Sticking the landing: Insect-inspired strategies for safely landing flapping-wing aerial microrobots

For flying insects, the transition from flight to surface locomotion requires effective touchdown maneuvers that allow stable landings on a variety of surfaces. Landing behaviors of insects are diverse, with some using more controlled flight approaches to landing, whereas others dampen collision impacts with parts of their bodies. The landing approaches of real insects inspired our current work, where we present a combined mechanical and control approach to achieving safe and accurate landings for flapping-wing microaerial vehicles. For the mechanical approach to landing, we took inspiration from the legs of the crane fly, designing lossy compliant legs that maximize energy dissipation during surface collisions. We explored three features in the compliant leg design: leg stance, number of joints, and joint placement. For the control approach to landing, the challenge lies in overcoming the aerodynamic ground effect near the surface. Leveraging the compliant leg design during impact, we designed the preimpact behavior, drawing inspiration from insect landing trajectories, to increase landing success. The proposed controlled landing sequence includes an initial acceleration from hovering, followed by deceleration toward the target, ending with a nonzero impact velocity, similar to what is observed in insects. Last, using an insect-scale flapping-wing aerial microrobot platform (Harvard RoboBee), we verified the controlled, safe, and accurate landing on natural terrain.

Embodied design for enhanced flipper-based locomotion in complex terrains

Robots are becoming increasingly essential for traversing complex environments such as disaster areas, extraterrestrial terrains, and marine environments. Yet, their potential is often limited by mobility and adaptability constraints. In nature, various animals have evolved finely tuned designs and anatomical features that enable efficient locomotion in diverse environments. Sea turtles, for instance, possess specialized flippers that facilitate both long-distance underwater travel and adept maneuvers across a range of coastal terrains. Building on the principles of embodied intelligence and drawing inspiration from sea turtle hatchings, this paper examines the critical interplay between a robot's physical form and its environmental interactions, focusing on how morphological traits and locomotive behaviors affect terrestrial navigation. We present a bioinspired robotic system and study the impacts of flipper/body morphology and gait patterns on its terrestrial mobility across diverse terrains ranging from sand to rocks. Evaluating key performance metrics such as speed and cost of transport, our experimental results highlight adaptive designs as crucial for multi-terrain robotic mobility to achieve not only speed and efficiency but also the versatility needed to tackle the varied and complex terrains encountered in real-world applications.

Form and function of anguilliform swimming

Anguilliform swimmers are long and narrow animals that propel themselves by undulating their bodies. Observations in nature and recent investigations suggest that anguilliform swimming is highly efficient. However, understanding the underlying reasons for the efficiency of this type of locomotion requires interdisciplinary studies spanning from biology to hydrodynamics. Regrettably, these different fields are rarely discussed together, which hinders our ability to understand the repeated evolution of this swimming mode in vertebrates. This review compiles the current knowledge of the anatomical features that drive anguilliform swimming, compares the resulting kinematics across a wide range of anguilliform swimmers, and describes the resulting hydrodynamic interactions using data from both in vivo experiments and computational studies.

Paleoinspired robotics as an experimental approach to the history of life

Paleontologists must confront the challenge of studying the forms and functions of extinct species for which data from preserved fossils are extremely limited, yielding only a fragmented picture of life in deep time. In response to this hurdle, we describe the nascent field of paleoinspired robotics, an innovative method that builds upon established techniques in bioinspired robotics, enabling the exploration of the biology of ancient organisms and their evolutionary trajectories. This Review presents ways in which robotic platforms can fill gaps in existing research using the exemplars of notable transitions in vertebrate locomotion. We examine recent case studies in experimental paleontology, highlighting substantial contributions made by engineering and robotics techniques, and further assess how the efficient application of robotic technologies in close collaboration with paleontologists and biologists can offer additional insights into the study of evolution that were previously unattainable.

An FPGA-Implemented Antinoise Fuzzy Recurrent Neural Network for Motion Planning of Redundant Robot Manipulators

When a robot completes end-effector tasks, internal error noises always exist. To resist internal error noises of robots, a novel fuzzy recurrent neural network (FRNN) is proposed, designed, and implemented on field-programmable gated array (FPGA). The implementation is pipeline-based, which guarantees the order of overall operations. The data processing is based on across-clock domain, which is beneficial for computing units' acceleration. Compared with traditional gradient-based neural networks (NNs) and zeroing neural networks (ZNNs), the proposed FRNN has faster convergence rate and higher correctness. Practical experiments on a 3 degree-of-freedom (DOs) planar robot manipulator show that the proposed fuzzy RNN coprocessor needs 496 lookup table random access memories (LUTRAMs), 205.5 block random access memories (BRAMs), 41384 lookup tables (LUTs), and 16743 flip-flops (FFs) of the Xilinx XCZU9EG chip.

Fly Me to the Micron: Microtechnologies for Drosophila Research

Multicellular model organisms, such as Drosophila melanogaster (fruit fly), are frequently used in a myriad of biological research studies due to their biological significance and global standardization. However, traditional tools used in these studies generally require manual handling, subjective phenotyping, and bulk treatment of the organisms, resulting in laborious experimental protocols with limited accuracy. Advancements in microtechnology over the course of the last two decades have allowed researchers to develop automated, high-throughput, and multifunctional experimental tools that enable novel experimental paradigms that would not be possible otherwise. We discuss recent advances in microtechnological systems developed for small model organisms using D. melanogaster as an example. We critically analyze the state of the field by comparing the systems produced for different applications. Additionally, we suggest design guidelines, operational tips, and new research directions based on the technical and knowledge gaps in the literature. This review aims to foster interdisciplinary work by helping engineers to familiarize themselves with model organisms while presenting the most recent advances in microengineering strategies to biologists.

Geometric phase predicts locomotion performance in undulating living systems across scales

Self-propelling organisms locomote via generation of patterns of self-deformation. Despite the diversity of body plans, internal actuation schemes and environments in limbless vertebrates and invertebrates, such organisms often use similar traveling waves of axial body bending for movement. Delineating how self-deformation parameters lead to locomotor performance (e.g. speed, energy, turning capabilities) remains challenging. We show that a geometric framework, replacing laborious calculation with a diagrammatic scheme, is well-suited to discovery and comparison of effective patterns of wave dynamics in diverse living systems. We focus on a regime of undulatory locomotion, that of highly damped environments, which is applicable not only to small organisms in viscous fluids, but also larger animals in frictional fluids (sand) and on frictional ground. We find that the traveling wave dynamics used by mm-scale nematode worms and cm-scale desert dwelling snakes and lizards can be described by time series of weights associated with two principal modes. The approximately circular closed path trajectories of mode weights in a self-deformation space enclose near-maximal surface integral (geometric phase) for organisms spanning two decades in body length. We hypothesize that such trajectories are targets of control (which we refer to as "serpenoid templates"). Further, the geometric approach reveals how seemingly complex behaviors such as turning in worms and sidewinding snakes can be described as modulations of templates. Thus, the use of differential geometry in the locomotion of living systems generates a common description of locomotion across taxa and provides hypotheses for neuromechanical control schemes at lower levels of organization.

