A Novel Modeling Method for Cooperative Multi-robot Systems Using Fuzzy Timed Agent Based Petri Nets

Characterized as cooperation and high efficiency, cooperative multi-robot systems (CMRS) have emerged as usual manufacturing equipments in current industries (Cao et al., 1997). Differing from generic control systems, the cooperation needs to be considered in the realization of CMRS (Cao et al., 1997). So the system modeling, analysis and refinement always meet with difficulties. As one of the typical multi-agent systems (MAS), CMRS can be regarded as one MAS in distributed artificial intelligence (Jennings et al., 1998). For modeling MAS, some attempts to use object-oriented methodology have been tried and some typical agent objects have been proposed, such as active object, etc (Guessoum & Briot, 1999). However, agent based object models still can not depict the structure and dynamic aspects of MAS, such as cooperation, learning, temporal constraints, etc (Jennings et al., 1998). On one hand, as one of the most proper and promised realization technology, objectoriented concurrent programming (OOCP) methodology is always used to realize MAS (Guessoum & Briot, 1999). In OOCP realization, one special object called active object is proposed (Guessoum & Briot, 1999), which can be used to model generic agent architectures and behaviors with OO methodology. Although OOCP can solve MAS realization problem favorably, the modeling problem mentioned above still exists. On the other hand, as a kind of powerful formal description and analysis method for dynamic systems (Murata, 1989), Petri net (PN) has become a bridge between practical application and model theories (Murata, 1989). With object-oriented concepts introduced into PN, typical object Petri nets such as HOONet (Hong & Bae, 2000) etc, al. are presented, which are strict OPNs. Then for providing the ability of modeling time critical complex systems, timed hierarchical object oriented Petri net (TOPN) (Xu & Jia, 2006) is proposed on the base of HOONet (Hong & Bae, 2000). It supports temporal knowledge description and object-oriented concepts. Modeling features in TOPN support describing and analyzing dynamic systems such as MAS and CMRS. Recently, some attempts have been conducted on modeling MAS by using OPN (Chainbi, 2004). Although Petri nets can be used to model and analyze different systems, they have failed to model learning ability and the aging effects in O pe n A cc es s D at ab as e w w w .in te hw eb .c om