Investigation on a New Discrete-Time Synchronous Motion Planning Scheme for Dual-Arm Robot Systems

Wang, Tie; Guo, Dongsheng

doi:10.1109/access.2020.3035602

Cited by 4 publications

(3 citation statements)

References 42 publications

(74 reference statements)

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“…3(a) and 3(b), it is observed that solutions ( 6) and ( 8) have high precision from start. In contrast, solutions (10) and ( 12) have high precision after nearly one hundred iterations. Thus, it is substantiated that TVLES-SCF solutions do not have convergence procedures and directly calculate and obtain future-instant results, while conventional solutions VOLUME 10, 2022 do not.…”

Section: Numerical Experimentsmentioning

confidence: 98%

“…− sin(0.1(i − j)t k )/(i − j), when i > j sin(0.1it k ) + 3, when i = j cos(0.1(j − i)t k )/(j − i), when i < j and b i (t k ) = cos(t k ), when i is odd sin(0.5t k ), when i is even, (15) where i, j = 1, 2, • • • , 9. First, to substantiate the effectiveness of the proposed solutions, we conduct a numerical experiment in which we employ the TVLES-SCF-I solution (6) and conventional solution (10) to solve the above TVLES problem (15). The sampling gap is set as 0.1 s and the coefficient h = 0.1.…”

Section: Numerical Experimentsmentioning

confidence: 99%

“…FIGURE 3. Comparisons of the errors of (a) TVLES-SCF solutions (6) and (8), (b) conventional stability-constraint solutions(10) and (12) satisfying stability-constraint, (c) conventional stability-constraint solutions (13) and (14) without satisfying stability-constraint when sampling gap τ = 0.01 s.…”

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confidence: 99%

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Stability-Constraint-Free Solutions to Solve Time-Varying Linear Equation System

Fan

Zhu

et al. 2022

IEEE Access

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Time-varying linear equation systems have been solved by the traditional zeroing neural dynamics approach in recent years. However, this method has to satisfy the stability constraint, which is a very rigorous condition. For this reason, traditional Lagrange-type finite difference formulas fail to lead to effective solutions, and we have to utilize more instants and reduce accuracy so that this condition is satisfied. In this work, we develop a new method of solving a time-varying linear equation system, which is based on theoretical solution decomposition. As a result, the proposed solutions are stability-constraint-free. We do not have to meticulously search effective time-discretization formulas because traditional Lagrange-type formulas are sufficient and especially effective. In addition, the proposed solutions have other advantages. For example, they do not need convergence procedures; they do not have storage requirements for past calculative results; and they are still effective when the sampling gap value is relatively large. Detailed comparisons are presented in this paper. Comparative numerical experiments are also shown to substantiate the effectiveness and advantages of the proposed solutions.

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Section: Numerical Experimentsmentioning

confidence: 98%