The Design and Development of an Omni-Directional Mobile Robot Oriented to an Intelligent Manufacturing System

In order to transport materials flexibly and smoothly in a tight plant environment, an omni-directional mobile robot based on four Mecanum wheels was designed. The mechanical system of the mobile robot is made up of three separable layers so as to simplify its combination and reorganization. Each modularized wheel was installed on a vertical suspension mechanism, which ensures the moving stability and keeps the distances of four wheels invariable. The control system consists of two-level controllers that implement motion control and multi-sensor data processing, respectively. In order to make the mobile robot navigate in an unknown semi-structured indoor environment, the data from a Kinect visual sensor and four wheel encoders were fused to localize the mobile robot using an extended Kalman filter with specific processing. Finally, the mobile robot was integrated in an intelligent manufacturing system for material conveying. Experimental results show that the omni-directional mobile robot can move stably and autonomously in an indoor environment and in industrial fields.

[1]  Roger V. Bostelman,et al.  Literature Review of Mobile Robots for Manufacturing , 2015 .

[2]  Luigi Fortuna,et al.  Modeling and design of novel photo-thermo-mechanical microactuators , 2002 .

[3]  Thomas Rühr,et al.  Integration and Assessment of Multiple Mobile Manipulators in a Real-World Industrial Production Facility , 2014, ISR 2014.

[4]  Damien Sallé,et al.  Towards a flexible production system Environment Server implementation , 2015, IEEE EUROCON 2015 - International Conference on Computer as a Tool (EUROCON).

[5]  Klaus-Dieter Thoben,et al.  "Industrie 4.0" and Smart Manufacturing - A Review of Research Issues and Application Examples , 2017, Int. J. Autom. Technol..

[6]  Giovanni Indiveri,et al.  Swedish Wheeled Omnidirectional Mobile Robots: Kinematics Analysis and Control , 2009, IEEE Transactions on Robotics.

[7]  Kiattisin Kanjanawanishkul,et al.  Omnidirectional wheeled mobile robots: wheel types and practical applications , 2016 .

[8]  Günter Ullrich,et al.  Automated Guided Vehicle Systems: A Primer with Practical Applications , 2014 .

[9]  Stephen F. Smith,et al.  Mobile manufacturing of large structures , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[10]  Shiqi Li,et al.  A Robust O(n) Solution to the Perspective-n-Point Problem , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Jun Qian,et al.  Fast reconstruction of an unmanned engineering vehicle and its application to carrying rocket , 2014 .

[12]  Bin Zi,et al.  Design, analysis and control of a winding hybrid-driven cable parallel manipulator , 2017 .

[13]  J. L. Roux An Introduction to the Kalman Filter , 2003 .

[14]  Yang Ru-qing,et al.  Research on Semi-Automatic Bomb Fetching for an EOD Robot , 2007 .

[15]  Jun Lin,et al.  Localization, obstacle avoidance planning and control of a cooperative cable parallel robot for multiple mobile cranes , 2015 .

[16]  William D. Smart,et al.  Programming Robots with ROS: A Practical Introduction to the Robot Operating System , 2015 .

[17]  Andre Heller,et al.  Global Localization and Position Tracking of Automatic Guided Vehicles using passive RFID Technology , 2014, ISR 2014.

[18]  Ching-Chih Tsai,et al.  Global Localization Using Dead-Reckoning and Kinect Sensors for Robots with Omnidirectional Mecanum Wheels , 2014 .

[19]  Seong-Bae Park,et al.  Kalman Filter Sensor Fusion for Mecanum Wheeled Automated Guided Vehicle Localization , 2015, J. Sensors.

[20]  D. Herrero-Pérez,et al.  An Accurate and Robust Flexible Guidance System for Indoor Industrial Environments , 2013 .

[21]  Hyungpil Moon,et al.  Flexible suspension mechanism for stable driving of a differential drive mobile robot , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[22]  David G. Lowe,et al.  Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration , 2009, VISAPP.

[23]  Daniel Hess,et al.  Linux Based Control Framework for Mecnaum Based Omnidirectional Automated Guided Vehicles , 2013 .

[24]  Sungshin Kim,et al.  Inertial navigation system for an automatic guided vehicle with Mecanum wheels , 2012 .

[25]  Christopher Hunt,et al.  Notes on the OpenSURF Library , 2009 .

[26]  Ana Barjau,et al.  Holonomy in mobile robots , 2009, Robotics Auton. Syst..

[27]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  Jong-Jin Bae,et al.  Design Optimization of a Mecanum Wheel to Reduce Vertical Vibrations by the Consideration of Equivalent Stiffness , 2016 .

[29]  Wolfram Burgard,et al.  G2o: A general framework for graph optimization , 2011, 2011 IEEE International Conference on Robotics and Automation.

[30]  Eric Guizzo,et al.  Three Engineers, Hundreds of Robots, One Warehouse , 2008, IEEE Spectrum.

[31]  Frederik Hegger,et al.  RoboCup@Work: Competing for the Factory of the Future , 2014, RoboCup.

[32]  B. Y. Duan,et al.  Dynamic modeling and active control of a cable-suspended parallel robot , 2008 .

[33]  Wolfram Burgard,et al.  On the position accuracy of mobile robot localization based on particle filters combined with scan matching , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[34]  Jun Qian,et al.  Mechanical Design and Control System of an Omni-directional Mobile Robot for Material Conveying , 2016 .

[35]  Jin S. Lee,et al.  The sources of position errors of omni-directional mobile robot with Mecanum wheel , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[36]  Luigi di Stefano,et al.  Fusion of Inertial and Visual Measurements for RGB-D SLAM on Mobile Devices , 2015, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW).

[37]  Jouni Mattila,et al.  System Integration for Real-Time Mobile Manipulation , 2014 .