Biomimetic Robot Research Articles

A Shift from Efficiency to Adaptability: Recent Progress in Biomimetic Interactive Soft Robotics in Wet Environments.

Research field of soft robotics develops exponentially since it opens up many imaginations, such as human‐interactive robot, wearable robots, and transformable robots in unpredictable environments. Wet environments such as sea and in vivo represent dynamic and unstructured environments that adaptive soft robots can reach their potentials. Recent progresses in soft hybridized robotics performing tasks underwater herald a diversity of interactive soft robotics in wet environments. Here, the development of soft robots in wet environments is reviewed. The authors recapitulate biomimetic inspirations, recent advances in soft matter materials, representative fabrication techniques, system integration, and exemplary functions for underwater soft robots. The authors consider the key challenges the field faces in engineering material, software, and hardware that can bring highly intelligent soft robots into real world.

The Chain-Link Actuator: Exploiting the Bending Stiffness of McKibben Artificial Muscles to Achieve Larger Contraction Ratios

McKibben artificial muscles, comprised of an expandable bladder wrapped in a double-helix-braided sheath, have the ability to generate forces without restricting motion to occur exclusively along the direction of actuation. This makes them attractive for a variety of applications including soft, wearable, and biomimetic robots. Despite their advantages, the theoretical maximum contraction ratio of McKibben muscles is only 36.3\%, which restricts the range of motion of the systems they actuate. This work introduces a novel ‘chain-link actuator’ that exploits the bending stiffness of McKibben muscles to achieve contraction ratios of more than 50\%. A static model that captures the relationship between pressure, displacement, and force is presented and validated on several real chain-link actuator systems.

Project on Student Editorial Committee: Report on the 39th Annual Conference of the Robotics Society of Japan (General Session: Biomimetic Robot)

Project on Student Editorial Committee: Report on the 39th Annual Conference of the Robotics Society of Japan (General Session: Biomimetic Robot)

Recent advances in biomimetic soft robotics: fabrication approaches, driven strategies and applications.

Compared to traditional rigid-bodied robots, soft robots are constructed using physically flexible/elastic bodies and electronics to mimic nature and enable novel applications in industry, healthcare, aviation, military, etc. Recently, the fabrication of robots on soft matter with great flexibility and compliance has enabled smooth and sophisticated 'multi-degree-of-freedom' 3D actuation to seamlessly interact with humans, other organisms and non-idealized environments in a highly complex and controllable manner. Herein, we summarize the fabrication approaches, driving strategies, novel applications, and future trends of soft robots. Firstly, we introduce the different fabrication approaches to prepare soft robots and compare and systematically discuss their advantages and disadvantages. Then, we present the actuator-based and material-based driving strategies of soft robotics and their characteristics. The representative applications of soft robotics in artificial intelligence, medicine, sensors, and engineering are summarized. Also, some remaining challenges and future perspectives in soft robotics are provided. This work highlights the recent advances of soft robotics in terms of functional material selection, structure design, control strategies and biomimicry, providing useful insights into the development of next-generation functional soft robotics.

A Map Construction Method Based on the Cognitive Mechanism of Rat Brain Hippocampus

The entorhinal-hippocampus structure in the mammalian brain is the core area for realizing spatial cognition. However, the visual perception and loop detection methods in the current biomimetic robot navigation model still rely on traditional visual SLAM schemes and lack the process of exploring and applying biological visual methods. Based on this, we propose a map construction method that mimics the entorhinal-hippocampal cognitive mechanism of the rat brain according to the response of entorhinal cortex neurons to eye saccades in recent related studies. That is, when mammals are free to watch the scene, the entorhinal cortex neurons will encode the saccade position of the eyeball to realize the episodic memory function. The characteristics of this model are as follows: 1) A scene memory algorithm that relies on visual saccade vectors is constructed to imitate the biological brain's memory of environmental situation information matches the current scene information with the memory; 2) According to the information transmission mechanism formed by the hippocampus and the activation theory of spatial cells, a localization model based on the grid cells of the entorhinal cortex and the place cells of the hippocampus was constructed; 3) Finally, the scene memory algorithm is used to correct the errors of the positioning model and complete the process of constructing the cognitive map. The model was subjected to simulation experiments on publicly available datasets and physical experiments using a mobile robot platform to verify the environmental adaptability and robustness of the algorithm. The algorithm will provide a basis for further research into bionic robot navigation.

