Artificial Potential Field and Ship Maneuverability based Collision Avoidance Path Planning

2020 ◽  
Author(s):  
Dengjun Huang ◽  
Zhengjiang Liu ◽  
Xin Wang
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Ship Maneuverability

scholarly journals A Study on Path Planning Algorithms of UAV Collision Avoidance

2019 ◽  
Vol 37 (1) ◽  
pp. 100-106
Author(s):  
Zhao Xu ◽  
Jinwen Hu ◽  
Yunhong Ma ◽  
Man Wang ◽  
Chunhui Zhao
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Potential Field ◽  
Ant Colony Algorithm ◽  
Artificial Potential Field ◽  
Fuzzy Logic Algorithm ◽  
Aerial Vehicle ◽  
Simulation Results ◽  
Planning Algorithms ◽  
Dynamic Obstacle

The unmanned aerial vehicle (UAV) has been a research hotspot worldwide. The UAV system is developing to be more and more intelligent and autonomous. UAV path planning is an important part of UAV autonomous control and the important guarantee of UAV's safety. For the purpose of improving the collision avoidance and path planning algorithms, the artificial potential field, fuzzy logic algorithm and ant colony algorithm are simulated respectively in the static obstacle and dynamic obstacle environments, and compared based on the minimum avoidance distance and range ratio. Meanwhile, an improved algorithm of artificial potential field is proposed, and the improvement helps the UAV escape the local minimum by introducing the vertical guidance repulsion. The simulation results are rigorous and reliable, which lay a foundation for the further fusion of multiple algorithms and improving the path planning algorithms.

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.

scholarly journals Research on path planning of three-neighbor search A* algorithm combined with artificial potential field

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110264
Author(s):  
Jiqing Chen ◽  
Chenzhi Tan ◽  
Rongxian Mo ◽  
Hongdu Zhang ◽  
Ganwei Cai ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Path Length ◽  
Search Time ◽  
Experimental Results ◽  
Artificial Potential Field ◽  
A Algorithm ◽  
Neighbor Search

Among the shortcomings of the A* algorithm, for example, there are many search nodes in path planning, and the calculation time is long. This article proposes a three-neighbor search A* algorithm combined with artificial potential fields to optimize the path planning problem of mobile robots. The algorithm integrates and improves the partial artificial potential field and the A* algorithm to address irregular obstacles in the forward direction. The artificial potential field guides the mobile robot to move forward quickly. The A* algorithm of the three-neighbor search method performs accurate obstacle avoidance. The current pose vector of the mobile robot is constructed during obstacle avoidance, the search range is narrowed to less than three neighbors, and repeated searches are avoided. In the matrix laboratory environment, grid maps with different obstacle ratios are compared with the A* algorithm. The experimental results show that the proposed improved algorithm avoids concave obstacle traps and shortens the path length, thus reducing the search time and the number of search nodes. The average path length is shortened by 5.58%, the path search time is shortened by 77.05%, and the number of path nodes is reduced by 88.85%. The experimental results fully show that the improved A* algorithm is effective and feasible and can provide optimal results.

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