A PRM Approach to Path Planning with Obstacle Avoidance of an Autonomous Robot
Saleh Alarabi, Chaomin Luo, Michael Santora
Abstract
A path planning algorithm is one of the most important parts of the system of an intelligent robot. There are many studies to avoid obstacles in a navigation route for a known environment, but it is difficult to get an optimal path. In short, knowing the environment is one of the most important parts of robotic planning and probabilistic Roadmap (PRM) uses this to direct the mobile robot to find the target while having obstacle avoidance. Mobile robots have been widely used in multiple automation-related settings. Navigation from one stage to another must be performed while avoiding current obstacles in the region to execute their duties effectively. The purpose of this research is to show the effectiveness of methods in path planning in different environments by using a PRM. This paper suggests a trajectory based on a PRM for an autonomous robot trajectory in a known environment. The robot motion path was simulated and compared to other studies.