Undulatory swimming animals exhibit diverse ranges of body shapes and motion patterns and are often considered as having superior locomotory performance. The extent to which morphological traits of swimming animals have evolved owing to primarily locomotion considerations is, however, not clear. To shed some light on that question, we present here the optimal shape and motion of undulatory swimming organisms obtained by optimizing locomotive performance measures within the framework of a combined hydrodynamical, structural and novel muscular model. We develop a muscular model for periodic muscle contraction which provides relevant kinematic and energetic quantities required to describe swimming. Using an evolutionary algorithm, we performed a multi-objective optimization for achieving maximum sustained swimming speed U and minimum cost of transport (COT)-two conflicting locomotive performance measures that have been conjectured as likely to increase fitness for survival. Starting from an initial population of random characteristics, our results show that, for a range of size scales, fishlike body shapes and motion indeed emerge when U and COT are optimized. Inherent boundary-layerdependent allometric scaling between body mass and kinematic and energetic quantities of the optimal populations is observed. The trade-off between U and COT affects the geometry, kinematics and energetics of swimming organisms. Our results are corroborated by empirical data from swimming animals over nine orders of magnitude in size, supporting the notion that optimizing U and COT could be the driving force of evolution in many species.

Swarm robotics has experienced a rapid expansion in recent years, primarily fueled by specialized multi-robot systems developed to achieve dedicated collective actions. These specialized platforms are, in general, designed with swarming considerations at the front and center. Key hardware and software elements required for swarming are often deeply embedded and integrated with the particular system. However, given the noticeable increase in the number of low-cost mobile robots readily available, practitioners and hobbyists may start considering to assemble full-fledged swarms by minimally retrofitting such mobile platforms with a swarm-enabling technology. Here, we report one possible embodiment of such a technology-an integrated combination of hardware and software-designed to enable the assembly and the study of swarming in a range of general-purpose robotic systems. This is achieved by combining a modular and transferable software toolbox with a hardware suite composed of a collection of low-cost and off-theshelf components. The developed technology can be ported to a relatively vast range of robotic platforms-such as land and surface vehicles-with minimal changes and high levels of scalability. This swarm-enabling technology has successfully been implemented on two distinct distributed multi-robot systems, a swarm of mobile marine buoys and a team of commercial terrestrial robots. We have tested the effectiveness of both of these distributed robotic systems in performing collective exploration and search scenarios, as well as other classical cooperative behaviors. Experimental results on different swarm behaviors are reported for the two platforms in uncontrolled environments and without any supporting infrastructure. The design of the associated software library allows for a seamless switch to other cooperative behaviors-e.g., leader-follower heading consensus and collision avoidance, and also offers the possibility to simulate newly designed collective behaviors prior to their implementation onto the platforms. This feature greatly facilitates behavior-based design, i.e., the design of new swarming behaviors, with the possibility to simulate them prior to physically test them.

The design, construction, and testing of a large distributed system of novel, small, low-cost, autonomous surface vehicles in the form of self-propelled buoys capable of operating in open waters is reported. We detail the successful testing of collective behaviors of systems with up to 50 buoys, achieving scalable deployment and dynamic monitoring in unstructured environments. This constitutes the largest distributed multi-robot system of its kind reported to date. We confirm the robustness of the system to the loss of multiple units for different collective behaviors such as flocking, navigation, and area coverage. For dynamic area monitoring, we introduce a new metric to quantify coverage effectiveness. Our system exhibits near optimal scalability for fixed target areas and a high degree of flexibility when the shape of the target changes with time. This system demonstrates the potential of distributed multi-robot systems for the pervasive and persistent monitoring of coastal and inland water environments.

We consider the hydrodynamics of wave energy converter (WEC) arrays consisting of periodically repeated single bodies or sub-arrays. Of special interest is the array gain due to wave interactions as a function of the spatial configuration of the array. For simplicity, we assume identical WECs oscillating in heave only, although the results should extend to general motions. We find that array gains can be as high as $O(10)$ compared to the same WECs operating in isolation. We show that prominent decreases in array gain are associated with Laue resonances, involving the incident and scattered wave modes, for which we obtain an explicit condition. We also show theoretically that Bragg resonances can result in large decreases in gain with as few as two rows of strong absorbers. For general WEC geometries, we develop a multiple-scattering method of wave–body interactions applicable to generally spaced periodic arrays. For arrays of truncated vertical cylinders, we perform numerical investigations confirming our theoretical predictions for Laue and Bragg resonances. For a special class of multiple-row rectangular WEC arrays, our numerical results show that motion-trapped Rayleigh–Bloch waves can exist and be excited by an incident wave, resulting in sharp, narrow-banded spikes in the array gain.

Swarms of autonomous surface vehicles equipped with environmental sensors and decentralized communications bring a new wave of attractive possibilities for the monitoring of dynamic features in oceans and other waterbodies. However, a key challenge in swarm robotics design is the efficient collective operation of heterogeneous systems. We present both theoretical analysis and field experiments on the responsiveness in dynamic area coverage of a collective of 22 autonomous buoys, where 4 units are upgraded to a new design that allows them to move 80% faster than the rest. This system is able to react on timescales of the minute to changes in areas on the order of a few thousand square meters. We have observed that this partial upgrade of the system significantly increases its average responsiveness, without necessarily improving the spatial uniformity of the deployment. These experiments show that the autonomous buoy designs and the cooperative control rule described in this work provide an efficient, flexible, and scalable solution for the pervasive and persistent monitoring of water environments.