On the Significance and Impact of a Novel Design Framework Leading to Optimal Computational Algorithms Encompassing Linear Multi-Step Methods for Structural Dynamics

The Bisociative Design framework proposed in this work aims to quantify hidden, previously unknown design synergies/insights across seemingly unrelated product domains. Despite the overabundance of data characterizing the digital age, designers still face tremendous challenges in transforming data into knowledge throughout the design processes. Data driven methodologies play a significant role in the product design process ranging from customer preference modeling to detailed engineering design. Existing data driven methodologies employed in the design community generate mathematical models based on data relating to a specific domain and are therefore constrained in their ability to discover novel design insights beyond the domain itself (I.e., cross domain knowledge). The Bisociative Design framework proposed in this work overcomes the limitations of current data driven design methodologies by decomposing design artifacts into form patterns, function patterns and behavior patterns and then evaluating potential cross-domain design insights through a proposed multidimensional Bisociative Design metric. A hybrid marine model involving multiple domains (capable of flight and marine navigation) is used as a case study to demonstrate the proposed Bisociative Design framework and explain how associations and novel design models can be generated through the discovery of hidden, previously unknown patterns across multiple, unrelated domains.

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A straightforward and miniature implementation method of postural synergies for replicating human grasp characteristics accurately and intuitively

Bioinspiration & Biomimetics ◽

10.1088/1748-3190/ac3f7f ◽

2021 ◽

Author(s):

Yuan Liu ◽

Li Jiang ◽

Hong Liu ◽

Dong Ming

Keyword(s):

Transmission Ratio ◽

Physical Parameters ◽

Robot Hand ◽

Design Framework ◽

Electrical System ◽

Implementation Method ◽

Complex Mapping ◽

Motion Characteristics ◽

Novel Design ◽

Postural Synergies

Abstract The postural synergies have great potentials to replicate human grasp characteristics, simplify grasp control and reduce the number of hardware needed actuators. However, due to the complex mapping relationship and jagged transmission ratio, the implemented mechanisms are always too bulky and loose which greatly limits its application. For current solutions, the replicating accuracy of motion characteristics or control intuition are compromised, and hitherto no work reports the replicating errors in literatures. To overcome these limitations, we present a novel design framework to determine the actuation configuration, implemented scheme and physical parameters. In this way, the mechanism is miniaturized and can be compactly embedded in hand palm, a self-contained synergy robot hand that integrated with mechanism, sensors and suited electrical system is built. The experiments demonstrate that the robot hand can accurately replicate the motion characteristics of two primary synergies, keep the control intuition to simplify grasp control, perform a better anthropomorphic motion capability and grasp different objects with versatile grasp functionality.

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