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This paper proposes an innovative jerk-layer multi-criteria simultaneous optimization (JLMCSO) scheme to effectively address the non-cyclic motion, non-zero final joint velocity, and joint-jerk incontinuity problems for jerk-bounded redundant robots. The JLMCSO scheme novelly integrates the minimal jerk norm, jerk-layer cyclic motion generation, and infinity-norm jerk minimality criteria as a hybrid performance index via three weighting factors, incorporating the joint physical restraints concurrently. The quadratic programming (QP) reformulation of the JLMCSO scheme is presented, and then the resulting QP problem is resolved by utilizing a projection-type iterative algorithm. Finally, comparative simulative experiments based on PUMA560 robot are performed to affirm the validity, superiority, and adaptability of the JLMCSO scheme.

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Jerk-Layer Multi-Criteria Simultaneous Optimization for Control of Redundant Robots

  • 会议论文

  • 发表日期：

    2026年

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  • Binbin Qiu,
  • Yusheng Zeng,
  • Jinjin Guo,
  • Guangfeng Cheng

摘要

This paper proposes an innovative jerk-layer multi-criteria simultaneous optimization (JLMCSO) scheme to effectively address the non-cyclic motion, non-zero final joint velocity, and joint-jerk incontinuity problems for jerk-bounded redundant robots. The JLMCSO scheme novelly integrates the minimal jerk norm, jerk-layer cyclic motion generation, and infinity-norm jerk minimality criteria as a hybrid performance index via three weighting factors, incorporating the joint physical restraints concurrently. The quadratic programming (QP) reformulation of the JLMCSO scheme is presented, and then the resulting QP problem is resolved by utilizing a projection-type iterative algorithm. Finally, comparative simulative experiments based on PUMA560 robot are performed to affirm the validity, superiority, and adaptability of the JLMCSO scheme.