Underwater walking

Effect of Bionic Crab Shell Attitude Parameters on Lift and Drag in a Flow Field

Underwater bionic-legged robots encounter significant challenges in attitude, velocity, and positional control due to lift and drag in water current environments, making it difficult to balance operational efficiency with motion stability. This study delves into the hydrodynamic properties of a bionic crab robot's shell, drawing inspiration from the sea crab's motion postures. It further refines the robot's underwater locomotion strategy based on these insights. Initially, the research involved collecting attitude data from crabs during underwater movement through biological observation. Subsequently, hydrodynamic simulations and experimental validations of the bionic shell were conducted, examining the impact of attitude parameters on hydrodynamic performance. The findings reveal that the transverse angle predominantly influences lift and drag. Experiments in a test pool with a crab-like robot, altering transverse angles, demonstrated that increased transverse angles enhance the robot's underwater walking efficiency, stability, and overall performance.

Underwater legged robotics: review and perspectives

Nowadays, there is a growing awareness on the social and economic importance of the ocean. In this context, being able to carry out a diverse range of operations underwater is of paramount importance for many industrial sectors as well as for marine science and to enforce restoration and mitigation actions. Underwater robots allowed us to venture deeper and for longer time into the remote and hostile marine environment. However, traditional design concepts such as propeller driven remotely operated vehicles, autonomous underwater vehicles, or tracked benthic crawlers, present intrinsic limitations, especially when a close interaction with the environment is required. An increasing number of researchers are proposing legged robots as a bioinspired alternative to traditional designs, capable of yielding versatile multi-terrain locomotion, high stability, and low environmental disturbance. In this work, we aim at presenting the new field of underwater legged robotics in an organic way, discussing the prototypes in the state-of-the-art and highlighting technological and scientific challenges for the future. First, we will briefly recap the latest developments in traditional underwater robotics from which several technological solutions can be adapted, and on which the benchmarking of this new field should be set. Second, we will the retrace the evolution of terrestrial legged robotics, pinpointing the main achievements of the field. Third, we will report a complete state of the art on underwater legged robots focusing on the innovations with respect to the interaction with the environment, sensing and actuation, modelling and control, and autonomy and navigation. Finally, we will thoroughly discuss the reviewed literature by comparing traditional and legged underwater robots, highlighting interesting research opportunities, and presenting use case scenarios derived from marine science applications.

A virtuous cycle between invertebrate and robotics research: perspective on a decade of Living Machines research

Many invertebrates are ideal model systems on which to base robot design principles due to their success in solving seemingly complex tasks across domains while possessing smaller nervous systems than vertebrates. Three areas are particularly relevant for robot designers: Research on flying and crawling invertebrates has inspired new materials and geometries from which robot bodies (their morphologies) can be constructed, enabling a new generation of softer, smaller, and lighter robots. Research on walking insects has informed the design of new systems for controlling robot bodies (their motion control) and adapting their motion to their environment without costly computational methods. And research combining wet and computational neuroscience with robotic validation methods has revealed the structure and function of core circuits in the insect brain responsible for the navigation and swarming capabilities (their mental faculties) displayed by foraging insects. The last decade has seen significant progress in the application of principles extracted from invertebrates, as well as the application of biomimetic robots to model and better understand how animals function. This Perspectives paper on the past 10 years of the Living Machines conference outlines some of the most exciting recent advances in each of these fields before outlining lessons gleaned and the outlook for the next decade of invertebrate robotic research.

