TASK SEQUENCE PLANNING USING FUZZY PETRI NETS

This paper discusses the problem of representation and planning of operations sequences in a robotic system using fuzzy Petri nets [2], [4], [7], [8]. In the fuzzy Petri net representation, objects whose internal states are altered during a process are termed soft objects, and the process steps where alterations may occur are labeled key transitions, A correct sequence is defined as a sequence which is feasible, complete, and satisfies precedence relations. In this formulation, the internal state of an object is represented by a global fuzzy variable attached to the token related to the degree of completion of the process, All correct operations sequences must satisfy process sequence constraints imposed by transition reasoning rules, The correct precedence relationships and the characteristics of completeness for operations in all feasible sequences are guaranteed by the prime number marking algorithm which marks the fuzzy Petri net, The use of transition reasoning rules in this application simplifies the representation and search problems for task planning where correct sequences do not depend on exact knowledge of internal states, but only their precedence relations.