A Study on Looking for Shortest Trajectory of Mobile Robot Using A* Algorithm

2017 ◽  
pp. 617-626
Author(s):  
Duy Lan Bui ◽  
Tri Cong Phung
Keyword(s):  
Mobile Robot ◽  
A Algorithm

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.

scholarly journals Navigation Simulation of a Mecanum Wheel Mobile Robot Based on an Improved A* Algorithm in Unity3D

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2976 ◽  
Author(s):  
Yunwang Li ◽  
Sumei Dai ◽  
Yong Shi ◽  
Lala Zhao ◽  
Minghua Ding
Keyword(s):  
Mobile Robot ◽  
Effective Means ◽  
Three Dimensional ◽  
Simulation Method ◽  
Virtual Prototype ◽  
Visual Navigation ◽  
A Algorithm ◽  
Navigation Algorithm ◽  
Navigation Simulation ◽  
Mecanum Wheel

Computer simulation is an effective means for the research of robot navigation algorithms. In order to implement real-time, three-dimensional, and visual navigation algorithm simulation, a method of algorithm simulation based on secondary development of Unity3D is proposed. With this method, a virtual robot prototype can be created quickly with the imported 3D robot model, virtual joints, and virtual sensors, and then the navigation simulation can be carried out using the virtual prototype with the algorithm script in the virtual environment. Firstly, the scripts of the virtual revolute joint, virtual LiDAR sensors, and terrain environment are written. Secondly, the A* algorithm is improved for navigation in unknown 3D space. Thirdly, taking the Mecanum wheel mobile robot as an example, the 3D robot model is imported into Unity3D, and the virtual joint, sensor, and navigation algorithm scripts are added to the model. Then, the navigation is simulated in static and dynamic environments using a virtual prototype. Finally, the navigation tests of the physical robot are carried out in the physical environment, and the test trajectory is compared with the simulation trajectory. The simulation and test results validate the algorithm simulation method based on the redevelopment of Unity3d, showing that it is feasible, efficient, and flexible.

A Proposed Trajectory Planning Algorithm for Mobile Robot Navigation Based on A* Algorithm

2020 ◽  
pp. 361-376
Author(s):  
Şahin Yıldırım ◽  
Sertaç Savaş
Keyword(s):  
Mobile Robot ◽  
Trajectory Planning ◽  
Heuristic Method ◽  
Working Environment ◽  
Mobile Robot Navigation ◽  
A Algorithm ◽  
Grid Map ◽  
Planning Approach ◽  
Planning Algorithm ◽  
Path Planning Algorithm

This chapter proposes a new trajectory planning approach by improving A* algorithm, which is a widely-used, path-planning algorithm. This algorithm is a heuristic method used in maps such as the occupancy grid map. As the resolution increases in these maps, obstacles can be defined more precisely. However, the cell/grid size must be larger than the size of the mobile robot to prevent the robot from crashing into the borders of the working environment or obstacles. The second constraint of the algorithm is that it does not provide continuous headings. In this study, an avoidance area is calculated on the map for the mobile robot to avoid collisions. Then curve-fitting methods, general polynomial and b-spline, are applied to the path calculated by traditional A* algorithm to obtain smooth rotations and continuous headings by staying faithful to the original path calculated. Performance of the proposed trajectory planning method is compared to others for different target points on the grid map by using a software developed in Labview Environment.

GA-based Global Path Planning for Mobile Robot Employing A* Algorithm

2012 ◽  
Vol 7 (2) ◽  
Author(s):  
Cen Zeng ◽  
Qiang Zhang ◽  
Xiaopeng Wei
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
A Algorithm ◽  
Global Path Planning
Sign in / Sign up

Export Citation Format

Share Document