Agent-based control for fuzzy behavior programming in robotic excavation

This paper discusses the concept, formulation, and implementation of the agent-based control for fuzzy behavior programming in robotic excavation. Petri net transducers are introduced to describe excavation control agent coordination and specification, while fuzzy control rules are used to implement primitive motions. A prototype laboratory excavation system is built with PUMA robotic manipulators and a force/torque sensor. Extensive experiments have been conducted and the results have demonstrated that the proposed control method is capable of continuously adapting and replanning its actions based on sensory feedback, and completing its excavation tasks in dynamic and unstructured environments.

[1]  Fei-Yue Wang,et al.  Implementing Adaptive Driving Systems for Intelligent Vehicles by Using Neuro-Fuzzy Networks , 2001 .

[2]  Fei-Yue Wang,et al.  Fuzzy behavior integration and action fusion for robotic excavation , 1996, IEEE Trans. Ind. Electron..

[3]  Sanjiv Singh,et al.  Models for Automated Earthmoving , 1999, ISER.

[4]  Fei-Yue Wang,et al.  Task translation and integration specification in intelligent machines , 1993, IEEE Trans. Robotics Autom..

[5]  Fei-Yue Wang,et al.  A fuzzy control system for an automated mining excavator , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[6]  Leonhard E. Bernold,et al.  Motion and Path Control for Robotic Excavation , 1993 .

[7]  H. F. Durrant-Whyte,et al.  Force and position control for electrohydraulic systems of A robotic excavator , 1999 .

[8]  Sanjiv Singh,et al.  The State of the Art in Automation of Earthmoving , 1997 .

[9]  Fei-Yue Wang,et al.  Experimental results of robotic excavation using fuzzy behavior control , 1996 .

[10]  Sanjiv Singh,et al.  Modeling and identification of soil-tool interaction in automated excavation , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[11]  Miroslaw J. Skibniewski,et al.  Cognitive Force Control of Excavators , 1993 .

[12]  Peter Corke,et al.  3D perception for mining robotics , 1998 .

[13]  Sanjiv Singh,et al.  Multi-resolution planning for earthmoving , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[14]  Sanjiv Singh The State of the Art in Automation of Earthmoving , 1997 .

[15]  Peter I. Corke,et al.  Experiments and Experiences in Developing a Large Robot Mining System , 1999, ISER.

[16]  Paul J. A. Lever,et al.  Intelligent Excavator Control System for Lunar Mining System , 1995 .

[17]  Fei-Yue Wang,et al.  Autonomous Robotic Mining Excavation Using Fuzzy Logic and Neural Networks , 1995, J. Intell. Fuzzy Syst..

[18]  Fei-Yue Wang,et al.  The VISTA Project and Its Applications , 2002, IEEE Intell. Syst..

[19]  Fei-Yue Wang,et al.  A coordination theory for intelligent machines , 1990, Autom..

[20]  MengChu Zhou,et al.  Petri net synthesis for discrete event control of manufacturing systems , 1992, The Kluwer international series in engineering and computer science.

[21]  Fei-Yue Wang,et al.  Agent-based control systems for operation and management of intelligent network-enabled devices , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[22]  Peter I. Corke,et al.  Autonomous control of underground mining vehicles using reactive navigation , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[23]  Chris Hendrickson,et al.  A Strategic Planner for Robot Excavation , 1989 .