Abstract
In this paper a dynamic task allocation and controller design methodology for cooperative robot teams is presented. Fuzzy logic based utility functions are derived to quantify each robot's ability to perform a task. These utility functions are used to allocate tasks in real-time through a limited lookahead control methodology partially based on the basic principles of discrete event supervisory control theory. The proposed controller design methodology accommodates flexibility in task assignments, robot coordination, and tolerance to robot failures and repairs. Implementation details of the proposed methodology are demonstrated through a warehouse patrolling case study.
Highlights
Many applications in industrial, civilian and military fields benefit from mobile robot utilization
In this paper we describe a novel control methodology for task allocation in cooperative robot teams
In developing the system model, we considered flexibility in task assignment, robot coordination for task completion and robot failures and repairs
Summary
Civilian and military fields benefit from mobile robot utilization. Several characteristics of the team members, such as endurance, reliability, efficiency etc, must be considered in task allocation decisions We describe these characteristics as fuzzy variables and develop a fuzzy controller to determine the utility function value for each task allocation event. This work combines the modeling strengths of DES and supervisory control theory to model comprehensive inter task dependences and robot interactions applicable to most task allocation problems. This works demonstrates flexibility in task assignments, task sequencing, robot cooperation and coordination, and tolerance in robot failures and repairs.
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