Why animals can outrun robots

Animals are much better at running than robots. The difference in performance arises in the important dimensions of agility, range, and robustness. To understand the underlying causes for this performance gap, we compare natural and artificial technologies in the five subsystems critical for running: power, frame, actuation, sensing, and control. With few exceptions, engineering technologies meet or exceed the performance of their biological counterparts. We conclude that biology's advantage over engineering arises from better integration of subsystems, and we identify four fundamental obstacles that roboticists must overcome. Toward this goal, we highlight promising research directions that have outsized potential to help future running robots achieve animal-level performance.

Integrated Modular Neural Control for Versatile Locomotion and Object Transportation of a Dung Beetle-Like Robot

Dung beetles can effectively transport dung pallets of various sizes in any direction across uneven terrain. While this impressive ability can inspire new locomotion and object transportation solutions in multilegged (insect-like) robots, to date, most existing robots use their legs primarily to perform locomotion. Only a few robots can use their legs to achieve both locomotion and object transportation, although they are limited to specific object types/sizes (10%-65% of leg length) on flat terrain. Accordingly, we proposed a novel integrated neural control approach that, like dung beetles, pushes state-of-the-art insect-like robots beyond their current limits toward versatile locomotion and object transportation with different object types/sizes and terrains (flat and uneven). The control method is synthesized based on modular neural mechanisms, integrating central pattern generator (CPG)-based control, adaptive local leg control, descending modulation control, and object manipulation control. We also introduced an object transportation strategy combining walking and periodic hind leg lifting for soft object transportation. We validated our method on a dung beetle-like robot. Our results show that the robot can perform versatile locomotion and use its legs to transport hard and soft objects of various sizes (60%-70% of leg length) and weights (approximately 3%-115% of robot weight) on flat and uneven terrains. The study also suggests possible neural control mechanisms underlying the dung beetle Scarabaeus galenus' versatile locomotion and small dung pallet transportation.

The Role of Locomotory Ancestry on Secondarily Aquatic Transitions

Land-to-sea evolutionary transitions are great transformations where terrestrial amniote clades returned to aquatic environments. These secondarily aquatic amniote clades include charismatic marine mammal and marine reptile groups, as well as countless semi-aquatic forms that modified their terrestrial locomotor anatomy to varying degrees to be suited for swimming via axial and/or appendicular propulsion. The terrestrial ancestors of secondarily aquatic groups would have started off swimming strikingly differently from one another given their evolutionary histories, as inferred by the way modern terrestrial amniotes swim. With such stark locomotor functional differences between reptiles and mammals, we ask if this impacted these transitions. Axial propulsion appears favored by aquatic descendants of terrestrially sprawling quadrupedal reptiles, with exceptions. Appendicular propulsion is more prevalent across the aquatic descendants of ancestrally parasagittal-postured mammals, particularly early transitioning forms. Ancestral terrestrial anatomical differences that precede secondarily aquatic invasions between mammals and reptiles, as well as the distribution of axial and appendicular swimming in secondarily aquatic clades, may indicate that ancestral terrestrial locomotor anatomy played a role, potentially in both constraint and facilitation, in certain aquatic locomotion styles. This perspective of the land-to-sea transition can lead to new avenues of functional, biomechanical, and developmental study of secondarily aquatic transitions.

Mechanical intelligence simplifies control in terrestrial limbless locomotion

Limbless locomotors, from microscopic worms to macroscopic snakes, traverse complex, heterogeneous natural environments typically using undulatory body wave propagation. Theoretical and robophysical models typically emphasize body kinematics and active neural/electronic control. However, we contend that because such approaches often neglect the role of passive, mechanically controlled processes (those involving "mechanical intelligence"), they fail to reproduce the performance of even the simplest organisms. To uncover principles of how mechanical intelligence aids limbless locomotion in heterogeneous terradynamic regimes, here we conduct a comparative study of locomotion in a model of heterogeneous terrain (lattices of rigid posts). We used a model biological system, the highly studied nematode worm Caenorhabditis elegans, and a robophysical device whose bilateral actuator morphology models that of limbless organisms across scales. The robot's kinematics quantitatively reproduced the performance of the nematodes with purely open-loop control; mechanical intelligence simplified control of obstacle navigation and exploitation by reducing the need for active sensing and feedback. An active behavior observed in C. elegans, undulatory wave reversal upon head collisions, robustified locomotion via exploitation of the systems' mechanical intelligence. Our study provides insights into how neurally simple limbless organisms like nematodes can leverage mechanical intelligence via appropriately tuned bilateral actuation to locomote in complex environments. These principles likely apply to neurally more sophisticated organisms and also provide a design and control paradigm for limbless robots for applications like search and rescue and planetary exploration.

Animal robots in the African wilderness: Lessons learned and outlook for field robotics

In early 2016, we had the opportunity to test a pair of sprawling posture robots, one designed to mimic a crocodile and another designed to mimic a monitor lizard, along the banks of the Nile River in Uganda, Africa. These robots were developed uniquely for a documentary by the BBC called Spy in the Wild and fell at the intersection of our interests in developing robots to study animals and robots for disaster response and other missions in challenging environments. The documentary required that these robots not only walk and swim in the same harsh, natural environments as the animals that they were modeled on and film up close but also move and even look exactly like the real animals from an aesthetic perspective. This pushed us to take a fundamentally different approach to the design and building of biorobots compared with our typical laboratory-residing robots, in addition to collaborating with sculpting artists to enhance our robots' aesthetics. The robots needed to be designed on the basis of a systematic study of data on the model specimens, be fabricated rapidly, and be reliable and robust enough to handle what the wild would throw at them. Here, we share the research efforts of this collaboration, the design specifications of the robots' hardware and software, the lessons learned from testing these robots in the field first hand, and how the eye-opening experience shaped our subsequent work on disaster response robotics and biorobotics for challenging amphibious scenarios.

