Teaching by Showing: Generating Robot Command Sequences Based on Real Time Visual Recognition of Human Pick and Place Actions.

摘要

"Teaching by Showing" is a straightforward teaching method in which a human instructor shows an assembly task to a robot by simply performing it with his own hand, and the robot automatically generates a program by watching the example task. For such a method to be realized, visual recognition of human action sequences becomes a crucial issue. In this paper, an experimental system that demonstrates the teaching method is presented. The system observes example tasks by stereo video cameras and generates symbolic descriptions of action sequences, which are translated into manipulator command sequences. Actions are modeled as partial state changes over segmented time intervals. And the partial state descriptors constitute the environment model. Segmentation events are defined for actions involved in hand assembly tasks, which are detected in terms of time differences of visual features. Integrating these, an algorithm of action recognition is fully described. It automatically segments and classifies every action in a robust and efficient manner. An experiment revealed that the system can recognize each action correctly in real time, and it can carry out the instructed task successfully.