A Reasonable Path Planning via Path Energy Minimization

2014 ◽  
Vol 26 (2) ◽  
pp. 236-244 ◽  
Author(s):  
Masashi Yokozuka ◽  
◽  
Osamu Matsumoto
Keyword(s):  
Path Planning ◽  
Energy Minimization ◽  
Planning Method ◽  
Motion Prediction ◽  
A Algorithm ◽  
Near Misses ◽  
Shortest Distance ◽  
Path Switching ◽  
Dynamic Obstacle ◽  
Minimum Curvature

This paper presents a path planning method by path energy minimizing that enables mobile robots to move smoothly in the real world with optimizing path shape for shortest distance or minimum curvature. It also enables robots to travel safely toward a destination because pedestrian motion prediction is embedded in path planning. This path planning method is based on problems experienced in a robot competition called Tsukuba Challenge. The problems involved nonsmooth motion arising from finite path patterns in A* algorithm, stuck motion arising from frequently path switching, and near misses arising from nonpredictive planning. Our path planning method minimizes pathshape energy defined as the connection between path points. Minimizing energy provides smooth paths and avoids path switching. We propose a path planning method with prediction of dynamic obstacle motion embedded to avoid near misses. Experimental results showed improvements in solving these problems.

A Method of Ship’s Path Planning at Sea

2013 ◽  
Vol 321-324 ◽  
pp. 2038-2041
Author(s):  
Yuan Liang Zhang
Keyword(s):  
Information System ◽  
Path Planning ◽  
Planning Method ◽  
A Algorithm ◽  
Optimum Trajectory ◽  
Optimization Task ◽  
Route Design ◽  
Electronic Chart

Automatic route design will help to develop electronic chart intelligence, hence to improve safety, economy and reliability of the route. In the paper rasterizing charts are used to expressed the navigation environment of the ship and the modified A* algorithm is used to compute the near optimum trajectory of a ship in given environment based on electronic chart dispiay and information system (ECDIS). By tracing Safety contours, computing obstacle areas and taking into account certain boundaries of the manoeuvring region, the problem of avoiding collisions at sea was reduced to optimization task with static constrains. Simulation using MATLAB is conducted to verify the proposed ship path planning method. The good results show the promise of this method for ship at sea.

Path Planning for Ground Simulation Objiect Based on A* Algorithm

2012 ◽  
Vol 229-231 ◽  
pp. 2019-2024 ◽  
Author(s):  
Zhi Qiang Zhao ◽  
Zhi Hua Liu ◽  
Jia Xin Hao
Keyword(s):  
Path Planning ◽  
Large Scale ◽  
Optimal Path ◽  
Planning Method ◽  
Heuristic Function ◽  
A Algorithm

In the process of ground simulation object maneuver simulation in large-scale operation simulation, an efficient path planning method based on A*algorithm is proposed. By means of introducing all kind of geography factors and security factors into heuristic function, the plan reaching method solves the problem of finding an optimal path under acquiring enemy's situation and terrain data. Experiment results show that it has effectively raised path planning speed of A* algorithm and the scheme is practical and feasible.

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 Matlab-Realized Visual A* Path Planning Teaching Platform

2018 ◽  
Vol 13 (10) ◽  
pp. 196
Author(s):  
Mingfeng Luo
Keyword(s):  
Path Planning ◽  
Teaching Method ◽  
Search Space ◽  
Planning Method ◽  
Simulation Platform ◽  
Parameter Setting ◽  
A Algorithm ◽  
Teaching Platform ◽  
Multimedia Teaching ◽  
Algorithm Search

Path planning in the global known environment is one of the main prob-lems in the field of mobile robots. Based on the characteristics of A* search method, this paper designs a simulation platform which is visible during the op-eration process to achieve graphicalization of the A* algorithm search process. The simulation platform is implemented by Matlab GUI method, which provides multi-parameter setting function, and outputs the specific traversal process of the planning method in the search space into the RGB space. The results of applying simulation platform to the teaching environment shows that this platform can provide an intuitive description of the path planning method. By extracting sam-ple data from the actual audience, the simulation platform proposed in this paper is compared with the platformless dissemination method. The experimental re-sults show that the simulation platform given in this paper can effectively im-prove the dissemination effect of the conventional multimedia teaching method.

scholarly journals Fault-Tolerant Path Planning of the Space Manipulator with Single Joint Failure Based on the Dexterity Space

2018 ◽  
Vol 160 ◽  
pp. 05010
Author(s):  
Jia-Yi Tan ◽  
Gang Chen ◽  
Yu-Qi Wang
Keyword(s):  
Path Planning ◽  
Fault Tolerant ◽  
Planning Method ◽  
A Algorithm ◽  
Joint Failure ◽  
Space Manipulator

To enable the space manipulator to complete the original task efficiently after any single joint fails, a fault-tolerant path planning method for the manipulator with single joint failure is proposed based on dexterity space in this paper. On the base of solving the degraded workspace, the dexterity space of the manipulator with single joint failure is established by constructing the dexterity index, and then the traditional A* algorithm is improved to complete fault-tolerant path planning in the dexterity space. The correctness and validity of fault-tolerant path planning based on improved A* algorithm are verified by simulating experiments with 7R manipulator.

A path planning method of 6-DOF robot for mirror therapy based on A* algorithm

2021 ◽  
pp. 1-12
Author(s):  
Zhenyu Xu ◽  
Shuai Guo ◽  
Leigang Zhang
Keyword(s):  
Path Planning ◽  
Population Aging ◽  
Planning Method ◽  
Motion Path ◽  
Mirror Therapy ◽  
A Algorithm ◽  
Acceptable Error ◽  
Rehabilitation System ◽  
Motion Performance ◽  
Kinematic Transformation

BACKGROUND: With the population aging, post-stroke patients suffering from hemiplegia are also rapidly increasing. It is essential to provide valid rehabilitation methods for hemiplegia patients. Mirror therapy is an effective rehabilitation method and is widely applied in many rehabilitation robots. OBJECTIVE: The aim of this paper is to present a path planning method to guarantee the robot’s motion performance during mirror therapy. METHODS: The kinematic framework of the proposed rehabilitation system is detailed, then the reference motion path of the manipulator is calculated according to kinematic transformation. The concept of manipulability is introduced to describe the motion performance of the manipulator. Based on the above work, a path planning method based on A* algorithm is proposed to quantitatively analyze and optimize the motion performance of the manipulator. RESULTS: Preliminary experiments with the proposed rehabilitation system are conducted to verify the proposed path planning method. The characteristics of the proposed method are analyzed through two typical situations. The results showed that the proposed method can build a new path for manipulator, which can ensure the robot’s motion performance and is highly consistent with the reference path. CONCLUSION: The results showed that the manipulator could achieve the task with acceptable error, which indicates the potential of the proposed path planning method for mirror therapy.

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.

Hierarchical optimal time path planning method for a autonomous mobile robot using A∗ algorithm

ICCAS 2010 ◽  
2010 ◽  
Author(s):  
Minhyeok Kwon ◽  
Heonyoung Lim ◽  
Yeonsik Kang ◽  
Changhwan Kim ◽  
Gwitae Park
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Planning Method ◽  
Optimal Time ◽  
Autonomous Mobile Robot ◽  
A Algorithm ◽  
Time Path
Sign in / Sign up

Export Citation Format

Share Document