi Robot

The artificial potential field method is one of multi-robot formation control methods. In this paper we make a study on multi-robot formation control based on the artificial potential field method and the leader-follower method. The robots are set leader robot and follower robots respectively. According to the known ideal distance between the leader and follower, we adjust the repulsiveness or attractiveness to maintain multi-robot formation. Multi-robots obstacle avoidance is adopted the artificial potential field method. In this paper the triangle formation is taken as an example. At last the simulation result proves the validity of this algorithm.

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 Analysis of Obstacle Avoidance Strategy for Dual-Arm Robot Based on Speed Field with Improved Artificial Potential Field Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1850
Author(s):  
Hui Zhang ◽  
Yongfei Zhu ◽  
Xuefei Liu ◽  
Xiangrong Xu
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Planning Methods ◽  
Avoidance Strategy ◽  
Dual Arm Robot ◽  
Dual Arm ◽  
Avoidance Problem

In recent years, dual-arm robots have been favored in various industries due to their excellent coordinated operability. One of the focused areas of study on dual-arm robots is obstacle avoidance, namely path planning. Among the existing path planning methods, the artificial potential field (APF) algorithm is widely applied in obstacle avoidance for its simplicity, practicability, and good real-time performance over other planning methods. However, APF is firstly proposed to solve the obstacle avoidance problem of mobile robot in plane, and thus has some limitations such as being prone to fall into local minimum, not being applicable when dynamic obstacles are encountered. Therefore, an obstacle avoidance strategy for a dual-arm robot based on speed field with improved artificial potential field algorithm is proposed. In our method, the APF algorithm is used to establish the attraction and repulsion functions of the robotic manipulator, and then the concepts of attraction and repulsion speed are introduced. The attraction and repulsion functions are converted into the attraction and repulsion speed functions, which mapped to the joint space. By using the Jacobian matrix and its inverse to establish the differential velocity function of joint motion, as well as comparing it with the set collision distance threshold between two robotic manipulators of robot, the collision avoidance can be solved. Meanwhile, after introducing a new repulsion function and adding virtual constraint points to eliminate existing limitations, APF is also improved. The correctness and effectiveness of the proposed method in the self-collision avoidance problem of a dual-arm robot are validated in MATLAB and Adams simulation environment.

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