Open Access
Issue
MATEC Web Conf.
Volume 220, 2018
2018 The 2nd International Conference on Mechanical, System and Control Engineering (ICMSC 2018)
Article Number 06003
Number of page(s) 7
Section Intelligent Robot and Control Technology
DOI https://doi.org/10.1051/matecconf/201822006003
Published online 29 October 2018
  1. Dong L.; Cao L. Effects of residual riblets of impeller’s hub surface on aerodynamic performance of centrifugal compressors. 9: 1, 99-113, DOI: 10.1080/19942060.2015.1004 813, (2015) [Google Scholar]
  2. Zhang Z.; Liu Z.; Cheng Q.; et al. An approach of comprehensive error modeling and accuracy allocation for the improvement of reliability and optimization of cost of a multi-axis NC machine tool. 89: 1-4, 1-19, DOI: 10.1007/s00170-016-8981-x, (2016) [Google Scholar]
  3. Olabi A.; Béaré R.; Gibaru O.; et al. Feedrate planning for machining with industrial six-axis robots. 18: 5, 471-482, DOI: 10.1016/j.conengprac.2010.01.004, (2010) [Google Scholar]
  4. Iglesias I.; Sebastián M A.; Ares J E. Overview of the State of Robotic Machining: Current Situation and Future Potentia. 132, 911-917, DOI: 10.1016/j.proeng.2015.12.577, (2015) [Google Scholar]
  5. Kubela T.; Pochyly A.; Singule V. Assessment of industrial robots accuracy in relation to accuracy improvement in machining processes. 720-725, DOI: 10.1109/EPEPEMC.2016.7752083, (2016) [Google Scholar]
  6. Kelaiaia R. Improving the pose accuracy of the Delta robot in machining operations, 91: 5-8, 2205-2215, DOI 10.1007/s00170-016-9955-8, (2017) [Google Scholar]
  7. Giberti H.; Sbaglia L.; Urgo M. A path planning algorithm for industrial processes under velocity constraints with an application to additive manufacturing. 43, 160-167, DOI: 10.1016/jjmsy.2017.03.003, (2017) [Google Scholar]
  8. Bharathi A.; Dong J. Feedrate optimization for smooth minimum-time trajectory generation with higher order constraints. 82: 5-8, 1029-1040, DOI: 10.1007/s00170-015-7447-x, (2016) [Google Scholar]
  9. Valente A.; Baraldo S. Carpanzano E. Smooth trajectory generation for industrial robots performing high precision assembly processes. 2017, https://doi.org/10.1016/j.cirp.2017.04.105. [Google Scholar]
  10. Avram O.; Valente A. Trajectory Planning for Reconfigurable Industrial Robots Designed to Operate in a High Precision Manufacturing Industry. 2016, 57: 461–466, DOI: 10.1016/j.procir.2016.11.080. [Google Scholar]
  11. Xu Z.; Wei S.; Wang N.; et al. Trajectory Planning with Bezier Curve in Cartesian Space for Industrial Gluing Robot. 146-154, (2014) [Google Scholar]
  12. Shi B H.; He J P. The robot motion trajectory algorithm research based on B-spline and new velocity planning. DOI: 10.1109/CCDC.2016.7532065, (2016) [Google Scholar]
  13. Gou Z J.; Wang C. The Trajectory Planning and Simulation for Industrial Robot Based on Fifth-Order B-Splines. 538, 367-370, DOI: 10.4028/www.scientific.net/AMM.538.367, (2014) [Google Scholar]
  14. Lin Y.; Zhao H.; Ding H. Posture optimization methodology of 6R industrial robots for machining using performance evaluation indexes. 48, 59-72, DOI: 10.1016/j.rcim.2017.02.002, (2017) [Google Scholar]
  15. Li S.; Xie X.; Yin L. Research on Robotic Trajectory Automatic Generation Method for Complex Surface Grinding and Polishing. 124-135, (2014) [Google Scholar]
  16. Siciliano B.; Sciavicco L.; Villani L.; et al. Robotics: modeling, planning and control. (2010). [Google Scholar]
  17. Corke P. Robotics, Vision and Control. Springer Berlin Heidelberg, (2011). [Google Scholar]
  18. Liu Y.; Hui L I.; Wang Y. Realization of a 5-axis NURBS Interpolation with Controlled Angular Velocity. 25: 1, 124-130, DOI: 10.1016/S1000-9361(11)60370-1, (2012) [Google Scholar]
  19. Liu Y.; Jin R.; Chen M.; et al. Contour propagation using non-uniform cubic B-splines for lung tumor delineation in 4D-CT. 1-13, DOI: 10.1007/s11548-016-1457-5, (2016) [Google Scholar]
  20. Vulliez M.; Lavernhe S.; Bruneau O. Dynamic approach of the feedrate interpolation for trajectory planning process in multi-axis machining. 88: 5-8, 1-12, DOI: 10.1007/s00170-016-8903-y, (2017) [Google Scholar]
  21. Sun Y.; Zhao Y.; Bao Y.; et al. A novel adaptive-feedrate interpolation method for NURBS tool path with drive constraints. 2014, 77: 1, 74-81, DOI: 10.1016/j.ijmachtools.11.002, (2013) [Google Scholar]
  22. Bian Z.; Ye Z.; Mu W. Kinematic analysis and simulation of 6-DOF industrial robot capable of picking up die-casting products. 41-44, DOI: 10.1109/AUS.2016.7748017, (2016) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.