scholarly journals A Balance-Artificial Potential Field Method for Autonomous Surface Vessel Navigation in Unstructured Riverine Environment

2015 ◽  
Vol 76 ◽  
pp. 198-202 ◽  
Author(s):  
Mei Jian Hong ◽  
M.R. Arshad
Keyword(s):  
Potential Field ◽  
Field Method ◽  
Artificial Potential Field ◽  
Potential Field Method ◽  
Riverine Environment ◽  
Surface Vessel ◽  
Artificial Potential Field Method

A MODIFIED ARTIFICIAL POTENTIAL FIELD METHOD FOR RIVERINE OBSTACLES AVOIDANCE

2016 ◽  
Vol 78 (6-13) ◽  
Author(s):  
Mei Jian Hong ◽  
M. R. Arshad
Keyword(s):  
Potential Field ◽  
Balance Control ◽  
Field Method ◽  
Artificial Potential Field ◽  
Potential Field Method ◽  
Control Scheme ◽  
Riverine Environment ◽  
Simulation Results ◽  
Surface Vessel ◽  
Artificial Potential Field Method

This paper presents a modified artificial potential field (APF) based method for an Autonomous Surface Vessel (ASV) obstacles avoidance in a dynamic riverine environment. The APF method is combined with a balance control scheme to achieve river tracking and obstacles avoidance simultaneously. The APF method is further modified modification to comply with marine collision avoidance regulations (COLREGs). The overtaking and head-on scenarios are simulated in MATLAB platform. The simulation results are compared with other APF methods to prove that the proposed method is efficient for the ASV riverine navigation. 

Route planning of intelligent bridge cranes based on an improved artificial potential field method

2021 ◽  
pp. 1-8
Author(s):  
Zhengyan Chang ◽  
Zhengwei Zhang ◽  
Qiang Deng ◽  
Zheren Li
Keyword(s):  
Potential Field ◽  
Autonomous Navigation ◽  
Route Planning ◽  
Simple Algorithm ◽  
Field Method ◽  
Artificial Potential Field ◽  
Planning Problem ◽  
Operating Characteristics ◽  
Potential Field Method ◽  
Artificial Potential Field Method

The artificial potential field method is usually applied to the path planning problem of driverless cars or mobile robots. For example, it has been applied for the obstacle avoidance problem of intelligent cars and the autonomous navigation system of storage robots. However, there have been few studies on its application to intelligent bridge cranes. The artificial potential field method has the advantages of being a simple algorithm with short operation times. However, it is also prone to problems of unreachable targets and local minima. Based on the analysis of the operating characteristics of bridge cranes, a two-dimensional intelligent running environment model of a bridge crane was constructed in MATLAB. According to the basic theory of the artificial potential field method, the double-layer artificial potential field method was deduced, and the path and track fuzzy processing method was proposed. These two methods were implemented in MATLAB simulations. The results showed that the improved artificial potential field method could avoid static obstacles efficiently.

scholarly journals Improved Artificial Potential Field and Dynamic Window Method for Amphibious Robot Fish Path Planning

2021 ◽  
Vol 11 (5) ◽  
pp. 2114
Author(s):  
Wenlin Yang ◽  
Peng Wu ◽  
Xiaoqi Zhou ◽  
Haoliang Lv ◽  
Xiaokai Liu ◽  
...  
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Local Minimum ◽  
Field Method ◽  
Artificial Potential Field ◽  
Evaluation Function ◽  
Potential Field Method ◽  
Robot Fish ◽  
Amphibious Robot ◽  
Artificial Potential Field Method

Aiming at the problems of “local minimum” and “unreachable target” existing in the traditional artificial potential field method in path planning, an improved artificial potential field method was proposed after analyzing the fundamental causes of the above problems. The method solved the problem of local minimum by modifying the direction and influence range of the gravitational field, increasing the virtual target and evaluation function, and the problem of unreachable targets is solved by increasing gravity. In view of the change of motion state of robot fish in amphibious environments, the improved artificial potential field method was fused with a dynamic window algorithm, and a dynamic window evaluation function of the optimal path was designed on the basis of establishing the dynamic equations of land and underwater. Then, the simulation experiment was designed under the environment of Matlab2019a. Firstly, the improved and traditional artificial potential field methods were compared. The results showed that the improved artificial potential field method could solve the above two problems well, shorten the operation time and path length, and have high efficiency. Secondly, the influence of different motion modes on path planning is verified, and the result also reflects that the amphibious robot can avoid obstacles flexibly and reach the target point accurately according to its own motion ability. This paper provides a new way of path planning for the amphibious robot.

Improved Artificial Potential Field Method Manipulator Inverse Kinematics

2013 ◽  
Vol 273 ◽  
pp. 119-123
Author(s):  
Ding Jin Huang ◽  
Teng Liu
Keyword(s):  
Potential Field ◽  
Inverse Kinematics ◽  
Search Space ◽  
Field Method ◽  
Robotic Arm ◽  
Artificial Potential Field ◽  
Robot Arm ◽  
Potential Field Method ◽  
Inverse Kinematics Problem ◽  
Artificial Potential Field Method

The use of traditional analytical method for manipulator inverse kinematics is able to get a display solution with the limitations of the application, only when the robotic arm has a specific structure. In view of the insufficient, this paper presents an improved artificial potential field method to solve the inverse kinematics problem of the manipulator which does not have a special structure. Firstly, establish the standard DH model for the robot arm. Then the strategy that improves search space of artificial potential field method and motion control standard is presented by combining artificial potential field method with the manipulator. Finally, the simulation results show that the proposed method is effective.

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