A biomimetic robot crawling bidirectionally with load inspired by rock-climbing fish

A biomimetic robot crawling bidirectionally with load inspired by rock-climbing fish

Lampreys in Human Life, Their Cultural and Folklore Importance

This contribution provides summary information on the historical and contemporary significance of lampreys for human life. The unusual to bizarre appearance of lampreys initially posed a problem for zoologists to correctly classify lampreys in the zoological system. In certain places, lampreys are used as bait in sport fishing, and a total of seven species are fished extensively for gastronomic purposes in Europe, North America, Australia, and Asia. New information about role of lampreys in human gastronomy was obtained by studying historical sources from Central Europe, especially from the region of Bohemia. The first specific cooking recipes have been preserved from the turn of the 15^th and 16^th Centuries. Instructions for cooking lampreys were mentioned by Georg Handsch von Limus, Paulus de Praga, Jan Severin the Younger and Pavel Severin of Kapí mountain. The quality of their meat is excellent, however, the slime and serum are poisonous, so there are known historical data about probable poisoning after their consumption. At present, lampreys are routinely available fresh, fried, smoked, marinated, canned or in vinegar. Lampreys play an important role in the culture and folklore of some nations. For example, lampreys are ecologically and culturally important for the North American Indian tribes of Yurok and Karuk.. The Pacific lamprey is also of spiritual significance for these tribes. The enormous esteem people have for lampreys is also reflected in the various coats of arms, in which the lamprey appears. Cooking skills and traditions are practiced at various public festivals where lampreys are caught and immediately consumed after cooking (e.g., Estonia, Latvia, Lithuania, Portugal, Spain). Lampreys have become an important model group in evolutionary studies of vertebrate development, and due to their remarkable properties, they are also used in biomedical research. Lampreys can be used for long-term bioindication of water environment, but their larvae are not a suitable bioindicator of short-term water quality worsening (see research results from the Czech Republic). Based on the analysis of the lamprey’s specific method of swimming, biologists and engineers created a biomimetic robot with an electronic nervous system that imitated the movement and orientation of lampreys in the water. Nevertheless, there is also an example of the harmful effect of lampreys, namely the parasitic sea lamprey, which causes significant damage to economically important fish in the Great Lakes, requiring a yearly implementation of financially expensive measures to eliminate the lamprey.

Graceful Transitions through Maximal Persistence of Behavior

Problems of locomotion typically encounter switching between gaits. In many applications, it is desirable to make such transitions between modes or gaits inconspicuous and graceful. This is achieved by keeping the typical behavior of the system as persistent as possible. It is shown that this problem can be defined in a more abstract sense, and therefore generalized to a new class of problems, called “maximum persistence of behavior.”In this presentation, I will give a precise definition of this concept, for signals and for systems, and illustrate some applications from thermodynamics to signal study and robotics. I will also introduce the dual problem of filtering in the context of “maximal persistence of behavior.” The results stem from joint work with Deryck Yeung (Trinity University, San Antonio, TX), Basit Memon (Habib University, Karachi, PK), and Vishal Murali (now at NVIDIA) while at Georgia Tech.The paradigm starts by defining typical behaviors in the framework initiated by J.C. Willems. Gluing two typical signals or typical system behaviors requires connections (raccordations) that belong to a larger class of behaviors, but are locally close to the typical behaviors. Solutions with persistent behavior are then sought via optimization for a kernel or an image problem. This solution encapsulates the controllability problem of Willems, morphing theory in image analysis, object shaping, quasi-stationary transitions from thermodynamics, and orbit transfer problems, and can be characterized in a geometric way. In the robotics framework, obvious applications are in gait transitions for biomimetic robots as when switching from walking (e.g., while inspecting) to running (evasion), or a gait transition necessitated by a change in terrain (solid, muddy, or granular). In particular, I will discuss a method of smoothly connecting periodic orbits of systems. We first deal with the case when the periodic signals to be connected are of the same period and then move on to discuss the case of different periods, requiring in addition a frequency warping.

Sector search strategies for odor trail tracking

Ants, mice, and dogs often use surface-bound scent trails to establish navigation routes or to find food and mates, yet their tracking strategies remain poorly understood. Chemotaxis-based strategies cannot explain casting, a characteristic sequence of wide oscillations with increasing amplitude performed upon sustained loss of contact with the trail. We propose that tracking animals have an intrinsic, geometric notion of continuity, allowing them to exploit past contacts with the trail to form an estimate of where it is headed. This estimate and its uncertainty form an angular sector, and the emergent search patterns resemble a "sector search." Reinforcement learning agents trained to execute a sector search recapitulate the various phases of experimentally observed tracking behavior. We use ideas from polymer physics to formulate a statistical description of trails and show that search geometry imposes basic limits on how quickly animals can track trails. By formulating trail tracking as a Bellman-type sequential optimization problem, we quantify the geometric elements of optimal sector search strategy, effectively explaining why and when casting is necessary. We propose a set of experiments to infer how tracking animals acquire, integrate, and respond to past information on the tracked trail. More generally, we define navigational strategies relevant for animals and biomimetic robots and formulate trail tracking as a behavioral paradigm for learning, memory, and planning.

