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Point-to-Point Trajectory Planning of Flexible Redundant Robot Manipulators Using Genetic Algorithms
Shigang Yue , Dominik Henrich , S. K. Tso , W. L. Xu

Abstract (english)
The paper focuses on the problem of point-to-point trajectory planning for flexible redundant robot manipulators (FRM) in joint space. Compared with irredundant flexible manipulators, a FRM possesses additional possibilities during point-to-point trajectory planning due to its kinematics redundancy. A trajectory planning method to minimize vibration and/or executing time of a point-to-point motion is presented for FRM based on Genetic Algorithms (GAs). Kinematics redundancy is integrated into the presented method as planning variables. Quadrinomial and quintic polynomial are used to describe the segments that connect the initial, intermediate, and final points in joint space. The trajectory planning of FRM is formulated as a problem of optimization with constraints. A planar FRM with three flexible links is used in simulation. Case studies show that the method is applicable.

Publication data

Year: 2001
Publication date: 03. September 2001
Source: Journal of Robotica, vol 20, pp 269-280, 2002
Keywords (english): flexible-link robot , genetic algorithms , point-to-point , redundancy , trajectory planning , vibration
Referrer: http://www.ai3.uni-bayreuth.de/resypub/?mode=pub_show&pub_ref=yue2001e

BibTeX

@MISC{yue2001e,
  TITLE             = "Point-to-Point Trajectory Planning of Flexible Redundant Robot Manipulators Using Genetic Algorithms",
  AUTHOR            = "Yue, Shigang and Henrich, Dominik and Tso, S. K. and Xu, W. L.",
  YEAR              = "2001",
  JOURNAL           = "Journal of Robotica, vol 20, pp 269-280, 2002",
  HOWPUBLISHED      = "\url{http://www.ai3.uni-bayreuth.de/resypub/?mode=pub_show&pub_ref=yue2001e}",
}

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yue2001e.PointtoPoint.Trajectory.Planning.of.Flexible.Redundant.Robot.Manipulators.Using.Genetic.Algorithms.djvu   471.3K   english   DJVU   download preprint
yue2001e.PointtoPoint.Trajectory.Planning.of.Flexible.Redundant.Robot.Manipulators.Using.Genetic.Algorithms.pdf   1.2M   english   PDF   download preprint


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