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

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.

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A Method of Ship’s Path Planning at Sea

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.321-324.2038 ◽

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.

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A Reasonable Path Planning via Path Energy Minimization

Journal of Robotics and Mechatronics ◽

10.20965/jrm.2014.p0236 ◽

2014 ◽

Vol 26 (2) ◽

pp. 236-244 ◽

Cited By ~ 11

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.

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Path Planning for Ground Simulation Objiect Based on A* Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.229-231.2019 ◽

2012 ◽

Vol 229-231 ◽

pp. 2019-2024 ◽

Cited By ~ 1

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.

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A Path Planning Method Based on Robot Automatic Grinding of Drills

Journal of Physics Conference Series ◽

10.1088/1742-6596/2133/1/012024 ◽

2021 ◽

Vol 2133 (1) ◽

pp. 012024

Author(s):

Weidong Hao ◽

Chaoquan Tan ◽

Yulu Sun ◽

Chuan Zheng ◽

Jingsen Jin

Keyword(s):

Path Planning ◽

Point Cloud ◽

Industrial Robots ◽

Planning Method ◽

Motion Path ◽

Point Cloud Data ◽

End Effector ◽

Cloud Data ◽

Pdc Bit ◽

Actual Operation

Abstract This paper proposes a path planning method for grinding excess material after PDC bit repair using industrial robots. Firstly, a 3D scanning instrument is used to obtain point cloud data of the bit to be ground, secondly, this data are imported into Geomagic Studio for processing to obtain the triangular sheet file of the area to be ground. Finally, the software based on MATLAB is used to process the file and calculate the motion path of the robot end-effector. The generated path is imported into ROS for simulation. By comparing the generated path with the grinding area, it was verified that the generated path could be used in actual operation.

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Matlab-Realized Visual A* Path Planning Teaching Platform

International Journal of Emerging Technologies in Learning (iJET) ◽

10.3991/ijet.v13i10.9463 ◽

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.

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

MATEC Web of Conferences ◽

10.1051/matecconf/201816005010 ◽

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.

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Second Path Planning for Unmanned Surface Vehicle Considering the Constraint of Motion Performance

Journal of Marine Science and Engineering ◽

10.3390/jmse7040104 ◽

2019 ◽

Vol 7 (4) ◽

pp. 104 ◽

Cited By ~ 8

Author(s):

Fan ◽

Li ◽

Liao ◽

Jiang ◽

Wang ◽

...

Keyword(s):

Path Planning ◽

Nonlinear Least Squares ◽

Optimization Method ◽

Field Method ◽

Planning Method ◽

Path Optimization ◽

Curvature Radius ◽

Tracking Accuracy ◽

Motion Performance ◽

Initial Path

When utilizing the traditional path planning method for unmanned surface vehicles (USVs), ‘planning-failure’ is a common phenomenon caused by the inflection points of large curvatures in the planned path, which exceed the performances of USVs. This paper presents a second path planning method (SPP), which is an initial planning path optimization method based on the geometric relationship of the three-point path. First, to describe the motion performance of a USV in conjunction with the limited test data, a method of integral nonlinear least squares identification is proposed to rapidly obtain the motion constraint of the USV merely by employing a zig zag test. It is different from maneuverability identification, which is performed in combination with various tests. Second, the curvature of the planned path is limited according to the motion performance of the USV based on the traditional path planning, and SPP is proposed to make the maximum curvature radius of the optimized path smaller than the rotation curvature radius of the USV. Finally, based on the ‘Dolphin 1’ prototype USV, comparative simulation experiments were carried out. In the experiment, the path directly obtained by the initial path planning and the path optimized by the SPP method were considered as the tracking target path. The artificial potential field method was used as an example for the initial path planning. The experimental results demonstrate that the tracking accuracy of the USV significantly improved after the path optimization using the SPP method.

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