Thermo‐ and Mechanochromic Camouflage and Self‐Healing in Biomimetic Soft Actuators Based on Liquid Crystal Elastomers

AbstractIn nature, many mysterious creatures capable of deformation camouflage, color camouflage, and self‐healing have inspired scientists to develop various biomimetic soft robots. However, the systematic integration of all the above functionalities into a single soft actuator system still remains a challenge. Here we chemically introduce a multi‐stimuli‐responsive tetraarylsuccinonitrile (TASN) chromophore into a liquid crystal elastomer (LCE) network through a facile thiol‐ene photoaddition method. The obtained TASN‐LCE soft actuators not only exhibit reversible shape‐morphing and reversible color‐changing behavior in response to heat and mechanical compression, but also show excellent self‐healing, reprogramming and recycling characteristics. We hope that such a TASN‐LCE actuator system endowed with dynamic distortion, thermo‐ and mechano‐chromic camouflage, and self‐healing functionalities would pave the way for further development of multifunctional biomimetic soft robotic devices.

Thermo- and Mechanochromic Camouflage and Self-Healing in Biomimetic Soft Actuators Based on Liquid Crystal Elastomers.

In nature, many mysterious creatures capable of deformation camouflage, color camouflage, and self-healing have inspired scientists to develop various biomimetic soft robots. However, the systematic integration of all the above functionalities into a single soft actuator system still remains a challenge. Here we chemically introduce a multi-stimuli-responsive tetraarylsuccinonitrile (TASN) chromophore into a liquid crystal elastomer (LCE) network through a facile thiol-ene photoaddition method. The obtained TASN-LCE soft actuators not only exhibit reversible shape-morphing and reversible color-changing behavior in response to heat and mechanical compression, but also show excellent self-healing, reprogramming and recycling characteristics. We hope that such a TASN-LCE actuator system endowed with dynamic distortion, thermo- and mechano-chromic camouflage, and self-healing functionalities would pave the way for further development of multifunctional biomimetic soft robotic devices.

A fast-response electroactive actuator based on TEMPO-oxidized cellulose nanofibers

Cellulose-based electroactive actuators are promising candidates for biomimetic robots and biomedical applications due to their lightweight, high mechanical strength, and natural abundance. However, cellulose-based electroactive actuators exhibit lower actuation performance than traditional conductive polymer actuators. This work reports a fast-response cellulose-based electroactive actuator based on 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) oxidized nanocellulose (TOCNF) film with layered structure fabricated by evaporation, and gold electrodes prepared by ion sputtering. The residual ions during the TEMPO oxidation process and the layered structure due to self-assembly accelerate the ion migration efficiency in actuators. The proposed actuator can reach a tip displacement of 32.1 mm at a voltage of 10 V and deflect 60° in 5 s. After applying a reverse 10 V voltage, the actuator can also be quickly deflected (42.5 mm). In addition, the actuator also shows high electrical actuation performance at low voltage (5 V). The excellent electroactive performance of as-prepared TOCNF/Au enables the feasibility to be applied to actuators.

Transparent Soft Electrothermal Actuators with Integrated Cu Nanowire Heater for Soft Robotics

AbstractSoft actuators with high flexibility have received widespread attention. Here, a transparent electrothermal soft actuator is designed and manufactured via sandwiched copper nanowires (Cu NWs) between two kinds of flexible substrates with different thermal expansion characteristics (polyethylene‐terephthalate (PET) and low‐density polyethylene (LDPE)). In order to improve bending characteristics of the soft actuator, heating performance of heaters with different widths is studied, and the bending characteristics of strain gauges under different voltages are also studied. The fabricated soft actuator can produce a bend of 90° and provide about 1 mN of force at a low voltage of 6 V. The application of this type of soft actuator is demonstrated toward biomimetic robotics, a two‐finger flexible transparent gripper is designed, where two soft actuators are utilized to simulate the movements of human fingers and realizes the operation of picking and placing fine objects. In addition, the topography of the object can be feasibly observed during clamping process of the soft actuator with certain light transmittance, which is favorable for the soft gripper application.

