|Programming by demonstration
(PbD) is a technique for programming robots that holds much promise in making
robots more accessible to ordinary, non-technical users. However, a well-known
difficulty with the method is that a human will often demonstrate the task
to be programmed inconsistently or even erroneously, leading to the inclusion
of what is essentially noise in the demonstration. A number of techniques
exist in the literature for filtering out this type of noise; however, most
focus on very low level control command details. In this paper, we propose
a new, complementary direction of research. We take a “task-level”
view of the demonstration, and note that noise can exist at this level also.We
propose a framework, based on a hybrid dynamic system modeling approach,
to select the most optimal, task-level execution strategies that were demonstrated.
We apply our framework to a real household task of inserting the compressible
spindle of a paper towel holder into its supports. We conduct experiments
to show that significant improvements in robot performance of the task can
be achieved by a PbD regime that includes our method.