Research On Deep Learning-based Voice Control Method For An Industrial Manipulator

Along with the high speed development of intelligent making techniques,the traditional artificial operation ways can no longer meet the current production demand,therefore the industrial robots are gradually replacing workers.To realize the real intelligence of the industrial robots,the premise of the communication between the industrial robots and the workers is that industrial robots can understand human's language.Therefore,through voice to control the industrial robot's behavior is first step.Since the shortcomings of the existing speech recognition systems,this thesis proposes a target detection method to recognize the spectrogram for the speech recognition,and applies the recognition results to the intelligent control of the industrial robots.The details of the work are as follows:1.According to the purpose and content of this thesis,the content of the isolated word instruction set is determined and the audio samples are recorded.And the recording environment is quiet environment.Since there are great differences between the human's voices and the noises,speech recognition can be achieved by recognizing the spectrogram.2.The traditional speech recognition systems have poor robustness,and they mainly focus on the analysis of the time dimension.Therefore,this thesis proposes a target detection method to recognize the spectrogram.The proposed method only focuses on the local interest region,which filters the noises that has a great impact on the recognition performance.The recognition accuracy in the quiet environment is basically more than 90%,and the recognition accuracy in the noisy environment is basically more than 85%.3.The speech recognition system using the target detection algorithm to recognize the spectrogram needs to select the pre-selected box of the test object before training,which helps to improve the forecast accuracy.Since the effective area scale of the spectrogram differs greatly from the scale of the objects seen daily,therefore,the machine learning clustering algorithm k-means is used to cluster the pre-selected boxes.4.The simulations of the industrial robot voice control system is designed on the ROS simulation software.The words obtained by the speech recognition based on the target detection method are transmitted to the ROS system and the industrial robot is controlled to make the corresponding actions,which proves the practicality of the methods in this thesis.