Light-powered soft steam engines for self-adaptive oscillation and biomimetic swimming.

Oscillation plays a vital role in the survival of living organisms in changing environments, and its relevant research has inspired many biomimetic approaches to soft autonomous robotics. However, it remains challenging to create mechanical oscillation that can work under constant energy input and actively adjust the oscillation mode. Here, a steam-driven photothermal oscillator operating under constant light irradiation has been developed to perform continuous or pulsed, damped harmonic mechanical oscillations. The key component of the oscillator comprises a hydrogel containing Fe3O4/Cu hybrid nanorods, which can convert light into heat and generate steam bubbles. Controllable perturbation to the thermomechanical equilibrium of the oscillator can thus be achieved, leading to either continuous or pulsed oscillation depending on the light intensity. Resembling the conventional heat steam engine, this environment-dictated multimodal oscillator uses steam as the working fluid, enabling the design of self-adaptive soft robots that can actively adjust their body functions and working modes in response to environmental changes. An untethered biomimetic neuston-like robot is further developed based on this soft steam engine, which can adapt its locomotion mechanics between uniform and recurrent swimming to light intensity changes and perform on-demand turning under continuous light irradiation. Fueled by water and remotely powered by light, this unique hydrogel oscillator enables easy control over the oscillation dynamics and modes, offering an effective approach to self-adaptive soft robots and solar steam engines.

Bird-inspired dynamic grasping and perching in arboreal environments.

Birds take off and land on a wide range of complex surfaces. In contrast, current robots are limited in their ability to dynamically grasp irregular objects. Leveraging recent findings on how birds take off, land, and grasp, we developed a biomimetic robot that can dynamically perch on complex surfaces and grasp irregular objects. To accommodate high-speed collisions, the robot’s two legs passively transform impact energy into grasp force, while the underactuated grasping mechanism wraps around irregularly shaped objects in less than 50 milliseconds. To determine the range of hardware design, kinematic, behavior, and perch parameters that are sufficient for perching success, we launched the robot at tree branches. The results corroborate our mathematical model, which shows that larger isometrically scaled animals and robots must accommodate disproportionately larger angular momenta, relative to their mass, to achieve similar landing performance. We find that closed-loop balance control serves an important role in maximizing the range of parameters sufficient for perching. The performance of the robot’s biomimetic features attests to the functionality of their avian counterparts, and the robot enables us to study aspects of bird legs in ways that are infeasible in vivo. Our data show that pronounced differences in modern avian toe arrangements do not yield large changes in perching performance, suggesting that arboreal perching does not represent a strong selection pressure among common bird toe topographies. These findings advance our understanding of the avian perching apparatus and highlight design concepts that enable robots to perch on natural surfaces for environmental monitoring.

Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding.

Recognising familiar places is a competence required in many engineering applications that interact with the real world such as robot navigation. Combining information from different sensory sources promotes robustness and accuracy of place recognition. However, mismatch in data registration, dimensionality, and timing between modalities remain challenging problems in multisensory place recognition. Spurious data generated by sensor drop-out in multisensory environments is particularly problematic and often resolved through adhoc and brittle solutions. An effective approach to these problems is demonstrated by animals as they gracefully move through the world. Therefore, we take a neuro-ethological approach by adopting self-supervised representation learning based on a neuroscientific model of visual cortex known as predictive coding. We demonstrate how this parsimonious network algorithm which is trained using a local learning rule can be extended to combine visual and tactile sensory cues from a biomimetic robot as it naturally explores a visually aliased environment. The place recognition performance obtained using joint latent representations generated by the network is significantly better than contemporary representation learning techniques. Further, we see evidence of improved robustness at place recognition in face of unimodal sensor drop-out. The proposed multimodal deep predictive coding algorithm presented is also linearly extensible to accommodate more than two sensory modalities, thereby providing an intriguing example of the value of neuro-biologically plausible representation learning for multimodal navigation.

Adapting Highly-Dynamic Compliant Movements to Changing Environments: A Benchmark Comparison of Reflex- vs. CPG-Based Control Strategies.

