Mobile robotics research is an emerging area since last three and
half decades. The present research on mobile robotics addresses the problems which
are mainly on path planning algorithm and optimization in static as well as
dynamic environments. A detailed review has been made in the broad field of
mobile robotic research especially focussing on the path planning strategy in
various cluttered environments and their advantages and disadvantages of each of
the techniques has been highlighted.  The
path planning strategy of mobile robots can be classified in four categories
such as; (1) Analytical methods, (2) Enumerative methods, (3) Evolutionary
methods and (4) Meta-heuristic Methods. Each of this aforesaid method has its
own advantages and disadvantages. However, the main weakness arises from the
fact that Analytical methods are too complex to be used intangible, where as
the enumerative methods are overwhelmed by the size of the search space. On the
other hand in path planning when search space is too large, many evolutionary
algorithms 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 robot
worldwide, however the most commonly used techniques are presented here for
further study.

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autonomous mobile robot, path planning is very important task and according to
some evaluation standards mobile robot finds obstacle-free path in the obstacle
prone environment from original start point to the target point. In many
automated environments, mobile robots are increasingly being employed.
Normally, there are various paths for robot to influence the target, but in
circumstance, the best path is selected according to some guideline as smallest
distance, minimum energy consuming or the most adopted criteria is the shortest
distance with shortest time. Path planning can be seen as an optimization
problem since its purpose is to search for a path with shortest distance under certain constraints such as the given
environment with collision-free motion
1. In general, mobile robot path planning is divided into local path planning
and global path planning. In local path planning, the robot travels in an
unknown or partially known environment to avoid collision with present
obstacles. On the other hand, in global path planning, the environment is
completely known to the mobile robot and then the robot reaches the target
along the predefined path. However, the method of global motion planning lacks
robustness due to terrain uncertainty. Normally, local path planning is more flexible
in unknown environments and a feasible path might be obtained using this

applications of mobile robot path planning are included in medical and surgical
uses, personal assistance, security, warehouse and distribution applications,
as well as ocean and space exploration, automated guided vehicles for
transferring goods in a factory, unmanned bomb disposal robots and planet
exploration robots.