Abstract
In Chaps. 2 and 3, we have theoretically demonstrated the effectiveness of such a physically constrained RMP scheme (and its solvers) on solving the joint-angle drift problem. In this chapter, a dual neural network (introduced in Chap. 4) and an LVI-based primal–dual neural network (introduced in Chap. 5) are presented for online repetitive motion planning (RMP) of redundant robot manipulators (with multilink planar manipulators as examples). As real-time QP solvers, the aforementioned two kinds of neural networks both have piecewise-linear dynamics and can globally exponentially converge to the optimal solution of strictly-convex quadratic programs. Furthermore, the neural-network-based physically constrained RMP scheme is simulated based on the multilink planar robot manipulators. Computer-simulation results substantiate the theoretical analysis and also show the effective remedy of the joint-angle drift problem of robot manipulators.
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References
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Zhang, Y., Zhang, Z. (2013). Examples of Planar Multilink Manipulators. In: Repetitive Motion Planning and Control of Redundant Robot Manipulators. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37518-7_8
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DOI: https://doi.org/10.1007/978-3-642-37518-7_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37517-0
Online ISBN: 978-3-642-37518-7
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