Two Acceleration-Layer Configuration Amendment Schemes of Redundant Robot Arms Based on Zhang Neurodynamics Equivalency

Author:

Tang Zanyu12ORCID,Mao Mingzhi3,Zhang Yunong1ORCID,Tan Ning1ORCID

Affiliation:

1. School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China

2. School of Computer Science and Engineering, Jishou University, Jishou 416000, China

3. School of Software Engineering, Sun Yat-sen University, Zhuhai 519082, China

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.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Natural Science Foundation of Hunan Province

Publisher

MDPI AG

Reference32 articles.

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