Akanyeti, O., Venturelli, R., Visentin, F., Chambers, L., Megill, W.M. and Fiorini, P. (2011). What information do Karman streets offer to ﬂow sensing? Bioinspiration and Biomimetics, 6, 036001.
In Akanyeti et.al, the authors use a sensor array that mimics the lateral lines of fish to sense complex hydrodynamic flows known as a Karman vortex street (KVS). According to the authors, flow information can be used to understand dipole fields, which are created by the flapping tail of a fish while swimming. Within this field, unsteady flows can be created that must be sensed and analyzed by swimming animals and machines alike to maximize performance [1, 2].
KVS structures form due to the presence of objects in a flow (such as prey or obstacles), and form as a columnar array of vortices which are propagated over time. KVS are turbulent, but can also be predictable. In this way, some fishes may exploit the information embedded in such flows to reduce energy expenditures. This has clear benefits to engineered systems which can sense and process these flows in real-time.
The authors remove the fluid-body interaction for purposes of establishing a baseline in building a predictive model for KVS structure and ultimately establishing a series of design principles. This is where the disembodied lateral line comes into play. The vortex profile of a KVS (Figure 3 in the paper) is shown below. A KVS consists of three regions: suction, vortex formation, and the vortex street. The street is shown in this diagram as the light blue region trailing from the area of yellows and reds which define vortex formation. The vortex detachment point (rightmost "X") is the point where the vortex formation region ends, and vortices travel off to the right as discrete packets of turbulence.
The authors also computed the power spectrum of their generated KVSs to evaluate periodicity in space and time. The authors use Fourier-based decomposition and deterministic noise to filter the KVS signature. The predominant frequencies are then recovered A KVS can be characterized by two dominant frequency components, but the boundary of a KVS requires many more.
Calisti, M., Giorelli, M., Levy, G., Mazzolai, B., Hochner, B., Laschi, C., and Dario, P. (2011). An octopus-bioinspired solution to movement and manipulation for soft robots. Bioinspiration and Biomimetics, 6(3), 036002.
In Calisti et.al, the authors review the state-of-the-art regarding soft robotics. Soft robots are a subset of continuum robotics, which bend easily (e.g. have a compliant physical structure), and have no rigid joints or other components. The "softness" of these machines is achieved by using strong, flexible materials for the structure and specialized actuators for the joints. One consequence of soft robots is that the biomimetic template must not be explicitly based on an animal design with skeletal structure. While this may seem to reduce the number of possible templates for engineering applications, there are actually several highly useful like designs in nature.
What kind of compliant yet highly-functional structures has the animal kingdom provided as a template? One example is the "muscular hydrostat" . In the article, this is characterized by octopus tentacles (OctArm) and an elephant trunk (Active Hose). The authors also characterize soft robots as either locomotors or manipulators. The muscular hydrostat is capable of performing both of these functions. Muscular hydrostats use a series of linearly-coupled muscle ganglia that can be coordinated globally to produce a semi-rigid locomotory structure, or locally to enable manipulation and fine motor control.
The authors also offer a candidate algorithm, show examples of how the soft robotic structure deforms during movement and when interacting with objects (Figure 8 in the paper), and a dictionary of robotic movements that map to behaviors observed in nature. Finally, the authors relate their work on soft robots to the principle of embodiment , which suggests that there is a complex interplay between movement control, morphology, and the environment.
From left: algorithm proposed in paper, dictionary of robotic actions mapped to natural behaviors, and Figure 8 from paper (geometric deformation during movement).
Peterson, K., Birkmeyer, P., Dudley, R., and Fearing, R.S. (2011). A wing-assisted running robot and implications for avian flight evolution. Bioinspiration and Biomimetics, 6(3), 046008.
Petersen et.al have examined the design of flapping wings by testing a range of wing morphologies. These experiments were conducted in a wind tunnel, while lift and drag forces were measured to evaluate each design. As background, the authors point out that airflow instability that causes gliding microrobots robots to catastrophically fail, while ground-reaction force interactions can destabilize ground-based locomotory robots in a similar manner . Consider that many of the animals who glide (birds, flying squirrels, etc.) also use a second mode of locomotion.
Flapping flight, with wingbeats that result in a highly-complex set of regulatory mechanisms which offset the effects of air turbulence, is superior to gliding flight in terms of minimizing the possible modes of failure. Yet flapping flight still does not totally remove the possibility of failure. Therefore, a hybrid robot capable of both flapping flight and ground locomotion is an optimal design . This design principle is demonstrated by the author’s DASH robot (featured in this paper).
In theory, one mode should take over when the other fails. Therefore, various wing designs were tested in a static context to evaluate possible failure modes. One test involved understanding how the presence of flapping wings affects the stability of ground locomotion. Not only does this additional morphology make the robot heavier and not able to move as fast, but also results in a selective stiffening of the body. This lack of compliance seems to negatively impact the overall stability of gait. This was compensated for by adding simple polyester (e.g. compliant) feet to each leg.
To summarize some of their better experimental results, the authors compare two different modes of flight (flapping vs. gliding) for a range of wind speeds (see below). Based on the results of their experiments, the authors finish up with a discussion of the optimal mode for flying locomotion.
 Liao, J.C., Beal, D.N., Lauder, G.V., and Triantafyllou, M.S. (2003). The Karman gait: novel body kinematics of rainbow trout swimming in a votex street. Journal of Experimental Biology, 206, 1059-1073.
 Muller, U.K., van den Heuvel, B., Stemhuis, E.J., and Videler, J.J. (1997). Fish footprints: morphology and energetics of the wake behind a continuously swimming mullet (Chelonlabrosus risso). Jounral of Experimental Biology, 200, 2893-2906.
 Gutfreund, Y., Flash, T., Fiorito, G., and Hochner, B. (1998) Patterns of arm muscle activation involved in octopus reaching movements. Journal of Neuroscience, 18(15), 5976–5987.
 Pfeifer, R., Iida, F., and Bongard, J. (2005) New robotics: design principles for intelligent systems. Artificial Life, 11, 99–120.
 Holmes, P., Full, R., Koditschek, D., and Guckenheimer, J. (2006). The dynamics of legged locomotion: models, analyses, and challenges, SIAM Review, 48, 207-304.
 Ijspeert, A.J., Crespi, A., Ryczko, D., and Cabelguen, J.M. (2007). From swimming to walking with a salamander robot driven by a spinal cord model. Science, 315, 1416-1420.