scholarly journals Experimental Test of Artificial Potential Field-Based Automobiles Automated Perpendicular Parking

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Yiqun Dong ◽  
Youmin Zhang ◽  
Jianliang Ai
Keyword(s):  
Potential Field ◽  
Artificial Potential Field ◽  
Test Results ◽  
Unmanned Ground Vehicle ◽  
Motion Controller ◽  
Ground Vehicle ◽  
Turning Radius ◽  
Minimum Turning Radius ◽  
Radius Constraint ◽  
Path Modification

Automobiles automated perpendicular parking using Artificial Potential Field (APF) is discussed in this paper. The Unmanned Ground Vehicle (UGV) used for carrying out experiments is introduced first; UGV configuration, kinematics, and motion controller are included. Based on discretized form of the parking space, the APF is generated. Holonomic path for the vehicle parking is found first; path modification to satisfy minimum turning-radius constraint is performed based on Reeds-Shepp curve connections. Optimization efforts are included to remove extra maneuvers and to reduce length of the path. Afterwards waypoints are generated as reference for the vehicle to track. Perpendicular parking tests with several different start configurations are demonstrated; based on the test results the automated parking framework proposed in this paper is considered to be effective.

Measuring Theory Research on the Automobile Steering Angle Automatic Measuring System

2013 ◽  
Vol 655-657 ◽  
pp. 731-734
Author(s):  
Hu Dai Fu ◽  
Zheng Zhong Wang
Keyword(s):  
Steering System ◽  
Measuring System ◽  
Test Results ◽  
Automatic Measuring ◽  
Steering Angle ◽  
Turning Radius ◽  
Minimum Turning Radius ◽  
Theory Research ◽  
Infrared Tracking ◽  
Measuring Plate

It is studied that a great proportion of traffic problems lies in vehicles’ steering system, and the maximum steering angle decides their steering capability and their minimum turning radius. The measuring principle of rapid measuring system, and the automatic tracking principle of measurement system have been analyzed in the paper. Also, the infrared tracking, the measuring plate positioning, the calculation of minimum turning radius, and the processing method of the test results have been described in detail. It is proved that the automatic automobile steering angle detecting system has reached the general requirements both in detection resolution and the measuring accuracy.

scholarly journals Path Planning Based on Improved Hybrid A* Algorithm

2021 ◽  
Vol 25 (1) ◽  
pp. 64-72
Author(s):  
Bijun Tang ◽  
◽  
Kaoru Hirota ◽  
Xiangdong Wu ◽  
Yaping Dai ◽  
...  
Keyword(s):  
Operating System ◽  
Path Planning ◽  
Mobile Robots ◽  
Potential Field ◽  
Artificial Potential Field ◽  
A Algorithm ◽  
Ground Vehicle ◽  
Holonomic Constraints ◽  
Robot Operating System ◽  
Maximum Curvature

Hybrid A* algorithm has been widely used in mobile robots to obtain paths that are collision-free and drivable. However, the outputs of hybrid A* algorithm always contain unnecessary steering actions and are close to the obstacles. In this paper, the artificial potential field (APF) concept is applied to optimize the paths generated by the hybrid A* algorithm. The generated path not only satisfies the non-holonomic constraints of the vehicle, but also is smooth and keeps a comfortable distance to the obstacle at the same time. Through the robot operating system (ROS) platform, the path planning experiments are carried out based on the hybrid A* algorithm and the improved hybrid A* algorithm, respectively. In the experiments, the results show that the improved hybrid A* algorithm greatly reduces the number of steering actions and the maximum curvature of the paths in many different common scenarios. The paths generated by the improved algorithm nearly do not have unnecessary steering or sharp turning before the obstacles, which are safer and smoother than the paths generated by the hybrid A* algorithm for the autonomous ground vehicle.

Design and Realization of an All-terrain Unmanned Ground Vehicle

ROBOT ◽  
2013 ◽  
Vol 35 (6) ◽  
pp. 657 ◽  
Author(s):  
Taoyi ZHANG ◽  
Tianmiao WANG ◽  
Yao WU ◽  
Qiteng ZHAO
Keyword(s):  
Unmanned Ground Vehicle ◽  
Ground Vehicle

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.

Unmanned Ground Vehicle for Security and Surveillance

2020 ◽  
Author(s):  
Prajot P. Kulkarni ◽  
Shubham R. Kutre ◽  
Shravan S. Muchandi ◽  
Pournima Patil ◽  
Shankargoud Patil
Keyword(s):  
Unmanned Ground Vehicle ◽  
Ground Vehicle

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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