Generating a configuration space representation for assembly tasks from demonstration

Removing suboptimal actions that can exist in a demonstration is a key problem to be solved in robot programming by demonstration. In this paper we present the first step of an approach for solving this problem. We present how the configuration space (C-space) of a task can be derived from demonstration. A demonstration traces out paths on a number of C-surfaces in C-space. The idea is to use statistical regression analysis on data from these paths to determine the unknown equation parameters of a C-surface. Experimental results show the validity of the approach. Accurate parameter estimates were obtained so long as a sufficiently rich set of demonstrated paths existed on the C-surface. The approach has the advantage that it tends to provide accurate parameter estimates for C-surfaces where they were most needed; that is, for C-surfaces (i) critical to task completion, and (ii) whose paths contained suboptimal actions.