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Romansy 13 pp 421-429 | Cite as

Application of the RNT Robot to Milling and Polishing

  • K. Mianowski
  • K. Nazarczuk
  • M. Wojtyra
  • W. Szynkiewicz
  • C. Zieliński
  • A. Woźniak
Part of the International Centre for Mechanical Sciences book series (CISM, volume 422)

Abstract

A new type of robot with six DOF invented by K. Nazarczuk and K. Mianowski (1992) is presented in the paper. The robot arm has serial-parallel structure, high stiffness — comparable to that of parallel manipulators and very large workspace — comparable to that of serial robots. Lately the RNT robot has been adapted to milling of soft materials and polishing large surfaces. The controller of the robot is based on the MRROC++ library/language described by Zielinski at all. (1997, 1998, 1999). Due to the modularity of the software and its open structure, it is especially well suited to investigative tasks. It enables easy incorporation of any sensors. The information gathered by sensors can be used for on-line trajectory generation, monitoring the progress of machining or for subsequent analysis of results. The MRROC++ control system can generate any trajectories, and for the purpose of machining it interprets APT program CL-files produced by a UNIGRAPHICS CAD system. The power of the controller lies in the possibility of combining the off-line generated trajectory coded in APT with sensor-gathered information to generate an on-line resultant trajectory. The RNT robot has very good position repeatability (±0.02mm). For achieving good absolute accuracy a special procedure of local kinematic model correction has been developed and implemented. Large workspace and high manoeuvrability of the RNT robot enables it to machine work-pieces that no NC-machine can produce - any 3D surfaces can be obtained. The robot has successfully polished large metal surfaces and milled soft materials, e.g. wood and plastic.

Keywords

Parallel Manipulator Virtual Sensor Serial Robot Position Repeatability Large Workspace 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Wien 2000

Authors and Affiliations

  • K. Mianowski
    • 1
  • K. Nazarczuk
    • 1
  • M. Wojtyra
    • 1
  • W. Szynkiewicz
    • 2
  • C. Zieliński
    • 2
  • A. Woźniak
    • 2
  1. 1.Institute of Aeronautics and Applied MechanicsWarsaw University of TechnologyPoland
  2. 2.Institute of Control and Computation EngineeringWarsaw University of TechnologyPoland

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