Research of an intelligent robot which observes human action sequences, understands these, and generates a program for the task.

“示范教学”是一种直截了当的教学方法，即由人类讲师亲自向机器人展示组装任务，机器人通过观看示例任务自动生成程序。为了实现这种方法，人类动作序列的视觉识别成为一个关键问题。在本研究中，开发了一个示范教学方法的原型系统。该系统通过立体摄像机观察示例任务，生成动作序列的符号描述，并将其转换为机械手命令序列。动作被建模为分段时间间隔内的部分状态变化。部分状态描述符构成了环境模型。针对手工装配任务中涉及的动作，定义了分割事件，并根据视觉特征的时间差进行检测。在此基础上，提出了一种动作识别算法。它以稳健和高效的方式自动分割和分类每个动作。实验结果表明，该系统能够实时准确地识别每个动作，并能顺利完成指令任务。

"Teaching by Showing" is a straightforward teaching method in which a human instructor shows an assembly task to the 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 research, a prototype system that demonstrates the teaching method is developed. 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 modelled 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.