Survey of biomechanical aspects of arthropod terrestrialisation - Substrate bound legged locomotion

Arthropods are the most diverse clade on earth with regard to both species number and variability of body plans. Their general body plan is characterised by variable numbers of legs, and many-legged locomotion is an essential aspect of many aquatic and terrestrial arthropod species. Moreover, arthropods belong to the first groups of animals to colonise subaerial habitats, and they did so repeatedly and independently in a couple of clades. Those arthropod clades that colonised land habitats were equipped with highly variable body plans and locomotor apparatuses. Proceeding from their respective specific anatomies, they were challenged with strongly changing environmental conditions as well as altered physical and physiological constraints. This review explores the transitions from aquatic to terrestrial habitats across the different arthropod body plans and explains the major mechanisms and principles that constrain design and function of a range of locomotor apparatuses. Important aspects of movement physiology addressed here include the effects of different numbers of legs, different body sizes, miniaturisation and simplification of body plans and different ratios of inertial and damping forces. The article's focus is on continuous legged locomotion, but related ecological and behavioural aspects are also taken into account.

Locomotory behaviour of the intertidal marble crab (Pachygrapsus marmoratus) supports the underwater spring-loaded inverted pendulum as a fundamental model for punting in animals

In aquatic pedestrian locomotion the dynamics of terrestrial and aquatic environments are coupled. Here we study terrestrial running and aquatic punting locomotion of the marine-living crab Pachygrapsus marmoratus. We detected both active and passive phases of running and punting through the observation of crab locomotory behaviour in standardized settings and by three-dimensional kinematic analysis of its dynamic gaits using high-speed video cameras. Variations in different stride parameters were studied and compared. The comparison was done based on the dimensionless parameter the Froude number (Fr) to account for the effect of buoyancy and size variability among the crabs. The underwater spring-loaded inverted pendulum (USLIP) model better fitted the dynamics of aquatic punting. USLIP takes account of the damping effect of the aquatic environment, a variable not considered by the spring-loaded inverted pendulum (SLIP) model in reduced gravity. Our results highlight the underlying principles of aquatic terrestrial locomotion by comparing it with terrestrial locomotion. Comparing punting with running, we show and increased stride period, decreased duty cycle and orientation of the carapace more inclined with the horizontal plane, indicating the significance of fluid forces on the dynamics due to the aquatic environment. Moreover, we discovered periodicity in punting locomotion of crabs and two different gaits, namely, long-flight punting and short-flight punting, distinguished by both footfall patterns and kinematic parameters. The generic fundamental model which belongs to all animals performing both terrestrial and aquatic legged locomotion has implications for control strategies, evolution and translation to robotic artefacts.

Comparative study of forced oscillators for the adaptive generation of rhythmic movements in robot controllers

The interest of central pattern generators in robot motor coordination is universally recognized so much so that a lot of possibilities on different scales of modeling are nowadays available. While each method obviously has its advantages and drawbacks, some could be more suitable for human-robot interactions. In this paper, we compare three oscillator models: Matsuoka, Hopf and Rowat-Selverston models. These models are integrated to a control architecture for a robotic arm and evaluated in simulation during a simplified handshaking interaction which involves constrained rhythmic movements. Furthermore, Hebbian plasticity mechanisms are integrated to the Hopf and Rowat-Selverston models which can incorporate such mechanisms, contrary to the Matsuoka. Results show that the Matsuoka oscillator is subpar in all aspects and for the two others, that plasticity improves synchronization and leads to a significant decrease in the power consumption.

Locomotion of arthropods in aquatic environment and their applications in robotics

Many bio-inspired robots have been developed so far after careful investigation of animals' locomotion. To successfully apply the locomotion of natural counterparts to robots for efficient and improved mobility, it is essential to understand their principles. Although a lot of research has studied either animals' locomotion or bio-inspired robots, there have only been a few attempts to broadly review both of them in a single article. Among the millions of animal species, this article reviewed various forms of aquatic locomotion in arthropods including relevant bio-inspired robots. Despite some previous robotics research inspired by aquatic arthropods, we found that many less-investigated or even unexplored areas are still present. Therefore, this article has been prepared to identify what types of new robotics research can be carried out after drawing inspiration from the aquatic locomotion of arthropods and to provide fruitful insights that may lead us to develop an agile and efficient aquatic robot.

