Action planning for multi–robot–based reconfigurable fixture. (21st November 2014)

• Record Type: Journal Article
• Authors: Szynkiewicz, Wojciech
• Is Part Of: International journal of ad hoc and ubiquitous computing. Volume 17:Number 2/3(2014)
• Page Start: 73
• Page End: 81
• Publication Date: 2014-11-21
• Subjects: reconfigurable fixtures -- multi–agent systems -- MAS -- agent–based systems -- constraint satisfaction problem -- CSP -- action planning -- self–reconfiguration -- mobile robots -- robotic fixtures -- thin sheet workpieces -- supporting head placement -- mobile base positioning -- parallel kinematic machines -- PKM positioning; Ubiquitous computing -- Periodicals; Embedded computer systems -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Wireless communication systems -- Periodicals; Computer architecture -- Periodicals; 004.2
• Languages: English
• ISSNs: 1743-8225

Abstract

The paper presents a planning system for a self–reconfigurable fixture. The fixture is a multi–agent system composed a variable number of adaptable mobile robotic agents and a workbench on which these agents can move and lock. The paper proposes an approach for the generation of a feasible action plan for the locomotion, reconfiguration, and positioning of robotic fixtures to support the thin–sheet workpiece near the operating machine–tool. The multi–agent action planning problem is converted to a constraint satisfaction problem (CSP). CSP is a computational problem where the task is to decide for a given finite set of variables and constraints whether there is an assignment to the variables that satisfies all constraints. The proposed approach called Triple–CSP applies an incremental state search to solve three hierarchical planning tasks for the three components of each mobile agent: a supporting head placement, a mobile base positioning, and a parallel kinematic machine positioning, respectively. Thus, the planner takes into account all the relevant physical, geometrical, and time constraints.