Command Understanding Using Attention-based Sequence to Sequence in Executing a Task of Robots

Abstract

In order to respond to human requests, it is very difficult for a robot to accurately understand a natural language to be expressed with many different ways for a unique command. In response to this, there is a method of the semantic analysis based on Seq2Seq (Sequence to Sequence) model of the attention-type for understanding the commands given by humans. However, since the output of the method is expressed in a complex logical form, it needs to be converted for the robot to perform the task for a command. Here, we propose a method for robots to understand commands with appropriate output in the execution of tasks. The output generated with the proposed method is composed of the information (words) necessary to a task in the order of [”task”, ”target”]. The experimental results using the instruction sentences used in a league of RoboCup@Home will show that it is possible to understand the instructions without using logical expressions.