The learning from observation (LFO) paradigm has been widely applied in various types of robot systems. It helps reduce the work of the programmer. However, the applications of available systems are limited to manipulation of rigid objects. Manipulation of deformable objects is rarely considered, because it is difficult to design a method for representing states of deformable objects and operations against them. Furthermore, too many operations are possible on them. In this paper, we choose knot tying as a case study for manipulating deformable objects, because the knot theory is available and the types of operations possible in knot tying are limited. We propose a knot planning from observation (KPO) paradigm, a KPO theory, and a KPO system.

Learning from Observation (LFO) has been widely applied in various types of robot system. It helps reduce the work of the programmer. But the available systems have application limited to rigid objects. Deformable objects are not considered because: 1) it is difficult to describe their state, and 2) too many operations are possible on them. In this paper, we choose the knot tying as case study for operating on nonrigid bodies, because a "knot theory" is available and the type of operations is limited. We describe the Knot Planning from Observation (KPO) paradigm, KPO theory and KPO system.