A comprehensive study for robot navigation techniques

Gul, Faiza; Rahiman, Wan; Alhady, S. S. N.

doi:10.1080/23311916.2019.1632046

Cited by 172 publications

(74 citation statements)

References 100 publications

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“…For a particular environment, a mobile robot determines an optimal or sub-optimal collision-free route towards its desired goal from the initial location according to a specific performance criterion. Path planning techniques are divided based on the environment [13] in which objects may be fixed or movable. Path planning techniques can also be divided into two divisions: global path planning and local path planning.…”

Section: Path Planningmentioning

confidence: 99%

“…These are known as the most straightforward methods for finding a path for the robot which needs to know the environment and the robot's primary and terminal position beforehand for working purposes. Some of the most notable heuristic algorithms are [13]: Dijkstra's algorithm, A*, D*, etc.…”

Section: ) Graph-based Searching Algorithmsmentioning

confidence: 99%

“…The selection of the best route for moving the mobile robot within the environment is done with the help of a navigation approach consisting of path-planning and object avoidance algorithms to generate real-time trajectories and avoid collisions [13]. The key factor of the navigation is localization that helps to optimize the working point of the robot within its surrounding environment [14].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Critical Design and Control Issues of Indoor Autonomous Mobile Robots: A Review

et al. 2021

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Robots that can move autonomously and can make intelligent decisions by perceiving their environments and surrounding objects are known as autonomous mobile robots. Such robots have rapidly moved from laboratories to automated industries to fill a variety of roles in our lives, homes, offices, hospitals, industries, and even on the streets. The interest in mobile robots is growing rapidly, prompting an enormous amount of research over the last 30 years, on critical factors of mobile robots such as locomotion, perception, localization, mapping, ego-motion tracking, and dynamic navigation. This article surveys these essential factors of autonomous mobile robots in terms of mathematical modeling, control issues, and challenging factors. Brief discussions are provided on the fundamentals of these technologies, popular algorithms in comprehensive mode, future challenges, and promising directions to guide the construction of an autonomous mobile robot with high accuracy and effectiveness. Since it is difficult to find complete coverage of those topics in a single location, this article provides a guideline for researchers entering the field or for innovators in the mobile robotics sector. The paper also examines open challenges in indoor mobile robots and identifies potential futures for autonomous mobile robots.

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Section: Path Planningmentioning

confidence: 99%

Section: ) Graph-based Searching Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Critical Design and Control Issues of Indoor Autonomous Mobile Robots: A Review

et al. 2021

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“…Then the issues related to these facilities using AGV can be divided into; estimated number of vehicles, guide path, idle-positioning, and vehicle scheduling and battery management. Bio-inspired techniques are most popular, and researchers are implementing them solving path planning problem for AGV or mobile robots [1]. The popular bio-inspired algorithms are based on the living creature behavior which include birds, bees, ants, whale, bat, fish, wolf [2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

A Review of Control Algorithm for Autonomous Guided Vehicle

Gul

2020

IJEECS

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The autonomous guided vehicle is a efficient and effective platform for control system. Their non-linear nature helps in analysing the control algorithms more efficiently and effectively. The main objective of path planning is to find the optimal and shortest path avoiding the time complexity so environment can be modelled completely for vehicle. The paper includes explanation of different systems together with numerous algorithms have been discussed with advantages and disadvantages for example: Fuzzy control, Neural Control, Back-stepping control, Adaptive control, Sliding mode control and PID control and linear quadratic regulator. The conclusion includes the hybrid system integration based on the advantages and disadvantages presented in this paper.

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“…Therefore, navigation of mobile robots that can move freely in a static or dynamic environment is an important problem. The main purpose of mobile robot navigation is to provide a smooth and safe transportation of the mobile robot in a dispersed environment by following a safe path from its starting position to its target position and producing an optimum trajectory [3]. Robots are basically designed to perform complex and nonlinear real-time operations in their environment.…”

Section: Introductionmentioning

confidence: 99%

Development of Artificial Neural Network Structures for Predicting Navigation Tasks of a Mobile Robot

Sahmutoglu

Akdoğan

2020

Int. J. Eng. Tech. Mgmt. Res.

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Determining trajectories in mobile robot navigation tasks is a difficult process to apply with conventional methods. Therefore, intelligent techniques produce highly effective results in trajectory optimization and orientation prediction. In this study, two different ANN (Artificial Neural Network) structures have been developed for the navigation prediction of the SCITOS G5 mobile robot. For this aim, RBF (Radial Basis Function) and MLP (Multi-Layer Perceptron) structures were used. Information obtained from 24 sensors of the robot was used as network inputs and network output determines robot direction. Accordingly, structures that have 24 inputs and one output were created. The best performance network structures obtained were compared among them in simulation environment. Accordingly, RBF has been observed to produce more accurate results than MLP.

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A comprehensive study for robot navigation techniques

Cited by 172 publications

References 100 publications

Critical Design and Control Issues of Indoor Autonomous Mobile Robots: A Review

Critical Design and Control Issues of Indoor Autonomous Mobile Robots: A Review

A Review of Control Algorithm for Autonomous Guided Vehicle

Development of Artificial Neural Network Structures for Predicting Navigation Tasks of a Mobile Robot

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