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Register a new userSupplementary Material to: Passive Controller Realization of a Biquadratic Impedance with Double Poles and Zeros as a Seven-Element Series-Parallel Network for Effective Mechanical Control
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This report presents some supplementary material to the paper entitled Passive controller realization of a biquadratic impedance with double poles and zeros as a seven-element Series-parallel network for effective mechanical control [1].
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This is a supplementary material to Realization of three-port spring networks with inerter for effective mechanical control [1], which provides the detailed proofs of some results. For more background information, refer to [2]-[32] and references therein.
This report includes the original manuscript and the supplementary material of Realization of Biquadratic Impedance as Five-Element Bridge Networks.
This report includes the original manuscript (pp. 2-40) and the supplementary material (pp. 41-48) of Passive Mechanical Realizations of Bicubic Impedances with No More Than Five Elements for Inerter-Based Control Design.
This is supplementary material to Realizations of a special class of admittances with strictly lower complexity than canonical forms [1], which presents the detailed proofs of some results. For more background information, refer to [2]-[22] and references therein.
Robust dynamic interactions are required to move robots in daily environments alongside humans. Optimisation and learning methods have been used to mimic and reproduce human movements. However, they are often not robust and their generalisation is limited. This work proposed a hierarchical control architecture for robot manipulators and provided capabilities of reproducing human-like motions during unknown interaction dynamics. Our results show that the reproduced end-effector trajectories can preserve the main characteristics of the initial human motion recorded via a motion capture system, and are robust against external perturbations. The data indicate that some detailed movements are hard to reproduce due to the physical limits of the hardware that cannot reach the same velocity recorded in human movements. Nevertheless, these technical problems can be addressed by using better hardware and our proposed algorithms can still be applied to produce imitated motions.
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