Semantic Mapping and Motion Planning with Turtlebot Roomba

Abstract

In this paper, we have successfully demonstrated the semantic mapping and motion planning experiments on Turtlebot Robot using Microsoft Kinect in ROS environment. Moreover, we have also performed the comparative studies on various sampling based motion planning algorithms with Turtlebot in Open Motion Planning Library. Our comparative analysis revealed that Expansive Space Trees (EST) surmounted all other approaches with respect to memory occupation and processing time. We have also tried to summarize the related concepts of autonomous robotics which we hope would be helpful for beginners.