Translating Virtual Prey-Predator Interaction to Real-World Robotic Environments: Enabling Multimodal Sensing and Evolutionary Dynamics

Prey-predator interactions play a pivotal role in elucidating the evolution and adaptation of various organism's traits. Numerous approaches have been employed to study the dynamics of prey-predator interaction systems, with agent-based methodologies gaining popularity. However, existing agent-based models are limited in their ability to handle multi-modal interactions, which are believed to be crucial for understanding living organisms. Conversely, prevailing prey-predator integration studies often rely on mathematical models and computer simulations, neglecting real-world constraints and noise. These elusive attributes, challenging to model, can lead to emergent behaviors and embodied intelligence. To bridge these gaps, our study designs and implements a prey-predator interaction scenario that incorporates visual and olfactory sensory cues not only in computer simulations but also in a real multi-robot system. Observed emergent spatial-temporal dynamics demonstrate successful transitioning of investigating prey-predator interactions from virtual simulations to the tangible world. It highlights the potential of multi-robotics approaches for studying prey-predator interactions and lays the groundwork for future investigations involving multi-modal sensory processing while considering real-world constraints.

Ions-Silica Percolated Ionic Dielectric Elastomer Actuator for Soft Robots

Soft robotics systems are currently under development using ionic electroactive polymers (i-EAP) as soft actuators for the human-machine interface. However, this endeavor has been impeded by the dilemma of reconciling the competing demands of force and strain in i-EAP actuators. Here, the authors present a novel design called "ions-silica percolated ionic dielectric elastomer (i-SPIDER)", which exhibits ionic liquid-confined silica microstructures that effectively resolve the chronic issue of conventional i-EAP actuators. The i-SPIDER actuator demonstrates remarkable electromechanical conversion capacity at low voltage, thanks to improved ion accumulation facilitated by interpreting electrode polarization at the electrolyte-electrode interface. This approach concurrently enhances both strain (by approximately 1.52%) and force (by roughly 1.06 mN) even at low Young's modulus (merely 5.9 MPa). Additionally, by demonstrating arachnid-inspired soft robots endowed with user-desired tasks through control of various form factors, the development of soft robots using the i-SPIDER that can concomitantly enhance strain and force holds promise as a compelling avenue for ushering in the next generation of miniaturized, low-powered soft robotics.

Bioinspired robots can foster nature conservation

We live in a time of unprecedented scientific and human progress while being increasingly aware of its negative impacts on our planet's health. Aerial, terrestrial, and aquatic ecosystems have significantly declined putting us on course to a sixth mass extinction event. Nonetheless, the advances made in science, engineering, and technology have given us the opportunity to reverse some of our ecosystem damage and preserve them through conservation efforts around the world. However, current conservation efforts are primarily human led with assistance from conventional robotic systems which limit their scope and effectiveness, along with negatively impacting the surroundings. In this perspective, we present the field of bioinspired robotics to develop versatile agents for future conservation efforts that can operate in the natural environment while minimizing the disturbance/impact to its inhabitants and the environment's natural state. We provide an operational and environmental framework that should be considered while developing bioinspired robots for conservation. These considerations go beyond addressing the challenges of human-led conservation efforts and leverage the advancements in the field of materials, intelligence, and energy harvesting, to make bioinspired robots move and sense like animals. In doing so, it makes bioinspired robots an attractive, non-invasive, sustainable, and effective conservation tool for exploration, data collection, intervention, and maintenance tasks. Finally, we discuss the development of bioinspired robots in the context of collaboration, practicality, and applicability that would ensure their further development and widespread use to protect and preserve our natural world.

Genes, Morphology, Performance, and Fitness: Quantifying Organismal Performance to Understand Adaptive Evolution

To understand the complexities of morphological evolution, we must understand the relationships between genes, morphology, performance, and fitness in complex traits. Genomicists have made tremendous progress in finding the genetic basis of many phenotypes, including a myriad of morphological characters. Similarly, field biologists have greatly advanced our understanding of the relationship between performance and fitness in natural populations. However, the connection from morphology to performance has primarily been studied at the interspecific level, meaning that in most cases we lack a mechanistic understanding of how evolutionarily relevant variation among individuals affects organismal performance. Therefore, functional morphologists need methods that will allow for the analysis of fine-grained intraspecific variation in order to close the path from genes to fitness. We suggest three methodological areas that we believe are well suited for this research program and provide examples of how each can be applied within fish model systems to build our understanding of microevolutionary processes. Specifically, we believe that structural equation modeling, biological robotics, and simultaneous multi-modal functional data acquisition will open up fruitful collaborations among biomechanists, evolutionary biologists, and field biologists. It is only through the combined efforts of all three fields that we will understand the connection between evolution (acting at the level of genes) and natural selection (acting on fitness).

Identification of the trade-off between speed and efficiency in undulatory swimming using a bio-inspired robot

Anguilliform swimmers, like eels or lampreys, are highly efficient swimmers. Key to understanding their performances is the relationship between the body's kinematics and resulting swimming speed and efficiency. But, we cannot prescribe kinematics to living fish, and it is challenging to measure their power consumption. Here, we characterise the swimming speed and cost of transport of a free-swimming undulatory bio-inspired robot as we vary its kinematic parameters, including joint amplitude, body wavelength, and frequency. We identify a trade-off between speed and efficiency. Speed, in terms of stride length, increases for increasing maximum tail angle, described by the newly proposed specific tail amplitude and reaches a maximum value around the specific tail amplitude of unity. Efficiency, in terms of the cost of transport, is affected by the whole-body motion. Cost of transport decreases for increasing travelling wave-like kinematics, and lower specific tail amplitudes. Our results suggest that live eels tend to choose efficiency over speed and provide insights into the key characteristics affecting undulatory swimming performance.

Mechanosensory Control of Locomotion in Animals and Robots: Moving Forward

While animals swim, crawl, walk, and fly with apparent ease, building robots capable of robust locomotion remains a significant challenge. In this review, we draw attention to mechanosensation-the sensing of mechanical forces generated within and outside the body-as a key sense that enables robust locomotion in animals. We discuss differences between mechanosensation in animals and current robots with respect to (1) the encoding properties and distribution of mechanosensors and (2) the integration and regulation of mechanosensory feedback. We argue that robotics would benefit greatly from a detailed understanding of these aspects in animals. To that end, we highlight promising experimental and engineering approaches to study mechanosensation, emphasizing the mutual benefits for biologists and engineers that emerge from moving forward together.

Robot Programming from Fish Demonstrations

Fish are capable of learning complex relations found in their surroundings, and harnessing their knowledge may help to improve the autonomy and adaptability of robots. Here, we propose a novel learning from demonstration framework to generate fish-inspired robot control programs with as little human intervention as possible. The framework consists of six core modules: (1) task demonstration, (2) fish tracking, (3) analysis of fish trajectories, (4) acquisition of robot training data, (5) generating a perception-action controller, and (6) performance evaluation. We first describe these modules and highlight the key challenges pertaining to each one. We then present an artificial neural network for automatic fish tracking. The network detected fish successfully in 85% of the frames, and in these frames, its average pose estimation error was less than 0.04 body lengths. We finally demonstrate how the framework works through a case study focusing on a cue-based navigation task. Two low-level perception-action controllers were generated through the framework. Their performance was measured using two-dimensional particle simulations and compared against two benchmark controllers, which were programmed manually by a researcher. The fish-inspired controllers had excellent performance when the robot was started from the initial conditions used in fish demonstrations (>96% success rate), outperforming the benchmark controllers by at least 3%. One of them also had an excellent generalisation performance when the robot was started from random initial conditions covering a wider range of starting positions and heading angles (>98% success rate), again outperforming the benchmark controllers by 12%. The positive results highlight the utility of the framework as a research tool to form biological hypotheses on how fish navigate in complex environments and design better robot controllers on the basis of biological findings.

