Adaptive Modeling of Robotic Assembly Using Augmented Petri Nets

Abstract

Robotic assembly process is modeled as a discrete event dynamic system using contact states of the workpieces and their transitions. The goal assembly state is obtained by changing the contact states. A primitive contact is defined as a relation between a vertex and an edge of two workpieces. An augmented Petri net is presented as a framework to model, plan, and control the assembly process. The augmented Petri-net assembly model is automatically built and modified on-line during the actual assembly to handle un-modeled and infeasible contact situations. Reachability graph of the assembly model is used to find sequence from the augmented Petri net model, by the weights of the arcs. The proposed method is evaluated by simulation with L-shaped peg-in-hole assembly.