Interpretation of force and moment data is used to guide the searching phase of a circular peg-in-hole assembly. It is shown that the available measurements carry varying quality of information, ambiguous in much of the search space and relatively precise in a small region. By interpreting the history of sensory data acquired during an assembly attempt, reliable interpretation of the data is possible. A feature-based technique is described for interpreting sensory data. Experiments with robotic peg-in-hole assembly demonstrated a speed-up of nearly an order of magnitude relative to a blind search.
free text keywords: Engineering, business.industry, business, Feature extraction, Peg in hole, Pattern matching, Computer vision, Sensory system, Artificial intelligence, Order of magnitude, Information quality