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Two Acceleration-Layer Configuration Amendment Schemes of Redundant Robot Arms Based on Zhang Neurodynamics Equivalency.
Tang, Zanyu; Mao, Mingzhi; Zhang, Yunong; Tan, Ning.
Afiliação
  • Tang Z; School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China.
  • Mao M; School of Computer Science and Engineering, Jishou University, Jishou 416000, China.
  • Zhang Y; School of Software Engineering, Sun Yat-sen University, Zhuhai 519082, China.
  • Tan N; School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China.
Biomimetics (Basel) ; 9(7)2024 Jul 17.
Article em En | MEDLINE | ID: mdl-39056876
ABSTRACT
Two innovative acceleration-layer configuration amendment (CA) schemes are proposed to achieve the CA of constrained redundant robot arms. Specifically, by applying the Zhang neurodynamics equivalency (ZNE) method, an acceleration-layer CA performance indicator is derived theoretically. To obtain a unified-layer inequality constraint by transforming from angle-layer and velocity-layer constraints to acceleration-layer constraints, five theorems and three corollaries are theoretically derived and rigorously proved. Then, together with the unified acceleration-layer bound constraint, an enhanced acceleration-layer CA scheme specially considering three-layer time-variant physical limits is proposed, and a simplified acceleration-layer CA scheme considering three-layer time-invariant physical limits is also proposed. The proposed CA schemes are finally formulated in the form of standard quadratic programming and are solved by a projection neurodynamics solver. Moreover, comparative simulative experiments based on a four-link planar arm and a UR3 spatial arm are performed to verify the efficacy and superiority of the proposed CA schemes. At last, physical experiments are conducted on a real Kinova Jaco2 arm to substantiate the practicability of the proposed CA schemes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article