Maneuvering on non-Newtonian fluidic terrain: a survey of animal and bio-inspired robot locomotion techniques on soft yielding grounds

Frictionally yielding media are a particular type of non-Newtonian fluids that significantly deform under stress and do not recover their original shape. For example, mud, snow, soil, leaf litters, or sand are such substrates because they flow when stress is applied but do not bounce back when released. Some robots have been designed to move on those substrates. However, compared to moving on solid ground, significantly fewer prototypes have been developed and only a few prototypes have been demonstrated outside of the research laboratory. This paper surveys the existing biology and robotics literature to analyze principles of physics facilitating motion on yielding substrates. We categorize animal and robot locomotion based on the mechanical principles and then further on the nature of the contact: discrete contact, continuous contact above the material, or through the medium. Then, we extract different hardware solutions and motion strategies enabling different robots and animals to progress. The result reveals which design principles are more widely used and which may represent research gaps for robotics. We also discuss that higher level of abstraction helps transferring the solutions to the robotics domain also when the robot is not explicitly meant to be bio-inspired. The contribution of this paper is a review of the biology and robotics literature for identifying locomotion principles that can be applied for future robot design in yielding environments, as well as a catalog of existing solutions either in nature or man-made, to enable locomotion on yielding grounds.

The elephant in the room: The biomimetic principle in bio-robotics and embodied AI

In recent years, bio-inspired robots have shaped numerous domains of technical and scientific production. Bio-inspired robots can now be found in all areas of industry, medicine, architecture, and even culture. Despite the wealth of historiographic and philosophical studies published on this topic, a philosophical investigation of the mimetic principle used in bio-robotics is still missing. In this paper, I will ask a simple question: what is the role of biomimetic and bio-inspired processes in the different practices of bio-robotics? In the following pages, I will first make some conceptual order. I discuss the differences between several bio-inspired disciplines to clearly identify the biomimetic principle. Second, I introduce the discussion on the necessity of imitating nature in early twentieth-century bio-robotics. Third, I state the broader philosophical issue at stake in the debate on the biomimetic principle: the model-world relation, as discussed in the philosophical literature on models and idealization. In section 4, I address several emblematic case studies in which the imitation of nature, variously declined, is fundamental for producing knowledge, thus providing cursory taxonomy of the biomimetic principle. In the conclusion, I will come back to the elephant in the room and suggest how to tackle it further in a fruitful manner. As a broader result, my proposed taxonomy might be used by historians of science and technology as a starting point for historicizing the different practices of current bio-robotics as well as by philosophers to further problematize the various philosophical frameworks that have been accepted and developed in bio-robotics.

No Need for Landmarks: An Embodied Neural Controller for Robust Insect-Like Navigation Behaviors

Bayesian filters have been considered to help refine and develop theoretical views on spatial cell functions for self-localization. However, extending a Bayesian filter to reproduce insect-like navigation behaviors (e.g., home searching) remains an open and challenging problem. To address this problem, we propose an embodied neural controller for self-localization, foraging, backward homing (BH), and home searching of an advanced mobility sensor (AMOS)-driven insect-like robot. The controller, comprising a navigation module for the Bayesian self-localization and goal-directed control of AMOS and a locomotion module for coordinating the 18 joints of AMOS, leads to its robust insect-like navigation behaviors. As a result, the proposed controller enables AMOS to perform robust foraging, BH, and home searching against various levels of sensory noise, compared to conventional controllers. Its implementation relies only on self-localization and heading perception, rather than global positioning and landmark guidance. Interestingly, the proposed controller makes AMOS achieve spiral searching patterns comparable to those performed by real insects. We also demonstrated the performance of the controller for real-time indoor and outdoor navigation in a real insect-like robot without any landmark and cognitive map.

Is biorobotics science? Some theoretical reflections

In this paper, we ask one fairly simple question: to what extent can biorobotics be sensibly qualified as science? The answer clearly depends on what 'science' means and whether what is actually done in biorobotics corresponds to this meaning. To respond to this question, we will deploy the distinction between science and so-called technoscience, and isolate different kinds of objects of inquiry in biorobotics research. Capitalising on the distinction between 'proximal' and 'distal' biorobotic hypotheses, we will argue that technoscientific biorobotic studies address proximal hypotheses, whilst scientific biorobotic studies address distal hypotheses. As a result, we argue that bioroboticians can be both considered as scientists and technoscientists and that this is one of the main payoffs of biorobotics. Indeed, technoscientists play an extremely important role in 21st-century culture and in the current critical production of knowledge. Today's world is increasingly technological, or rather, it is a bio-hybrid system in which the biological and the technological are mixed. Therefore, studying the behaviour of robotic systems and the phenomena of animal-robot interaction means analysing, understanding, and shaping our world. Indeed, in the conclusion of the paper, we broadly reflect on the philosophical and disciplinary payoff of seeing biorobotics as a science and/or technoscience for the increasingly bio-hybrid and technical world of the 21st century.

Biohybrid robots: recent progress, challenges, and perspectives

The past ten years have seen the rapid expansion of the field of biohybrid robotics. By combining engineered, synthetic components with living biological materials, new robotics solutions have been developed that harness the adaptability of living muscles, the sensitivity of living sensory cells, and even the computational abilities of living neurons. Biohybrid robotics has taken the popular and scientific media by storm with advances in the field, moving biohybrid robotics out of science fiction and into real science and engineering. So how did we get here, and where should the field of biohybrid robotics go next? In this perspective, we first provide the historical context of crucial subareas of biohybrid robotics by reviewing the past 10+ years of advances in microorganism-bots and sperm-bots, cyborgs, and tissue-based robots. We then present critical challenges facing the field and provide our perspectives on the vital future steps toward creating autonomous living machines.

