scholarly journals Research on Global Dynamic Path Planning Method Based on Improved A ∗ Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Chuanhu Niu ◽  
Aijuan Li ◽  
Xin Huang ◽  
Wei Li ◽  
Chuanyan Xu
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Planning Method ◽  
Intelligent Vehicle ◽  
Global Dynamic ◽  
Dynamic Path Planning ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Path ◽  
Dynamic Obstacle

Aiming at the optimal path and planning efficiency of global path planning for intelligent driving, this paper proposes a global dynamic path planning method based on improved A ∗ algorithm. First, this method improves the heuristic function of the traditional A ∗ algorithm to improve the efficiency of global path planning. Second, this method uses a path optimization strategy to make the global path smoother. Third, this method is combined with the dynamic window method to improve the real-time performance of the dynamic obstacle avoidance of the intelligent vehicle. Finally, the global dynamic path planning method of the proposed improved A ∗ algorithm is verified through simulation experiments and real vehicle tests. In the simulation analysis, compared with the modified A ∗ algorithm and the traditional A ∗ algorithm, the method in this paper shortens the path distance by 2.5%∼3.0%, increases the efficiency by 10.3%∼13.6% and generates a smoother path. In the actual vehicle test, the vehicle can avoid dynamic obstacles in real time. Therefore, the method proposed in this paper can be applied on the intelligent vehicle platform. The path planning efficiency is high, and the dynamic obstacle avoidance is good in real time.

scholarly journals A New Hybrid Method in Global Dynamic Path Planning of Mobile Robot

2018 ◽  
Vol 13 (6) ◽  
pp. 1032-1046 ◽  
Author(s):  
Xiaoru Song ◽  
Song Gao ◽  
C.B. Chen ◽  
Kai Cao ◽  
Jiaoru Huang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Real Time ◽  
Obstacle Avoidance ◽  
A Algorithm ◽  
Fusion Algorithm ◽  
Global Dynamic ◽  
Dynamic Path Planning ◽  
Dynamic Path ◽  
Dynamic Obstacle

Path planning and real-time obstacle avoidance is the key technologies of mobile robot intelligence. But the efficiency of the global path planning is not very high. It is not easy to avoid obstacles in real time. Aiming at these shortcomings it is proposed that a global dynamic path planning method based on improved A* algorithm and dynamic window method. At first the improved A* algorithm is put forward based on the traditional A* algorithm in the paper. Its optimized heuristic search function is designed. They can be eliminated that the redundant path points and unnecessary turning points. Simulation experiment 1 results show that the planned path length is reduced greatly. And the path transition points are less, too. And then it is focused on the global dynamic path planning of fusion improved A* Algorithm and Dynamic Window Method. The evaluation function is constructed taking into account the global optimal path. The real time dynamic path is planning. On the basis of ensuring the optimal global optimization of the planning path, it is improved that the smoothness of the planning path and the local real-time obstacle avoidance ability. The simulation experiments results show that the fusion algorithm is not only the shorter length, but also the smoother path compared the traditional path planning algorithms with the fusion algorithm in the paper. It is more fit to the dynamics of the robot control. And when a dynamic obstacle is added, the new path can be gained. The barrier can be bypass and the robot is to reach the target point. It can be guaranteed the global optimality of the path. Finally the Turtlebot mobile robot was used to experiment. The experimental results show that the global optimality of the proposed path can be guaranteed by the fusion algorithm. And the planned global path is smoother. When the random dynamic obstacle occurs in the experiment, the robot can be real-time dynamic obstacle avoidance. It can re-plan the path. It can bypass the random obstacle to reach the original target point. The outputting control parameters are more conducive to the robot’s automatic control. The fusion method is used for global dynamic path planning of mobile robots in this paper. In summary the experimental results show that the method is good efficiency and real-time performance. It has great reference value for the dynamic path planning application of mobile robot.

scholarly journals Research on Local Dynamic Path Planning Method for Intelligent Vehicle Lane-Changing

