Biomimetic design applies biological analogies to solve design problems and has been known to produce innovative solutions. However, when designers are asked to perform biomimetic design, they often have difficulty recognizing analogies between design problems and biological phenomena. Therefore, this research aims to investigate designer behaviors that either hinder or promote the use of analogies in biomimetic design. A verbal protocol study was conducted on 30 engineering students working in small teams while participating in biomimetic design sessions. A coding scheme was developed to analyze cognitive processes involved in biomimetic design. We observed that teams were less likely to apply overall biological analogies if they tended to recall existing solutions that could be easily associated with specific superficial or functional characteristics of biological phenomena. We also found that the tendency to evaluate ideas, which reflects critical thinking, correlates with the likelihood of identifying overall biological analogies. Insights from this paper may contribute toward developing generalized methods to facilitate biomimetic design.

When generating gaits for soft robots (those with no explicit joints), it is not evident that undulating control schemes are the most efficient. In considering alternative control schemes, however, the computational costs of evaluating continuum mechanic models of soft robots represent a significant bottleneck. We consider the use of lumped dynamic models for soft robotic systems. Such models have not been employed previously to design gaits for soft robotic systems, though they are widely used to simulate robots with compliant joints. A major question is whether these methods are accurate enough to be representations of soft robots to enable gait design and optimization. This paper addresses the potential “reality gap” between simulation and experiment for the particular case of a soft caterpillar-like robot. Experiments with a prototype soft crawler demonstrate that the lumped dynamic model can capture essential soft-robot mechanics well enough to enable gait optimization. Significantly, experiments verified that a prototype robot achieved high performance for control patterns optimized in simulation and dramatically reduced performance for gait parameters perturbed from their optimized values.

This paper summarizes various aspects of identifying and applying biological analogies in engineering design using a natural-language approach. To avoid the immense as well as potentially biased task of creating a biological database specifically for engineering design, the chosen approach searches biological knowledge in natural-language format, such as books and papers, for instances of keywords describing the engineering problem. Strategies developed to facilitate this search are identified, and how text descriptions of biological phenomena are used in problem solving is summarized. Several application case studies are reported to illustrate the approach. The value of the natural-language approach is demonstrated by its ability to identify relevant biological analogies that are not limited to those entered into a database specifically for engineering design.

The growing movement of biologically inspired design is driven in part by the need for sustainable development and in part by the recognition that nature could be a source of innovation. Biologically inspired design by definition entails cross-domain analogies from biological systems to problems in engineering and other design domains. However, the practice of biologically inspired design at present typically is ad hoc, with little systemization of either biological knowledge for the purposes of engineering design or the processes of transferring knowledge of biological designs to engineering problems. In this paper we present an intricate episode of biologically inspired engineering design that unfolded over an extended period of time. We then analyze our observations in terms of why, what, how, and when questions of analogy. This analysis contributes toward a content theory of creative analogies in the context of biologically inspired design.

In this paper, a new biomimetic tendon-driven actuation system for prosthetic and wearable robotic hand applications is presented. It is based on the combination of compliant tendon cables and one-way shape memory alloy (SMA) wires that form a set of agonist–antagonist artificial muscle pairs for the required flexion/extension or abduction/adduction of the finger joints. The performance of the proposed actuation system is demonstrated using a 4 degree-of-freedom (three active and one passive) artificial finger testbed, also developed based on a biomimetic design approach. A microcontroller-based pulse-width-modulated proportional-derivation (PWM-PD) feedback controller and a minimum jerk trajectory feedforward controller are implemented and tested in an ad hoc fashion to evaluate the performance of the finger system in emulating natural joint motions. Part II describes the dynamic modeling of the above nonlinear system, and the model-based controller design.