Development of an intelligent agent-based AGV controller for a flexible manufacturing system

Models for AGVs’ Scheduling and Routing

“…Complex issues associated with the design of AGV control of these systems are conflict-free shortest path, minimum time motion planning and deadlock avoidance. Srivastava et al (2008) presented an intelligent agent-based framework to overcome the inefficacies associated with the aforementioned issues. Proposed approach described the operational control of AGVs by integrating different activities such as path generation, journey time enumeration, collision and deadlock identification, waiting node location and its time estimation, and decision making on the selection of the conflict-free shortest feasible path.…”

A multi-agent based approach to dynamic scheduling with flexible processing capabilities

“…Wallace (2007) conducted a research which made use of some heuristics to improve the performance of an agent-based controller. An intelligent agent-based framework was presented by Srivastava et al (2008) to solve some of the complex problems related to collisions among the vehicles. Komma et al (2011) investigated modeling of different agents in manufacturing area on JADE reactive architecture.…”

Zone design and control for vehicle collision prevention and load balancing in a zone control AGV system

“…Sarker and Gurav (2005) present a bi-directional path flow layout and a routing algorithm that guarantee conflict-free, shortest-time routes for AGVs. Srivastava, Choudhary, Kumar, and Tiwari (2007) present an intelligent agent-based framework to overcome the inefficacies associated with issues (e.g. conflict-free shortest path, minimum time motion planning, and deadlock avoidance) in the design of AGV control.…”