Robotic Path Planning Implementation using Search Algorithms

TL;DR

This paper demonstrates the implementation of path planning algorithms, specifically Dijkstra's and A*, on a TurtleBot3 robot in Gazebo to navigate uneven terrains with obstacles, highlighting practical application in robotics.

Contribution

It provides a practical implementation of search algorithms for robotic path planning in complex environments using simulation.

Findings

Successful navigation of uneven terrain with obstacles

Comparison of Dijkstra's and A* algorithms in simulation

Insights into algorithm performance in real-world scenarios

Abstract

Till now, many path planning algorithms have been proposed in the literature. The objective of these algorithms is to find the quickest path between initial position to the end position in a certain environment. The complexity of these algorithms depends on the internal parameters such as motor speed or sensor range and on other external parameters, including the accuracy of the map, size of the environment, and the number of obstacles. In this paper, we are giving information about how path planning algorithm finds the optimal path in an uneven terrain with a multiple obstacle using TurtleBot3 robot into the Gazebo environment using Dijkstra's and A(star).