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.

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.

A Novel Approach for Path Planning Based on Reactive Behavior-Artificial Potential Filed

2014 ◽  
Vol 529 ◽  
pp. 646-649 ◽  
Author(s):  
Long Xiang Yang ◽  
Zai Xin Liu ◽  
Hao Tang
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Real Time ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Optimal Selection ◽  
Local Minima ◽  
Novel Approach ◽  
Reactive Behavior ◽  
Real Time Application

The main objective of this paper is to focus on the local minima and the GNRON issues encountered in path planning by the artificial potential field (APF) method, and propose a novel approach to plan a trajectory adaptive for the environment that the obstacles are randomly distributed. By introducing the ideas of reactive behaviors (RB), the RB-APF method is presented, which combines the efficiency of the APF with the simplicity of the RB, so it can be suitable for real-time application in mobile robots. In this algorithm (RB-APF), the switch conditions and optimal selection equations are reasonably designed with the consideration of the different circumstances of the robot located in. Simulations are presented and the results further demonstrate that the proposed approach is applicable for the environment that obstacles are randomly distributed.

Vision Based Path Planning for Mobile Robot Using Extrapolated Artificial Potential Field and Probabilistic Obstacle Avoidance

2002 ◽  
Author(s):  
Waqar A. Malik ◽  
Jae-Yong Lee ◽  
Sooyong Lee
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Collision Detection ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Robot Path Planning ◽  
Moving Obstacles ◽  
Novel Method ◽  
Robot Path

Mobile robots are increasingly being used to do tasks in unknown environment. The potential of robots to undertake such tasks lies on their ability to intelligently and efficiently locate and interact with objects in their environment. This paper describes a novel method to plan paths for mobile robots in a partially known environment observed by an overhead camera. The environment consists of dynamic obstacles and targets. A new methodology, Extrapolated Artificial Potential Field is proposed for real time robot path planning. The proposed Extrapolated Artificial Potential Field is capable of navigating robots situated among moving obstacles and target. An algorithm for probabilistic collision detection is introduced. The paper summarizes this approach, and discusses the results of path planning experiments using an Amigobot. The result shows that our method is effective.

scholarly journals Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 188 ◽  
Author(s):  
Qing Wu ◽  
Zeyu Chen ◽  
Lei Wang ◽  
Hao Lin ◽  
Zijing Jiang ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Real Time ◽  
Potential Field ◽  
Optimization Method ◽  
Artificial Potential Field ◽  
Planning Time ◽  
Time Dynamic ◽  
Dynamic Path Planning ◽  
Dynamic Path

Mobile robots are becoming more and more widely used in industry and life, so the navigation of robots in dynamic environments has become an urgent problem to be solved. Dynamic path planning has, therefore, received more attention. This paper proposes a real-time dynamic path planning method for mobile robots that can avoid both static and dynamic obstacles. The proposed intelligent optimization method can not only get a better path but also has outstanding advantages in planning time. The algorithm used in the proposed method is a hybrid algorithm based on the beetle antennae search (BAS) algorithm and the artificial potential field (APF) algorithm, termed the BAS-APF method. By establishing a potential field, the convergence speed is accelerated, and the defect that the APF is easily trapped in the local minimum value is also avoided. At the same time, by setting a security scope to make the path closer to the available path in the real environment, the effectiveness and superiority of the proposed method are verified through simulative results.

Sign in / Sign up

Export Citation Format

Share Document