Bioinspired Design in Research: Evolution as Beta-Testing

Modern fishes represent over 400 million years of evolutionary processes that, in many cases, resulted in selection for phenotypes with particular performance advantages. While this certainly occurred without a trajectory for optimization, it cannot be denied that some morphologies allow organisms to be more effective than others at tasks like evading predation, securing food, and ultimately passing on their genes. In this way, evolution generates a series of iterative prototypes with varying but measurable success in accomplishing objectives. Therefore, careful analysis of fundamental properties underlying biological phenomena allow us to fast-track development of bioinspired technologies aiming to accomplish similar objectives. At the same time, bioinspired designs can be a way to explore evolutionary processes, by better understanding the performance space within which a given morphology operates. Through strong interdisciplinary collaborations, we can develop novel bioinspired technologies that not only excel as robotic devices but that teach us something about biology and the rules of life in the process.

Beyond Bio-Inspired Robotics: How Multi-Robot Systems Can Support Research on Collective Animal Behavior

In the study of collective animal behavior, researchers usually rely on gathering empirical data from animals in the wild. While the data gathered can be highly accurate, researchers have limited control over both the test environment and the agents under study. Further aggravating the data gathering problem is the fact that empirical studies of animal groups typically involve a large number of conspecifics. In these groups, collective dynamics may occur over long periods of time interspersed with excessively rapid events such as collective evasive maneuvers following a predator’s attack. All these factors stress the steep challenges faced by biologists seeking to uncover the fundamental mechanisms and functions of social organization in a given taxon. Here, we argue that beyond commonly used simulations, experiments with multi-robot systems offer a powerful toolkit to deepen our understanding of various forms of swarming and other social animal organizations. Indeed, the advances in multi-robot systems and swarm robotics over the past decade pave the way for the development of a new hybrid form of scientific investigation of social organization in biology. We believe that by fostering such interdisciplinary research, a feedback loop can be created where agent behaviors designed and tested in robotico can assist in identifying hypotheses worth being validated through the observation of animal collectives in nature. In turn, these observations can be used as a novel source of inspiration for even more innovative behaviors in engineered systems, thereby perpetuating the feedback loop.

Going Beyond the "Synthetic Method": New Paradigms Cross-Fertilizing Robotics and Cognitive Neuroscience

In so-called ethorobotics and robot-supported social cognitive neurosciences, robots are used as scientific tools to study animal behavior and cognition. Building on previous epistemological analyses of biorobotics, in this article it is argued that these two research fields, widely differing from one another in the kinds of robots involved and in the research questions addressed, share a common methodology, which significantly differs from the "synthetic method" that, until recently, dominated biorobotics. The methodological novelty of this strategy, the research opportunities that it opens, and the theoretical and technological challenges that it gives rise to, will be discussed with reference to the peculiarities of the two research fields. Some broad methodological issues related to the generalization of results concerning robot-animal interaction to theoretical conclusions on animal-animal interaction will be identified and discussed.

A fish-like soft-robotic model generates a diversity of swimming patterns

Fish display a versatile array of swimming patterns, and frequently demonstrate the ability to switch between these patterns altering kinematics as necessary. Many hard and soft robotic systems have sought to understand a variety of aspects pertaining to undulatory swimming, but most have been built to focus solely on a subset of those swimming patterns. We have expanded upon a previous soft robotic model, the pneufish, so that it can now simulate a variety of swimming patterns, much like a real fish. We explore the performance space available for this longer soft robotic model, which we call the quad-pneufish, with particular attention to the effects on lateral forces and z-torques produced during locomotion. We show that the quad-pneufish is capable of achieving a variety of midline patterns - including more realistic, fish-like patterns - and introducing a slight amount of co-activation between the left and right sides maintains forward thrust while decreasing lateral forces, indicating an increase in swimming efficiency. Robotic systems that are capable of producing an array of swimming movement patterns hold promise as experimental platforms for studying the diversity of fish locomotor patterns.

Flexible Shoulder in Quadruped Animals and Robots Guiding Science of Soft Robotics

Cursorial quadrupeds have different connections to the trunk for forelimbs and hindlimbs: a flexible connection through the muscles to the forelimb, and a secure connection through the hip joint to the hindlimb. Although anatomical and biological studies have described the structure and behavior of cursorial quadrupeds by focusing on flexible shoulders, the functionality of the flexible shoulder remains unclear. In this study, we first survey the anatomical and biological studies. Second, we introduce our robotics studies, which focus on flexible connections for proximal limb joints. Further, we discuss future directions for extracting a design principle based on complex animal body structures, and we suggest the potential for interdisciplinary research between anatomy and soft robotics.

Biomimetic Soft Wings for Soft Robot Science

Flight and swimming in nature can inspire the design of highly adaptive robots capable of working in complex environments. In this letter, we reviewed our work on robotic propulsion in the air and water, with a specific focus on the crucial functions of elastic components involved in the driving mechanism and flapping wings. Elasticity in the driving mechanism inspired by birds and insects can enhance both the aerodynamic efficiency of flapping wings and robustness against disturbances with appropriate design. A flapping wing surface with a stiffness distribution inspired by hummingbirds was fabricated by combining tapered spars and ribs with a thin film. The biomimetic flexible wing could generate more lift than the nontapered wing with a similar amount of power consumption. Underwater flapping-wing propulsion inspired by penguins was investigated by combining the 3-degree-of-freedom (DoF) flapping mechanism and hydrodynamic calculation, which indicates that wing bending increases the propulsion efficiency. This work demonstrates the importance of passive deformation of both wing surfaces and driving mechanisms for improving the fluid dynamic efficiency and robustness in flight and swimming, as well as providing biological insight from an engineering perspective.

Robotics as a Comparative Method in Ecology and Evolutionary Biology

Comparative biologists have typically used one or more of the following methods to assist in evaluating the proposed functional and performance significance of individual traits: comparative phylogenetic analysis, direct interspecific comparison among species, genetic modification, experimental alteration of morphology (for example by surgically modifying traits), and ecological manipulation where individual organisms are transplanted to a different environment. But comparing organisms as the endpoints of an evolutionary process involves the ceteris paribus assumption: that all traits other than the one(s) of interest are held constant. In a properly controlled experimental study, only the variable of interest changes among the groups being compared. The theme of this paper is that the use of robotic or mechanical models offers an additional tool in comparative biology that helps to minimize the effect of uncontrolled variables by allowing direct manipulation of the trait of interest against a constant background. The structure and movement pattern of mechanical devices can be altered in ways not possible in studies of living animals, facilitating testing hypotheses of the functional and performance significant of individual traits. Robotic models of organismal design are particularly useful in three arenas: (1) controlling variation to allow modification only of the trait of interest, (2) the direct measurement of energetic costs of individual traits, and (3) quantification of the performance landscape. Obtaining data in these three areas is extremely difficult through the study of living organisms alone, and the use of robotic models can reveal unexpected effects. Controlling for all variables except for the length of a swimming flexible object reveals substantial non-linear effects that vary with stiffness. Quantification of the swimming performance surface reveals that there are two peaks with comparable efficiency, greatly complicating the inference of performance from morphology alone. Organisms and their ecological interactions are complex, and dissecting this complexity to understand the effects of individual traits is a grand challenge in ecology and evolutionary biology. Robotics has great promise as a "comparative method," allowing better-controlled comparative studies to analyze the many interacting elements that make up complex behaviors, ecological interactions, and evolutionary histories.

