Adding Common Sense to Robots by Completing the Incomplete Natural Language Instructions

This system is developed to identify and complete the human’s instructions or incomplete sentences given by a user as a command. It would facilitate the interaction between the human and mobile service robots. However, when humans give the instruction, there can be incompleteness or else missing the information related to the environment. That is because humans, generally based on common sense, depending on the environment. Then the human brain can complete all those incomplete sentences by using common sense knowledge. This paper itself introduced a model of a service robot who can compete with the given incomplete instructions, display the related sentences or words, and finally move to the related objects in the environment. First, it will consider and identify the objects in the environment and then consider the given natural language instruction by humans. As a first step of the approach, complete the incomplete sentences. Those sentences are coming as natural language instructions. By parsing it into as the frame can identify the related words by using the created model or can call as language model and here used some identify words from the human common sense also, then the service robot will learn about the commonsense knowledge automatically from the parsing sentences as a speaker. Considering all the parsing sentences, it calculates and measures the accuracy of this service robot model. Simply this is a commonsense reasoning model. The result of the provided solution can enable the robot model that works in a ROS environment to identify and automatically perform the tasks.