Comparative study of soft computing techniques for mobile robot navigation in an unknown environment

Algabri, Mohammed; Mathkour, Hassan; Hedjar, Ramdane; Alsulaiman, Mansour

doi:10.1016/j.chb.2015.03.062

Cited by 85 publications

(44 citation statements)

References 12 publications

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“…Any part of the image can be selected and knowing the coordinates the original space can be reconstructed. This can give further research topics in the field of mobile robot navigation especially regarding optimalisation for computing techniques [12] and since after practice the image can be expressive and contain easily computable data, this method can give an alternative solution for aesthetic markers also [13].…”

Section: Computer Visualisationmentioning

confidence: 99%

Perspective with Six Vanishing Points - an Alternative Method

Urbin

Szilágyi

2015

Period. Polytech. Civil Eng.

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Section: Computer Visualisationmentioning

confidence: 99%

Perspective with Six Vanishing Points - an Alternative Method

Urbin

Szilágyi

2015

Period. Polytech. Civil Eng.

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“…Algabri et al [39] have combined the fuzzy logic with other soft computing techniques such as Genetic Algorithm (GA), Neural Networks (NN), and Particle Swarm Optimization (PSO) to optimize the membership function parameters of the fuzzy controller for improving the navigation performance of mobile robot. They have designed two basic fuzzy logic behaviors: Motion to target behavior (MFLC) and obstacle avoidance behavior (AFLC).…”

Section: Hybridization Of Fuzzy and Nondeterministic Algorithmmentioning

confidence: 99%

Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review

Pandey¹

2017

IRATJ

178

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Mobile robot is an autonomous agent capable of navigating intelligently anywhere using sensor-actuator control techniques. The applications of the autonomous mobile robot in many fields such as industry, space, defence and transportation, and other social sectors are growing day by day. The mobile robot performs many tasks such as rescue operation, patrolling, disaster relief, planetary exploration, and material handling, etc. Therefore, an intelligent mobile robot is required that could travel autonomously in various static and dynamic environments. Several techniques have been applied by the various researchers for mobile robot navigation and obstacle avoidance. The present article focuses on the study of the intelligent navigation techniques, which are capable of navigating a mobile robot autonomously in static as well as dynamic environments. Keywords: IntroductionThis article introduces the literature survey of the various techniques used for mobile robot navigation. Navigation and obstacle avoidance are one of the fundamental problems in mobile robotics, which are being solved by the various researchers in the past two decades. The aim of navigation is to search an optimal or suboptimal path from the start point to the goal point with obstacle avoidance competence. Basically, the mobile robot navigation has been done by the Deterministic algorithm and Nondeterministic (Stochastic) algorithm. Nowadays, the hybridization of both the algorithms called as an Evolutionary algorithm is being used to solve the mobile robot navigation problem. Figure 1 shows the general classification of the Deterministic algorithm, Nondeterministic (Stochastic) algorithm, and Evolutionary algorithm, which are implemented for mobile robot navigation by various authors.

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“…Evolutionary and swarm algorithms have also been combined with fuzzy systems and neural networks (these are further discussed below). Algabri [18] presented a comparison of four hybrid methods (namely manual fuzzy, genetic algorithm-based fuzzy, PSO-based fuzzy, and neuro-fuzzy) to assess the performance of these methods relative to each other. The author notes that these methods outperform each other for different aspects and no one method is necessarily superior overall for general applications.…”

Section: Navigation Of Autonomous Planetary Rovers a Path Planningmentioning

confidence: 99%

Adaptive and intelligent navigation of autonomous planetary rovers — A survey

Wong

Yang

Yan

et al. 2017

2017 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

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Abstract-The application of robotics and autonomous systems in space has increased dramatically. The ongoing Mars rover mission involving the Curiosity rover, along with the success of its predecessors, is a key milestone that showcases the existing capabilities of robotic technology. Nevertheless, there has still been a heavy reliance on human tele-operators to drive these systems. Reducing the reliance on human experts for navigational tasks on Mars remains a major challenge due to the harsh and complex nature of the Martian terrains. The development of a truly autonomous rover system with the capability to be effectively navigated in such environments requires intelligent and adaptive methods fitting for a system with limited resources. This paper surveys a representative selection of work applicable to autonomous planetary rover navigation, discussing some ongoing challenges and promising future research directions from the perspectives of the authors.

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Comparative study of soft computing techniques for mobile robot navigation in an unknown environment

Cited by 85 publications

References 12 publications

Perspective with Six Vanishing Points - an Alternative Method

Perspective with Six Vanishing Points - an Alternative Method

Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review

Adaptive and intelligent navigation of autonomous planetary rovers — A survey

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