Intelligent navigation strategies for an automated earthwork system

Abstract The need for automation to better deal with the safety and the productivity requirements of earthwork operations in today's construction market has been increasing. In this paper, intelligent navigation strategies, which are essential for an automated earthwork system to execute excavation effectively, are suggested. The first type, which we call a global navigation strategy, creates movable paths between two work areas, reflecting the size and safety buffer of equipment, and suggests a method to reach the target point without collision with mobile obstacles. The second type, which we call a local navigation strategy, generates efficient paths for earthwork operations in a given work area. The possible application is tested using computer simulation. The results show that the navigation strategies can introduce intelligence to the automated system to generate a safe and effective path for remote or automated earthwork operations without human intervention and to execute earthwork in a hazard-free environment.

[1]  Nils J. Nilsson,et al.  A mobius automation: an application of artificial intelligence techniques , 1969, IJCAI 1969.

[2]  Myung Jin Chae,et al.  A 3D surface modeling system for intelligent excavation system , 2011 .

[3]  Edward J. Jaselskis,et al.  PILOT STUDY ON IMPROVING THE EFFICIENCY OF TRANSPORTATION PROJECTS USING LASER SCANNING , 2003 .

[4]  Kyo-Jin Koo,et al.  Construction Robot Path-Planning for Earthwork Operations , 2003 .

[5]  Daehie Hong,et al.  A Path Planning for Autonomous Excavation Based on Energy Function Minimization , 2010 .

[6]  Günther Schmidt,et al.  Path planning and guidance techniques for an autonomous mobile cleaning robot , 1995, Robotics Auton. Syst..

[7]  Vladimir J. Lumelsky,et al.  A paradigm for incorporating vision in the robot navigation function , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[8]  Sung-Keun Kim,et al.  A Platform Moving Model for an Intelligent Excavator , 2007 .

[9]  R. Araujo,et al.  Fuzzy ART based approach for real-time map building , 1998, AMC'98 - Coimbra. 1998 5th International Workshop on Advanced Motion Control. Proceedings (Cat. No.98TH8354).

[10]  Jeffrey S. Russell,et al.  Framework for an intelligent earthwork system: Part II. Task identification/scheduling and resource allocation methodology , 2003 .

[11]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1986 .

[12]  Myung Jin Chae,et al.  3D Work Environment Modeling for the Intelligent Excavation System (IES) , 2009 .

[13]  Jongwon Seo,et al.  Task planner design for an automated excavation system , 2011 .

[14]  Howie Choset,et al.  Path Planning for Robotic Demining: Robust Sensor-Based Coverage of Unstructured Environments and Probabilistic Methods , 2003, Int. J. Robotics Res..

[15]  Hanan Samet,et al.  Applications of spatial data structures , 1989 .

[16]  Hiroshi Yamamoto,et al.  Basic Technology toward Autonomous Hydraulic Excavator , 2009 .

[17]  Junbok Lee,et al.  A Study on the Development of Technology Roadmap for Construction Automation , 2008 .

[18]  Vladimir J. Lumelsky,et al.  Path-planning strategies for a point mobile automaton moving amidst unknown obstacles of arbitrary shape , 1987, Algorithmica.

[19]  Michael A. Mooney,et al.  Instrumentation of a roller compactor to monitor vibration behavior during earthwork compaction , 2008 .

[20]  Rodney A. Brooks,et al.  Solving the Find-Path Problem by Good Representation of Free Space , 1983, Autonomous Robot Vehicles.

[21]  D. T. Lee,et al.  Generalization of Voronoi Diagrams in the Plane , 1981, SIAM J. Comput..

[22]  Ehud Rivlin,et al.  Sensory-based motion planning with global proofs , 1997, IEEE Trans. Robotics Autom..

[23]  Tomás Lozano-Pérez,et al.  Automatic Planning of Manipulator Transfer Movements , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[24]  Hong-Chul Kim,et al.  A Model for Allocating Automated Earthwork Equipment Using Contract Net , 2005 .

[25]  Michael Gervautz,et al.  A simple method for color quantization: octree quantization , 1990 .

[26]  Vladimir J. Lumelsky,et al.  An algorithm for maze searching with azimuth input , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[27]  Jean-Claude Latombe,et al.  Robot motion planning , 1970, The Kluwer international series in engineering and computer science.

[28]  Shuzhi Sam Ge,et al.  New potential functions for mobile robot path planning , 2000, IEEE Trans. Robotics Autom..