Adaptive Centipede Walking via Synergetic Coupling Between Decentralized Control and Flexible Body Dynamics

Multi-legged animals such as myriapods can locomote on unstructured rough terrain using their flexible bodies and legs. This highly adaptive locomotion emerges through the dynamic interactions between an animal’s nervous system, its flexible body, and the environment. Previous studies have primarily focused on either adaptive leg control or the passive compliance of the body parts and have shown how each enhanced adaptability to complex terrains in multi-legged locomotion. However, the essential mechanism considering both the adaptive locomotor circuits and bodily flexibility remains unclear. In this study, we focused on centipedes and aimed to understand the well-balanced coupling between the two abovementioned mechanisms for rough terrain walking by building a neuromechanical model based on behavioral findings. In the behavioral experiment, we observed a centipede walking when part of the terrain was temporarily removed and thereafter restored. We found that the ground contact sense of each leg was essential for generating rhythmic leg motions and also for establishing adaptive footfall patterns between adjacent legs. Based on this finding, we proposed decentralized control mechanisms using ground contact sense and implemented them into a physical centipede model with flexible bodies and legs. In the simulations, our model self-organized the typical gait on flat terrain and adaptive walking during gap crossing, which were similar to centipedes. Furthermore, we demonstrated that the locomotor performance deteriorated on rough terrain when adaptive leg control was removed or when the body was rigid, which indicates that both the adaptive leg control and the flexible body are essential for adaptive locomotion. Thus, our model is expected to capture the possible essential mechanisms underlying adaptive centipede walking and pave the way for designing multi-legged robots with high adaptability to irregular terrain.

Switch controllers of an n-link revolute manipulator with a prismatic end-effector for landmark navigation

Robotic arms play an indispensable role in multiple sectors such as manufacturing, transportation and healthcare to improve human livelihoods and make possible their endeavors and innovations, which further enhance the quality of our lives. This paper considers such a robotic arm comprised of n revolute links and a prismatic end-effector, where the articulated arm is anchored in a restricted workspace. A new set of stabilizing switched velocity-based continuous controllers was derived using the Lyapunov-based Control Scheme (LbCS) from the category of classical approaches where switching of these nonlinear controllers is invoked by a new rule. The switched controllers enable the end-effector of the robotic arm to navigate autonomously via a series of landmarks, known as hierarchal landmarks, and finally converge to its equilibrium state. The interaction of the inherent attributes of LbCS that are the safeness, shortness and smoothness of paths for motion planning bring about cost and time efficiency of the controllers. The stability of the switched system was proven using Branicky's stability criteria for switched systems based on multiple Lyapunov functions and was numerically validated using the RK4 method (Runge-Kutta method). Finally, computer simulation results are presented to show the effectiveness of the continuous time-invariant velocity-based controllers.

Ecology of fear in highly invasive fish revealed by robots

Invasive species threaten biodiversity and ecosystem functioning. We develop an innovative experimental approach, integrating biologically inspired robotics, time-series analysis, and computer vision, to build a detailed profile of the effects of non-lethal stress on the ecology and evolution of mosquitofish (Gambusia holbrooki)—a global pest. We reveal that brief exposures to a robotic predator alter mosquitofish behavior, increasing fear and stress responses, and mitigate the impact of mosquitofish on native tadpoles (Litoria moorei) in a cause-and-effect fashion. Effects of predation risk from the robot carry over to routine activity and feeding rate of mosquitofish weeks after exposure, resulting in weight loss, variation in body shape, and reduction in the fertility of both sexes—impairing survival, reproduction, and ecological success. We capitalize on evolved responses of mosquitofish to reduce predation risk—neglected in biological control practices—and provide scientific foundations for widespread use of state-of-the-art robotics in ecology and evolution research.

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Can robotic predators reveal the vulnerabilities of invasive and pest species?

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Our predator selectively targets invasive fish to protect native amphibians

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Stress from the robot compromises behavior, health, and reproduction of invaders

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We open new frontiers for robotics in ecology, evolution, and biocontrol research

Tunable stiffness in fish robotics: mechanisms and advantages

One of the emerging themes of fish-inspired robotics is flexibility. Adding flexibility to the body, joints, or fins of fish-inspired robots can significantly improve thrust and/or efficiency during locomotion. However, the optimal stiffness depends on variables such as swimming speed, so there is no one 'best' stiffness that maximizes efficiency in all conditions. Fish are thought to solve this problem by using muscular activity to tune their body and fin stiffness in real-time. Inspired by fish, some recent robots sport polymer actuators, adjustable leaf springs, or artificial tendons that tune stiffness mechanically. Models and water channel tests are providing a theoretical framework for stiffness-tuning strategies that devices can implement. The strategies can be thought of as analogous to car transmissions, which allow users to improve efficiency by tuning gear ratio with driving speed. We provide an overview of the latest discoveries about (1) the propulsive benefits of flexibility, particularlytunableflexibility, and (2) the mechanisms and strategies that fish and fish-inspired robots use to tune stiffness while swimming.

A bio-inspired robotic climbing robot to understand kinematic and morphological determinants for an optimal climbing gait

Robotic systems for complex tasks, such as search and rescue or exploration, are limited for wheeled designs, thus the study of legged locomotion for robotic applications has become increasingly important. To successfully navigate in regions with rough terrain, a robot must not only be able to negotiate obstacles, but also climb steep inclines. Following the principles of biomimetics, we developed a modular bio-inspired climbing robot, named X4, which mimics the lizard's bauplan including an actuated spine, shoulders, and feet which interlock with the surface via claws. We included the ability to modify gait and hardware parameters and simultaneously collect data with the robot's sensors on climbed distance, slip occurrence and efficiency. We first explored the speed-stability trade-off and its interaction with limb swing phase dynamics, finding a sigmoidal pattern of limb movement resulted in the greatest distance travelled. By modifying foot orientation, we found two optima for both speed and stability, suggesting multiple stable configurations. We varied spine and limb range of motion, again showing two possible optimum configurations, and finally varied the centre of pro- and retraction on climbing performance, showing an advantage for protracted limbs during the stride. We then stacked optimal regions of performance and show that combining optimal dynamic patterns with either foot angles or ROM configurations have the greatest performance, but further optima stacking resulted in a decrease in performance, suggesting complex interactions between kinematic parameters. The search of optimal parameter configurations might not only be beneficial to improve robotic in-field operations but may also further the study of the locomotive evolution of climbing of animals, like lizards or insects.

