A dual neural network for bi-criteria kinematic control of redundant manipulators

Yunong Zhang, Jun Wang, Yangsheng Xu

Research output: Contribution to journalArticlepeer-review

130 Citations (Scopus)


A dual neural network is presented for the bi-criteria kinematic control of redundant manipulators. To diminish the discontinuity of minimum infinity-norm solutions, the kinematic-control problem is formulated in the bi-criteria of the infinity and Euclidean norms. Physical constraints such as joint limits and joint velocity limits are also incorporated simultaneously into the proposed kinematic control scheme. The single-layer dual neural network model with a simple structure is developed for bi-criteria redundant resolution of redundant manipulators subject to robot physical constraints. The dual neural network is shown to be globally convergent to optimal solutions in the bi-criteria sense, and is demonstrated to be effective in controlling the PA10 robot manipulator.

Original languageEnglish
Pages (from-to)923-931
Number of pages9
JournalIEEE Transactions on Robotics and Automation
Issue number6
Publication statusPublished - Dec 2002
Externally publishedYes


  • Bi-criteria
  • Dual neural network
  • Joint limits
  • Joint velocity limits
  • Kinematically
  • Redundant manipulators


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