A study and implementation of mapping and speech recognition techniques for an autonomous mobile robot based on ROS

Abstract

Autonomous mobile robots work in close interaction with humans in environments such as homes, hospitals, public places and disaster areas. In autonomous mobile robots, the main constraints are safety, autonomy and efficiency in helping the humans. Given these constraints, developing the autonomous mobile robot technologies is a major challenge for both the industry and the research society. This paper work is about how an indoor autonomous mobile robot can work based on robot operating system and using Lidar and other sensors to create a map of an environment, and perform autonomous navigation with using capabilities like dynamic obstacle avoidance, speech recognition and video streaming. To achieve the above features, different algorithms like SLAM, AMCL, dynamic window approach algorithms, and CMU PocketSphinx speech recogniser are used. For video steaming, ROS web video server is used and the recorded video can be sent to a remote desktop system using ROS network.