The creation of phenomena in interactive biorobotics

In so-called interactive biorobotics, robotic models of living systems interact with animals in controlled experimental settings. By observing how the focal animal reacts to the stimuli delivered by the robot, one tests hypotheses concerning the determinants of animal behaviour in social contexts. Building on previous methodological reconstructions of interactive biorobotics, this article reflects on the claim, made by several authors in the field, that this strategy may enable one to explain social phenomena in animals. The answer offered here will be negative: interactive biorobotics does not contribute to the explanation of social phenomena. However, it may greatly contribute to the study of animal behaviour by creating social phenomena in the sense discussed by Ian Hacking, i.e. by precisely defining new phenomena to be explained. It will be also suggested that interactive biorobotics can be combined with more classical robot-based approaches to the study of living systems, leading to a so-called simulation-interactive strategy for the mechanistic explanation of social behaviour in animals.

Insect inspired vision-based velocity estimation through spatial pooling of optic flow during linear motion

Insects rely on the perception of image motion, or optic flow, to estimate their velocity relative to nearby objects. This information provides important sensory input for avoiding obstacles. However, certain behaviors, such as estimating the absolute distance to a landing target, accurately measuring absolute distance traveled, and estimating the ambient wind speed require decoupling optic flow into its component parts: absolute ground velocity and distance to nearby objects. Behavioral experiments suggest that insects perform these calculations, but their mechanism for doing so remains unknown. Here we present a novel algorithm that combines the geometry of dynamic forward motion with known features of insect visual processing to provide a hypothesis for how insects mightdirectlyestimate absolute ground velocity from a combination of optic flow and acceleration information. Our robotics-inspired-biology approach reveals three critical requirements. First, absolute ground velocity can only be directly estimated from optic flow during times of active acceleration and deceleration. Second, spatial pooling of optic flow across a receptive field helps to alleviate the effects of noise and/or low resolution visual systems. Third, averaging velocity estimates from multiple receptive fields further helps to reject noise. Our algorithm provides a hypothesis for how insects might estimate absolute velocity from vision during active maneuvers, and also provides a theoretical framework for designing fast analog circuitry for efficient state estimation that can be applied to insect-sized robots.

Tails stabilize landing of gliding geckos crashing head-first into tree trunks

Animals use diverse solutions to land on vertical surfaces. Here we show the unique landing of the gliding gecko, Hemidactylus platyurus. Our high-speed video footage in the Southeast Asian rainforest capturing the first recorded, subcritical, short-range glides revealed that geckos did not markedly decrease velocity prior to impact. Unlike specialized gliders, geckos crashed head-first with the tree trunk at 6.0 ± 0.9 m/s (~140 body lengths per second) followed by an enormous pitchback of their head and torso 103 ± 34° away from the tree trunk anchored by only their hind limbs and tail. A dynamic mathematical model pointed to the utility of tails for the fall arresting response (FAR) upon landing. We tested predictions by measuring foot forces during landing of a soft, robotic physical model with an active tail reflex triggered by forefoot contact. As in wild animals, greater landing success was found for tailed robots. Experiments showed that longer tails with an active tail reflex resulted in the lower adhesive foot forces necessary for stabilizing successful landings, with a tail shortened to 25% requiring over twice the adhesive foot force.

A minimal robophysical model of quadriflagellate self-propulsion

Locomotion at the microscale is remarkably sophisticated. Microorganisms have evolved diverse strategies to move within highly viscous environments, using deformable, propulsion-generating appendages such as cilia and flagella to drive helical or undulatory motion. In single-celled algae, these appendages can be arranged in different ways around an approximately 10 μm long cell body, and coordinated in distinct temporal patterns. Inspired by the observation that some quadriflagellates (bearing four flagella) have an outwardly similar morphology and flagellar beat pattern, yet swim at different speeds, this study seeks to determine whether variations in swimming performance could arise solely from differences in swimming gait. Robotics approaches are particularly suited to such investigations, where the phase relationships between appendages can be readily manipulated. Here, we developed autonomous, algae-inspired robophysical models that can self-propel in a viscous fluid. These macroscopic robots (length and width = 8.5 cm, height = 2 cm) have four independently actuated 'flagella' (length = 13 cm) that oscillate under low-Reynolds number conditions (Re∼O(10-1)). We tested the swimming performance of these robot models with appendages arranged two distinct configurations, and coordinated in three distinct gaits. The gaits, namely the pronk, the trot, and the gallop, correspond to gaits adopted by distinct microalgal species. When the appendages are inserted perpendicularly around a central 'body', the robot achieved a net performance of 0.15-0.63 body lengths per cycle, with the trot gait being the fastest. Robotic swimming performance was found to be comparable to that of the algal microswimmers across all gaits. By creating a minimal robot that can successfully reproduce cilia-inspired drag-based swimming, our work paves the way for the design of next-generation devices that have the capacity to autonomously navigate aqueous environments.

Body Caudal Undulation measured by Soft Sensors and emulated by Soft Artificial Muscles

We propose the use of bio-inspired robotics equipped with soft sensor technologies to gain a better understanding of the mechanics and control of animal movement. Soft robotic systems can be used to generate new hypotheses and uncover fundamental principles underlying animal locomotion and sensory capabilities, which could subsequently be validated using living organisms. Physical models increasingly include lateral body movements, notably back and tail bending, which are necessary for horizontal plane undulation in model systems ranging from fish to amphibians and reptiles. We present a comparative study of the use of physical modeling in conjunction with soft robotics and integrated soft and hyperelastic sensors to monitor local pressures, enabling local feedback control, and discuss issues related to understanding the mechanics and control of undulatory locomotion. A parallel approach combining live animal data with biorobotic physical modeling promises to be beneficial for gaining a better understanding of systems in motion.

Soft robotics: the route to true robotic organisms

Soft Robotics has come to the fore in the last decade as a new way of conceptualising, designing and fabricating robots. Soft materials empower robots with locomotion, manipulation, and adaptability capabilities beyond those possible with conventional rigid robots. Soft robots can also be made from biological, biocompatible and biodegradable materials. This offers the tantalising possibility of bridging the gap between robots and organisms. Here, we discuss the properties of soft materials and soft systems that make them so attractive for future robots. In doing so, we consider how future robots can behave like, and have abilities akin to, biological organisms. These include huge numbers, finite lifetime, homeostasis and minimal—and even positive—environmental impact. This paves the way for future robots, not as machines, but as robotic organisms.

