Robust Object Recognition and Command Understanding for a House Tidying-Up Robot

In this study, a robust object recognition and command understanding system for a house tidying-up robot is proposed. The robot can understand the user’s intentions by using a speech recognition system. When the user in-structs the tidying-up robot to tidy up an object using voice commands, the robot detects and recognizes the object. To detect and recognize multiple objects, we employ an instance segmentation method using deep learning. This method extracts the contour and shape of objects and generates the appropriate grasping posture of the robot arm. An experiment using the tidying-up robot is conducted to verify the effectiveness of the tidying-up system.