scholarly journals A bibliometric analysis on path planning methods for mobile robots published in scientific citation index-expanded indexed journals between 2000-2020

2021 ◽  
Vol 1045 (1) ◽  
pp. 012017
Author(s):  
Aisha Muhammad ◽  
Mohammed AH Ali ◽  
Ibrahim Haruna Shanono
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Bibliometric Analysis ◽  
Citation Index ◽  
Planning Methods ◽  
Scientific Citation

A systematic and bibliometric analysis on 3D printing published in scientific citation index-expanded indexed journals between 1999 and 2019

2021 ◽  
Vol 44 ◽  
pp. 1739-1743
Author(s):  
Aisha Muhammad ◽  
Mohammed A.H. Ali ◽  
Ibrahim Haruna Shanono ◽  
Nor Rul Hasma Abdullah
Keyword(s):  
3D Printing ◽  
Bibliometric Analysis ◽  
Citation Index ◽  
Scientific Citation

scholarly journals Path-Planning for Mobile Robots Using a Novel Variable-Length Differential Evolution Variant

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 357
Author(s):  
Alejandro Rodríguez-Molina ◽  
José Solís-Romero ◽  
Miguel Gabriel Villarreal-Cervantes ◽  
Omar Serrano-Pérez ◽  
Geovanni Flores-Caballero
Keyword(s):  
Path Planning ◽  
Differential Evolution ◽  
Mobile Robots ◽  
Vector Optimization ◽  
Vector Optimization Problem ◽  
Variable Length ◽  
Planning Problem ◽  
Novel Variant ◽  
Planning Methods ◽  
Path Planning Problem

Mobile robots are currently exploited in various applications to enhance efficiency and reduce risks in hard activities for humans. The high autonomy in those systems is strongly related to the path-planning task. The path-planning problem is complex and requires in its formulation the adjustment of path elements that take the mobile robot from a start point to a target one at the lowest cost. Nevertheless, the identity or the number of the path elements to be adjusted is unknown; therefore, the human decision is necessary to determine this information reducing autonomy. Due to the above, this work conceives the path-planning as a Variable-Length-Vector optimization problem (VLV-OP) where both the number of variables (path elements) and their values must be determined. For this, a novel variant of Differential Evolution for Variable-Length-Vector optimization named VLV-DE is proposed to handle the path-planning VLV-OP for mobile robots. VLV-DE uses a population with solution vectors of different sizes adapted through a normalization procedure to allow interactions and determine the alternatives that better fit the problem. The effectiveness of this proposal is shown through the solution of the path-planning problem in complex scenarios. The results are contrasted with the well-known A* and the RRT*-Smart path-planning methods.

Path Planning Methods of Mobile Robot Based on Soft Computing Technique

2011 ◽  
Vol 216 ◽  
pp. 677-680
Author(s):  
Hong Min Zhang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Soft Computing ◽  
Computing Technique ◽  
The Future ◽  
Planning Methods ◽  
Soft Computing Technique

Path planning is one of the most important and challenging problems of mobile robot. It is one of the keys that will make the mobile robots fully autonomous. In this paper, we summarized the application of soft computing approaches in path planning for mobile robot. Finally the future works of path planning for mobile robots are prospected.

Comparative analysis of intelligent planning methods

2012 ◽  
Vol 9 (2) ◽  
pp. 53-57 ◽  
Author(s):  
O.V. Darintsev ◽  
A.B. Migranov
Keyword(s):  
Neural Networks ◽  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Comparative Analysis ◽  
Mobile Robots ◽  
Sensory Information ◽  
Working Environment ◽  
Planning Methods ◽  
Intelligent Planning

The main stages of solving the problem of planning movements by mobile robots in a non-stationary working environment based on neural networks, genetic algorithms and fuzzy logic are considered. The features common to the considered intellectual algorithms are singled out and their comparative analysis is carried out. Recommendations are given on the use of this or that method depending on the type of problem being solved and the requirements for the speed of the algorithm, the quality of the trajectory, the availability (volume) of sensory information, etc.

A Novel Static Path Planning Method for Mobile Anchor-Assisted Localization in Wireless Sensor Networks

2020 ◽  
Vol 10 ◽  
Author(s):  
Abdelhady M. Naguib ◽  
Shahzad Ali
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Path Planning ◽  
Sensor Node ◽  
Large Scale ◽  
Performance Metrics ◽  
Wireless Sensor ◽  
Anchor Node ◽  
Mobile Anchor ◽  
Planning Methods

Background: Many applications of Wireless Sensor Networks (WSNs) require awareness of sensor node’s location but not every sensor node can be equipped with a GPS receiver for localization, due to cost and energy constraints especially for large-scale networks. For localization, many algorithms have been proposed to enable a sensor node to be able to determine its location by utilizing a small number of special nodes called anchors that are equipped with GPS receivers. In recent years a promising method that significantly reduces the cost is to replace the set of statically deployed GPS anchors with one mobile anchor node equipped with a GPS unit that moves to cover the entire network. Objectives: This paper proposes a novel static path planning mechanism that enables a single anchor node to follow a predefined static path while periodically broadcasting its current location coordinates to the nearby sensors. This new path type is called SQUARE_SPIRAL and it is specifically designed to reduce the collinearity during localization. Results: Simulation results show that the performance of SQUARE_SPIRAL mechanism is better than other static path planning methods with respect to multiple performance metrics. Conclusion: This work includes an extensive comparative study of the existing static path planning methods then presents a comparison of the proposed mechanism with existing solutions by doing extensive simulations in NS-2.

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