An Autonomous Processing Method of Chinese Service Instruction for Indoor Intelligent Robot

An autonomous processing method of Chinese service instruction is investigated to make robot understand natural language. This method directly maps Chinese service instructions to sequences of executable actions. Firstly, the collected corpus of the service instruction expressed in Chinese is deeply studied, and the corresponding relationship between the key information and syntactical structure is presented. According to the grammar rules of phrase chunk, a probability model is used for key information extraction. In order to resolve the problem of task decomposition, a task decomposition template (TDT) is presented. Based on this, the service instruction is mapped to sequences of actions. At last, the simulation about autonomous Chinese instruction processing is performed, and the experimental results of every step are provided, with the average accuracies of 92.9% in chunk marking, 92.7% in information extraction, and 97.2% in instruction parsing, which validates the correctness and availability of the proposed method.