Development and Training of a Neural Controller for Hind Leg Walking in a Dog Robot

Animals dynamically adapt to varying terrain and small perturbations with remarkable ease. These adaptations arise from complex interactions between the environment and biomechanical and neural components of the animal's body and nervous system. Research into mammalian locomotion has resulted in several neural and neuro-mechanical models, some of which have been tested in simulation, but few “synthetic nervous systems” have been implemented in physical hardware models of animal systems. One reason is that the implementation into a physical system is not straightforward. For example, it is difficult to make robotic actuators and sensors that model those in the animal. Therefore, even if the sensorimotor circuits were known in great detail, those parameters would not be applicable and new parameter values must be found for the network in the robotic model of the animal. This manuscript demonstrates an automatic method for setting parameter values in a synthetic nervous system composed of non-spiking leaky integrator neuron models. This method works by first using a model of the system to determine required motor neuron activations to produce stable walking. Parameters in the neural system are then tuned systematically such that it produces similar activations to the desired pattern determined using expected sensory feedback. We demonstrate that the developed method successfully produces adaptive locomotion in the rear legs of a dog-like robot actuated by artificial muscles. Furthermore, the results support the validity of current models of mammalian locomotion. This research will serve as a basis for testing more complex locomotion controllers and for testing specific sensory pathways and biomechanical designs. Additionally, the developed method can be used to automatically adapt the neural controller for different mechanical designs such that it could be used to control different robotic systems.

A survey on CPG-inspired control models and system implementation

This paper surveys the developments of the last 20 years in the field of central pattern generator (CPG) inspired locomotion control, with particular emphasis on the fast emerging robotics-related applications. Functioning as a biological neural network, CPGs can be considered as a group of coupled neurons that generate rhythmic signals without sensory feedback; however, sensory feedback is needed to shape the CPG signals. The basic idea in engineering endeavors is to replicate this intrinsic, computationally efficient, distributed control mechanism for multiple articulated joints, or multi-DOF control cases. In terms of various abstraction levels, existing CPG control models and their extensions are reviewed with a focus on the relative advantages and disadvantages of the models, including ease of design and implementation. The main issues arising from design, optimization, and implementation of the CPG-based control as well as possible alternatives are further discussed, with an attempt to shed more light on locomotion control-oriented theories and applications. The design challenges and trends associated with the further advancement of this area are also summarized.

Dynamic Modelling of a CPG-Controlled Amphibious Biomimetic Swimming Robot

This paper focuses on the modelling and control problems of a self-propelled, multimodal amphibious robot. Inspired by the undulatory body motions of fish and dolphins, the amphibious robot propels itself underwater by oscillations of several modular fish-like propelling units coupled with a pair of pectoral fins capable of non-continuous 360 degree rotation. In order to mimic fish-like undulating propulsion, a control architecture based on Central Pattern Generator (CPG) is applied to the amphibious robot for robust swimming gaits, including forward and backward swimming and turning, etc. With the simplification of the robot as a multi-link serial mechanism, a Lagrangian function is employed to establish the hydrodynamic model for steady swimming. The CPG motion control law is then imported into the Lagrangian-based dynamic model, where an associated system of kinematics and dynamics is formed to solve real-time movements and, further, to guide the exploration of the CPG parameters and steady locomotion gaits. Finally, comparative results between the simulations and experiments are provided to show the effectiveness of the built control models.

Design, Simulation, Fabrication and Testing of a Bio-Inspired Amphibious Robot with Multiple Modes of Mobility

