A Method of Ship’s Path Planning at Sea

2013 ◽  
Vol 321-324 ◽  
pp. 2038-2041
Author(s):  
Yuan Liang Zhang

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.

2014 ◽  
Vol 26 (2) ◽  
pp. 236-244 ◽  
Author(s):  
Masashi Yokozuka ◽  
◽  
Osamu Matsumoto

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.


2004 ◽  
Vol 3 (1) ◽  
pp. 33-36
Author(s):  
Yu-xin Zhao ◽  
Ji-qiang Tang ◽  
Gang Li ◽  
Chao Gao

2012 ◽  
Vol 229-231 ◽  
pp. 2019-2024 ◽  
Author(s):  
Zhi Qiang Zhao ◽  
Zhi Hua Liu ◽  
Jia Xin Hao

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.


Author(s):  
Mingfeng Luo

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.


2018 ◽  
Vol 160 ◽  
pp. 05010
Author(s):  
Jia-Yi Tan ◽  
Gang Chen ◽  
Yu-Qi Wang

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.


2021 ◽  
pp. 1-12
Author(s):  
Zhenyu Xu ◽  
Shuai Guo ◽  
Leigang Zhang

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.


ICCAS 2010 ◽  
2010 ◽  
Author(s):  
Minhyeok Kwon ◽  
Heonyoung Lim ◽  
Yeonsik Kang ◽  
Changhwan Kim ◽  
Gwitae Park

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