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Zhi-qiang Liu ◽  
Teng Zhang ◽  
Yi-fan Wang
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Planning Method ◽  
Local Dynamic ◽  
Vehicle Speed ◽  
Lane Changing ◽  
Dynamic Path Planning ◽  
Dynamic Path ◽  
Real Time Information ◽  
Time Information

A local dynamic path planning method is proposed to compensate for the lack of consideration of the movement state of surrounding vehicles, the poor comfort, and the low traffic efficiency when the existing vehicle changes lanes automatically. Firstly, the cubic polynomial is predefined, and the optimal track path is solved. According to the real-time information of environment perception, the model is continuously modified by acquiring real-time information in the course of path planning, and the regional safety of the vehicle is realized. The Carsim and simulink simulation results and actual vehicle verification show that, compared with the traditional nondynamic research method, this method can effectively solve the problem that the vehicle speed variation and the sudden intrusions of the vehicle leading to the compulsory operation of the vehicle during the course of lane-changing. The safety is also improved. In order to ensure the vehicle comfort and stability, the lane-changing time is shortened by 20%, and the efficiency of lane-changing is improved obviously.

scholarly journals Global Dynamic Path Planning Fusion Algorithm Combining Jump-A* Algorithm and Dynamic Window Approach

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 19632-19638
Author(s):  
Lisang Liu ◽  
Jinxin Yao ◽  
Dongwei He ◽  
Jian Chen ◽  
Jing Huang ◽  
...  
Keyword(s):  
Path Planning ◽  
A Algorithm ◽  
Fusion Algorithm ◽  
Global Dynamic ◽  
Dynamic Path Planning ◽  
Dynamic Path ◽  
Window Approach

scholarly journals New Algorithm for Autonomous Dynamic Path Planning in Real-Time Intelligent Robot Car

2017 ◽  
Vol 14 (11) ◽  
pp. 5499-5507
Author(s):  
Aqeel A. Mohammed ◽  
Ishak Aris ◽  
Mohd Khair Hassan ◽  
Noor Ain Kamsani
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Intelligent Robot ◽  
Dynamic Path Planning ◽  
Dynamic Path

scholarly journals A Novel Vector-Based Dynamic Path Planning Method in Urban Road Network

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 9046-9060
Author(s):  
Zhi Cai ◽  
Xuerui Cui ◽  
Xing Su ◽  
Qing Mi ◽  
Limin Guo ◽  
...  
Keyword(s):  
Path Planning ◽  
Road Network ◽  
Planning Method ◽  
Urban Road Network ◽  
Urban Road ◽  
Dynamic Path Planning ◽  
Dynamic Path

scholarly journals Dynamic Path Planning for Bevel-Tip Flexible Needle Insertion into Soft Tissue Based on a Real-Time Finite Element Model

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Murong Li ◽  
Dedong Gao ◽  
Yong Lei ◽  
Tian Xu
Keyword(s):  
Finite Element ◽  
Soft Tissue ◽  
Path Planning ◽  
Finite Element Model ◽  
Real Time ◽  
Ccd Camera ◽  
Element Model ◽  
Online Planning ◽  
Dynamic Path Planning ◽  
Dynamic Path

This paper presents a novel dynamic path planning methodology for needle steering into the soft tissue. A real-time finite element model is used to simulate the procedure of a flexible needle into the homogeneous soft tissue, which provides the dynamic deformation information for the path planning. The relationship between needle base and tip is formulated as the transformations of homogeneous matrix with quasi-static assumptions. Based on the reachability of the flexible needle, the real-time motions of obstacles and target are considered through the dynamic needle-tissue interactions. A testbed including a XY linear stage, one rotator, and a CCD camera is constructed, and the experiments are designed to validate the proposed method. The 23G PTC needle was inserted into the PVA phantom with markers, and the CCD camera was utilized to record the needle trajectories and motions of target and obstacles. The targeting errors between the experimental and planned paths are less than 1.20 mm, and the distance from the obstacle to needle is not smaller than 1.16 mm. The results demonstrate that the proposed algorithm is effective for online planning the paths in the needle-tissue interactive environment.

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