To control highly-dynamic compliant motions such as running or hopping, vertebrates rely on reflexes and Central Pattern Generators (CPGs) as core strategies. However, decoding how much each strategy contributes to the control and how they are adjusted under different conditions is still a major challenge. To help solve this question, the present paper provides a comprehensive comparison of reflexes, CPGs and a commonly used combination of the two applied to a biomimetic robot. It leverages recent findings indicating that in mammals both control principles act within a low-dimensional control submanifold. This substantially reduces the search space of parameters and enables the quantifiable comparison of the different control strategies. The chosen metrics are motion stability and energy efficiency, both key aspects for the evolution of the central nervous system. We find that neither for stability nor energy efficiency it is favorable to apply the state-of-the-art approach of a continuously feedback-adapted CPG. In both aspects, a pure reflex is more effective, but the pure CPG allows easy signal alteration when needed. Additionally, the hardware experiments clearly show that the shape of a control signal has a strong influence on energy efficiency, while previous research usually only focused on frequency alignment. Both findings suggest that currently used methods to combine the advantages of reflexes and CPGs can be improved. In future research, possible combinations of the control strategies should be reconsidered, specifically including the modulation of the control signal's shape. For this endeavor, the presented setup provides a valuable benchmark framework to enable the quantitative comparison of different bioinspired control principles.

Metarpillar: Soft robotic locomotion based on buckling-driven elastomeric metamaterials

Mechanical instabilities are emerging as novel actuation mechanisms for the design of biomimetic soft robots and smart structures. The present study shows that by coupling buckling-driven elastomeric auxetic modules actuated by a negative air-pressure, a novel metamaterial-based caterpillar can be designed—the Metarpillar. Following a detailed analysis of the caterpillar’s locomotion, we were able to mimic both its crawling movement and locomotion by using the unique isometric compression of the modules and properly programing the anterograde modular peristaltic contractions. The bioinspired locomotion of the Metarpillar uses the bending triggered by the buckling-driven module contraction to control the friction through a dynamic anchoring between the soft robot and the surface, which is the main mechanism for locomotion in caterpillars and other crawling organisms. Thus, the Metarpillar not only mimics the locomotion of the caterpillar but also displays dynamic similarity and equivalent, or even faster, speeds. Our approach based on metamaterial buckling actuator units opens up a novel strategy for biomimetic soft robotic locomotion that can be extended beyond caterpillars.

Designing biomimetic robots: iterative development of an integrated technology design curriculum

In most middle schools, learning is segregated by discipline. Yet interdisciplinary approaches have been shown to cultivate creative thinking, support problem solving, and develop interest while supporting knowledge gains (NAE & NRC in STEM Integration in K-12 Education: Status, Prospects, and an Agenda for Research. National Academies Press, Washington, 2014). The Designing Biomimetic Robots project emphasizes problem-based learning to integrate engineering, science, and computational thinking (CT). During a 3 to 4-week unit, students study the natural world to learn how animals accomplish different tasks, then design a robot inspired by what they learned. The project engages students in science, engineering, and CT practices. Over the course of a 3-year project, we used a design-based research approach to: (1) identify and describe strategies and challenges that emerge from integrated curriculum design, (2) explicate how a balance of integrated disciplines can provide opportunities for student participation in science, engineering, and CT practices, and (3) explore how a technology design task can support students’ participation in integrated learning. Data from three focal groups (one from each year of the project) suggest that a focused design task, supported by explicit and targeted supports for science, CT, and engineering practices, led to a student technology design process that was driven by disciplinary understanding. This work highlights the importance of drawing out and prioritizing alignments between disciplines (Barber in Educ Des, 2(8), 2015), to enable integrated learning. Additionally, this work demonstrates how a technology design task can support student learning across disciplines, and how engaging in CT practices can further help students draw these connections.

A Polyester/Polypyrrole Textile‐Based Ultrasensitive Wearable Microdistance Sensor

AbstractMicrodistance sensor, which can accurately detect the microdistance change, possesses significant applications in the cutting‐edge technologies including biomedicine, energy storage, and info‐communications. However, the high cost, complicated operation, and stringent testing requirements of the existing microdistance sensors limit their widespread application in the frontier fields, especially for the intelligent wearable electronics. Herein, a novel mechanism to detect microdistance change is developed, in which the external microdistance brings a change in the thickness of conductive textile and further converts into a distinguishable electrical signal. The polyester/polypyrrole (PET/PPy) conductive textile is fabricated via in situ solventless polymerization, and the derived microdistance sensor exhibits an ultrahigh sensitivity of 179 m−1 within the detection region of 10–480 µm, a high resolution up to 5 µm, and good stability. The excellent sensing performance can be attributed to the high elasticity, deformation‐recovery property, and 3D network structures of the PET/PPy conductive textile. Furthermore, the wearable sensor is applied to detect the microdistance changes in human and robot activities, providing an efficient and low‐cost solution for microdistance detection in intelligent medical, health monitoring system, and biomimetic robot.