Symbolic representation of trajectories for skill generation

The completion of robot programs requires long development time and much effort. To shorten this programming time and minimize the effort, we have been developing a system which we refer to as “assembly-plan-from-observation (APO) system;” this system provides the ability for a robot to observe a human performing an assembly tasks, understand the tasks, and subsequently generate a program to perform that same task. One of the necessary tasks in APO is to create a trajectory of robot hand movement from observing human performance. The previous system developed a direct observation method based on the trajectory of a human movement. Though simple and handy, the system was susceptible to noise. This paper proposes a method to make the observation robust against noise by using symbolic representations of a trajectory based on contact analysis. The system divides the trajectory into small segments based on the contact analysis, then allocates an operation element referred to as a sub-skill to those segments; the result is a robust trajectory-based APO system