Abstract- Navigation movement of the robot is one of the most important parts in an intelligent robot system. a lot of studies have done on avoiding trajectory, navigation and obstacle in the known environment, but it is difficult to get, the optimum trajectory in the path in a known environment this is one of the important parts of the robotic planning.

PRM use to direct the mobile robot to find the target with obstacle avoidance. This paper suggests trajectory based on a probabilistic Roadmap (PRM) for an autonomous robot trajectory in a known environment. To simulate and compare the robot motion path with other studies was simulated. The PRM algorithm uses MATLAB.

Keywords - Navigation, Path planning, known environments.

I.
*…show more content…*

In this paper, a probabilistic roadmap method of path planning for mobile robot is proposed to use it in Known environment.

II. RELATED WORK

PRM are considered as optimization algorithms for search in a space of potential solutions, the solution to the problem of planning by PRM is proposed for the first time by [5]. Optimal trajectory is calculated after several of Numnodes. Some papers have focused on known environments. Path planning is an important subject in navigation of autonomous mobile robots, which is to find a best path according to some criterion such as distance or time [6].

In this paper, PRM approach to path planning with Obstacle to solve the problem of path planning for autonomous robots. We have mostly focused on using PRM to calculate optimized trajectory, we have thus demonstrated their advantages and disadvantages, and for this we made a comparison with a widely used approach, PRM associated with GA algorithm study for finding optimal paths.

III. Basic PRM

PRM consist from two important parts Node generation or Num nodes and Node Connection:

PRM are randomly generated in free-space. Different studies have been developed that the generation of nodes to ward specific areas of free-space to improve the probability

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