Collecting eco-evolutionary data in the dark: Impediments to subterranean research and how to overcome them

Caves and other subterranean habitats fulfill the requirements of experimental model systems to address general questions in ecology and evolution. Yet, the harsh working conditions of these environments and the uniqueness of the subterranean organisms have challenged most attempts to pursuit standardized research.Two main obstacles have synergistically hampered previous attempts. First, there is a habitat impediment related to the objective difficulties of exploring subterranean habitats and our inability to access the network of fissures that represents the elective habitat for the so-called "cave species." Second, there is a biological impediment illustrated by the rarity of most subterranean species and their low physiological tolerance, often limiting sample size and complicating laboratory experiments.We explore the advantages and disadvantages of four general experimental setups (in situ, quasi in situ, ex situ, and in silico) in the light of habitat and biological impediments. We also discuss the potential of indirect approaches to research. Furthermore, using bibliometric data, we provide a quantitative overview of the model organisms that scientists have exploited in the study of subterranean life.Our over-arching goal is to promote caves as model systems where one can perform standardized scientific research. This is important not only to achieve an in-depth understanding of the functioning of subterranean ecosystems but also to fully exploit their long-discussed potential in addressing general scientific questions with implications beyond the boundaries of this discipline.

Locomotion of Miniature Soft Robots

Miniature soft robots are mobile devices, which are made of smart materials that can be actuated by external stimuli to realize their desired functionalities. Here, the key advancements and challenges of the locomotion producible by miniature soft robots in micro- to centimeter length scales are highlighted. It is highly desirable to endow these small machines with dexterous locomotive gaits as it enables them to easily access highly confined and enclosed spaces via a noninvasive manner. If miniature soft robots are able to capitalize this unique ability, they will have the potential to transform a vast range of applications, including but not limited to, minimally invasive medical treatments, lab-on-chip applications, and search-and-rescue missions. The gaits of miniature soft robots are categorized into terrestrial, aquatic, and aerial locomotion. Except for the centimeter-scale robots that can perform aerial locomotion, the discussions in this report are centered around soft robots that are in the micro- to millimeter length scales. Under each category of locomotion, prospective methods and strategies that can improve their gait performances are also discussed. This report provides critical analyses and discussions that can inspire future strategies to make miniature soft robots significantly more agile.

Locomotor transitions in the potential energy landscape-dominated regime

To traverse complex three-dimensional terrain with large obstacles, animals and robots must transition across different modes. However, the most mechanistic understanding of terrestrial locomotion concerns how to generate and stabilize near-steady-state, single-mode locomotion (e.g. walk, run). We know little about how to use physical interaction to make robust locomotor transitions. Here, we review our progress towards filling this gap by discovering terradynamic principles of multi-legged locomotor transitions, using simplified model systems representing distinct challenges in complex three-dimensional terrain. Remarkably, general physical principles emerge across diverse model systems, by modelling locomotor-terrain interaction using a potential energy landscape approach. The animal and robots' stereotyped locomotor modes are constrained by physical interaction. Locomotor transitions are stochastic, destabilizing, barrier-crossing transitions on the landscape. They can be induced by feed-forward self-propulsion and are facilitated by feedback-controlled active adjustment. General physical principles and strategies from our systematic studies already advanced robot performance in simple model systems. Efforts remain to better understand the intelligence aspect of locomotor transitions and how to compose larger-scale potential energy landscapes of complex three-dimensional terrains from simple landscapes of abstracted challenges. This will elucidate how the neuromechanical control system mediates physical interaction to generate multi-pathway locomotor transitions and lead to advancements in biology, physics, robotics and dynamical systems theory.

The Role of the Tail or Lack Thereof in the Evolution of Tetrapod Aquatic Propulsion

Synopsis Secondary aquatic vertebrates exhibit a diversity of swimming modes that use paired limbs and/or the tail. Various secondarily aquatic tetrapod clades, including amphibians, reptiles, and mammals employ transverse undulations or oscillations of the tail for swimming. These movements have often been classified according to a kinematic gradient that was established for fishes, but may not be appropriate to describe the swimming motions of tetrapods. To understand the evolution of movements and design of the tail in aquatic tetrapods, we categorize the types of tails used for swimming and examine swimming kinematics and hydrodynamics. From a foundation of a narrow, elongate ancestral tail, the tails used for swimming by aquatic tetrapods are classified as tapered, keeled, paddle, and lunate. Tail undulations are associated with tapered, keeled, and paddle tails for a diversity of taxa. Propulsive undulatory waves move down the tail with increasing amplitude toward the tail tip, while moving posteriorly at a velocity faster than the anterior motion of the body indicating that the tail is used for thrust generation. Aquatic propulsion is associated with the transfer of momentum to the water from the swimming movements of the tail, particularly at the trailing edge. The addition of transverse extensions and flattening of the tail increases the mass of water accelerated posteriorly and affects vorticity shed into the wake for more aquatically adapted animals. DPIV (Digital Particle Image Velocimetry) reveals differences were exhibited in the vortex wake between the morphological and kinematic extremes of the alligator with a tapering undulating tail and the dolphin with oscillating wing-like flukes that generate thrust. In addition to exploring the relationship between shape of undulating tails and swimming performance across aquatic tetrapods, the role of tail reduction or loss of a tail in aquatic-tetrapod swimming was also explored. For aquatic tetrapods, reduction would have been due to factors including locomotor and defensive specializations and phylogenetic and physiological constraints. Possession of a thrust-generating tail for swimming, or lack thereof, guided various lineages of secondarily aquatic vertebrates into different evolutionary trajectories for effective aquatic propulsion (i.e., speed, efficiency, acceleration).

Archerfish coordinate fin maneuvers with their shots

Archerfish down a variety of aerial prey from a range of distances using water jets that they adjust to the size and distance of their prey. We describe here that characteristic rapid fin maneuvers, most notably of the pectoral and pelvic fins, are precisely coordinated with the release of the jet. We discovered these maneuvers in two fish, the jets of which had been characterized in detail, that had been trained to shoot from fixed positions at targets at different heights and that remained stable during their shots. Based on the findings in these individuals, we examined shooting-associated fin movement in 28 further archerfish of two species that could shoot from freely chosen positions at targets at different heights. Slightly before the onset of the water jet, at a time when the shooter remains stable, the pectoral fins of all shooters switched from asynchronous low-amplitude beating to a synchronized rapid forward flap. The onset and duration of the forward and subsequent backward flap were robust across all individuals and shooting angles but depended on target height. The pelvic fins were slowly adducted at the start of the jet and stopped moving after its release. All other fins also showed a characteristic sequence of activation, some starting ∼0.5 s before the shot. Our findings suggest that shooting-related fin maneuvers are needed to stabilize the shooter, and that these maneuvers are an important component in the precise and powerful far-distance shooting in archerfish.