Surf-zone environments represent an extreme challenges to robot operation. A robot that autonomously navigates rocky terrain, constantly changing underwater currents, hard-packed moist sand and loose dry sand characterizing this environment, would have significant utility in a range of defence and civilian missions. The study of animal locomotion mechanisms can elucidate specific movement principles that can be applied to address these demands. In this work, we report on the design and optimization of a biologically inspired amphibious robot for deployment and operation in an ocean beach environment. We specifically report a new design fusing a range of insectinspired passive mechanisms with active autonomous control architectures to seamlessly adapt to and traverse a range of challenging substrates both in and out of the water, and the design and construction of SeaDog, a proof-of-concept amphibious robot built for navigating rocky or sandy beaches and turbulent surf zones. The robot incorporates a layered hull and chassis design that is integrated into a waterproof Explorer Case in order to provide a large, protected payload in an easy-to-carry package. It employs a rugged drivetrain with four wheel-legs and a unique tail design and actuation strategy to aid in climbing, swimming and stabilization. Several modes of terrestrial and aquatic locomotion are suggested and tested versus range of mobility metrics, including data obtained in simulation and hardware testing. A waterproofing strategy is also tested and discussed, providing a foundation for future generations of amphibious mobile robots.

Neuromechanical simulation

The importance of the interaction between the body and the brain for the control of behavior has been recognized in recent years with the advent of neuromechanics, a field in which the coupling between neural and biomechanical processes is an explicit focus. A major tool used in neuromechanics is simulation, which connects computational models of neural circuits to models of an animal's body situated in a virtual physical world. This connection closes the feedback loop that links the brain, the body, and the world through sensory stimuli, muscle contractions, and body movement. Neuromechanical simulations enable investigators to explore the dynamical relationships between the brain, the body, and the world in ways that are difficult or impossible through experiment alone. Studies in a variety of animals have permitted the analysis of extremely complex and dynamic neuromechanical systems, they have demonstrated that the nervous system functions synergistically with the mechanical properties of the body, they have examined hypotheses that are difficult to test experimentally, and they have explored the role of sensory feedback in controlling complex mechanical systems with many degrees of freedom. Each of these studies confronts a common set of questions: (i) how to abstract key features of the body, the world and the CNS in a useful model, (ii) how to ground model parameters in experimental reality, (iii) how to optimize the model and identify points of sensitivity and insensitivity, and (iv) how to share neuromechanical models for examination, testing, and extension by others.

Robot navigation: implications from search strategies in exploring crayfish

Biomimetic applications play an important role in informing the field of robotics. One aspect is navigation – a skill automobile robots require to perform useful tasks. A sub-area of this is search strategies, e.g. for search and rescue, demining, exploring surfaces of other planets or as a default strategy when other navigation mechanisms fail. Despite that, only a few approaches have been made to transfer biological knowledge of search mechanisms on surfaces along the ground into biomimetic applications. To provide insight for robot navigation strategies, this study describes the paths a crayfish used to explore terrain. We tracked movement when different sets of sensory input were available. We then tested this algorithm with a computer model crayfish and concluded that the movement ofC. destructorhas a specialised walking strategy that could provide a suitable baseline algorithm for autonomous mobile robots during navigation.

Kinematics, hydrodynamics and force production of pleopods suggest jet-assisted walking in the American lobster (Homarus americanus)

The American lobster (Homarus americanus) displays a diverse set of locomotory behaviours that includes tail flips, walking and paddling. Paddling is carried out by the four pairs of paddle-shaped pleopods on the ventral abdomen. Although it is recognized that pleopod-generated fluid flows have some locomotory role in adults, reports on their relative importance in locomotion are inconsistent. This paper integrates experimental kinematics and hydrodynamics of lobster pleopod beating to determine the mechanism and magnitude of pleopod force production. A kinematic analysis of pleopod beating in live lobsters showed that the pleopods execute an adlocomotory metachronal beating pattern. We modelled in vivo pleopod kinematics with a set of simple trigonometric functions, and used these functions to program a mechanical lobster model consisting of motor-driven pleopods on a lobster abdomen exoskeleton. Based on flow visualizations obtained from applying particle image velocimetry to the lobster model, we propose that the unsteady metachronal kinematics of the pleopods can maximize thrust by exploiting forces arising from individual pleopod activity and interactions among adjacent pairs. The pleopods continuously entrain fluid surrounding the lobster and create a caudally directed fluid jet oriented parallel to the substratum. Inputting wake morphology and velocity data into a simplified model for steady jet thrust showed that the pleopods of the lobster model produced 27–54 mN of thrust, which is comparable to the propulsive forces generated by other proficient swimmers. These results suggest that lobster pleopods are capable of producing forces of a magnitude that could assist the walking legs in forward propulsion.

