Mobile robotics research is an emerging area since last three andhalf decades.

The present research on mobile robotics addresses the problems whichare mainly on path planning algorithm and optimization in static as well asdynamic environments. A detailed review has been made in the broad field ofmobile robotic research especially focussing on the path planning strategy invarious cluttered environments and their advantages and disadvantages of each ofthe techniques has been highlighted.  Thepath planning strategy of mobile robots can be classified in four categoriessuch as; (1) Analytical methods, (2) Enumerative methods, (3) Evolutionarymethods and (4) Meta-heuristic Methods. Each of this aforesaid method has itsown advantages and disadvantages.

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However, the main weakness arises from thefact that Analytical methods are too complex to be used intangible, where asthe enumerative methods are overwhelmed by the size of the search space. On theother hand in path planning when search space is too large, many evolutionaryalgorithms have been shown to be ineffective. To overcome these drawbacks,meta-heuristic approaches have been attracting considerably in this research area.

Many techniques are developed for path planning of mobile robotworldwide, however the most commonly used techniques are presented here forfurther study. Keywords:   1. INTRODUCTIONInautonomous mobile robot, path planning is very important task and according tosome evaluation standards mobile robot finds obstacle-free path in the obstacleprone environment from original start point to the target point. In manyautomated environments, mobile robots are increasingly being employed.Normally, there are various paths for robot to influence the target, but incircumstance, the best path is selected according to some guideline as smallestdistance, minimum energy consuming or the most adopted criteria is the shortestdistance with shortest time.

Path planning can be seen as an optimizationproblem since its purpose is to search for a path with shortest distance under certain constraints such as the givenenvironment with collision-free motion1. In general, mobile robot path planning is divided into local path planningand global path planning. In local path planning, the robot travels in anunknown or partially known environment to avoid collision with presentobstacles. On the other hand, in global path planning, the environment iscompletely known to the mobile robot and then the robot reaches the targetalong the predefined path. However, the method of global motion planning lacksrobustness due to terrain uncertainty.

Normally, local path planning is more flexiblein unknown environments and a feasible path might be obtained using thisapproach2Theapplications of mobile robot path planning are included in medical and surgicaluses, personal assistance, security, warehouse and distribution applications,as well as ocean and space exploration, automated guided vehicles fortransferring goods in a factory, unmanned bomb disposal robots and planetexploration robots.