The flow generated by an active olfactory system of the red swamp crayfish

Crayfish are nocturnal animals that mainly rely on their chemoreceptors to locate food. On a crayfish scale, chemical stimuli received from a distant source are dispersed by an ambient flow rather than molecular diffusion. When the flow is weak or absent, food searching can be facilitated by currents generated by the animal itself. Crayfish employ their anterior fan organs to produce a variety of flow patterns. Here we study the flow generated by Procambarus clarkii in response to odour stimulation. We found that while searching for food the crayfish generates one or two outward jets. These jets induce an inflow that draws odour to the crayfish's anterior chemoreceptors. We quantified velocity fields in the inflow region using Particle Image Velocimetry. The results show that the inflow velocity decreases proportionally to the inverse distance from the animal so that it takes about 100 s for an odour plume to reach the animal's chemoreceptors from a distance of 10 cm. We compare the inflow generated by live crayfish with that produced by a mechanical model. The model consists of two nozzles and an inlet and provides two jets and a sink so that the overall mass flux is zero. Use of the model enabled us to analyze the inflow at various jet parameters. We show that variation of directions and relative intensities of the jets allows the direction of odour attraction to be changed. These results provide a rationale for biomimetic robot design. We discuss sensitivity and efficiency of such a robot.

Biomimetic approaches to the control of underwater walking machines

We have developed a biomimetic robot based on the American lobster. The robot is designed to achieve the performance advantages of the animal model by adopting biomechanical features and neurobiological control principles. Three types of controllers are described. The first is a state machine based on the connectivity and dynamics of the lobster central pattern generator (CPG). The state machine controls myomorphic actuators based on shape memory alloys (SMAs) and responds to environmental perturbation through sensors that employ a labelled-line code. The controller supports a library of action patterns and exteroceptive reflexes to mediate tactile navigation, obstacle negotiation and adaptation to surge. We are extending this controller to neuronal network-based models. A second type of leg CPG is based on synaptic networks of electronic neurons and has been adapted to control the SMA actuated leg. A brain is being developed using layered reflexes based on discrete time map-based neurons.

Whole cell stochastic model reproduces the irregularities found in the membrane potential of bursting neurons

Irregular intrinsic behavior of neurons seems ubiquitous in the nervous system. Even in circuits specialized to provide periodic and reliable patterns to control the repetitive activity of muscles, such as the pyloric central pattern generator (CPG) of the crustacean stomatogastric ganglion (STG), many bursting motor neurons present irregular activity when deprived from synaptic inputs. Moreover, many authors attribute to these irregularities the role of providing flexibility and adaptation capabilities to oscillatory neural networks such as CPGs. These irregular behaviors, related to nonlinear and chaotic properties of the cells, pose serious challenges to developing deterministic Hodgkin-Huxley-type (HH-type) conductance models. Only a few deterministic HH-type models based on experimental conductance values were able to show such nonlinear properties, but most of these models are based on slow oscillatory dynamics of the cytosolic calcium concentration that were never found experimentally in STG neurons. Based on an up-to-date single-compartment deterministic HH-type model of a STG neuron, we developed a stochastic HH-type model based on the microscopic Markovian states that an ion channel can achieve. We used tools from nonlinear analysis to show that the stochastic model is able to express the same kind of irregularities, sensitivity to initial conditions, and low dimensional dynamics found in the neurons isolated from the STG. Without including any nonrealistic dynamics in our whole cell stochastic model, we show that the nontrivial dynamics of the membrane potential naturally emerge from the interplay between the microscopic probabilistic character of the ion channels and the nonlinear interactions among these elements. Moreover, the experimental irregular behavior is reproduced by the stochastic model for the same parameters for which the membrane potential of the original deterministic model exhibits periodic oscillations.