Bio-inspired Robot Research Articles

The Impact of Dorsal Fin Design on the Swimming Performance of a Snake-Like Robot

Lampreys&#x2019; posterior dual dorsal fins can function as a thrust booster. In addition, the fin-fin interaction of these dorsal fins enables utilization of the energy from the wake, making this species one of the most efficient swimmers. Thus, this dorsal fin configuration can serve as a great source of inspiration for improving the swimming speed and efficiency of bioinspired underwater robots. We perform a systematic experimental and computational study to understand the impact of a dual dorsal fin design on swimming speed and efficiency of an underwater snake-like robot. In the proposed dorsal fin structure, the hind fin often operates in the wake of the fore fin. Hence, its performance is affected by the vortices shed by the fore fin. The spacing of the two dorsal fins and the robot&#x2019;s oscillation parameters significantly impact the swimming performance of the snake-like robot. Four different spacings ranging from 0 to 3 link gaps were tested at three different amplitudes (<inline-formula><tex-math notation="LaTeX">$15^\circ$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$30^{\circ }$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$45^{\circ }$</tex-math></inline-formula>) and angular velocities (2, 3 and 4 rad/s). It was found that changes in the spacing and kinematic parameters would significantly affect the interactions of the vortices shed from the fore and hind fins. This interaction, in turn, affects the vortex formation on the hind fin, resulting in changes in wake strength and formation direction, which would significantly affect the swimming speed and efficiency of the underwater snake-like robot. These findings provide better understanding of how dual dorsal fins and the respective fin-fin interactions affect the swimming performance and can be used as guidelines for designing bioinspired underwater robots.

A biomimetic remora disc with tunable, reversible adhesion for surface sliding and skimming

Remora suckerfish (Echeneis naucrates) can perform skimming and sliding motions on the surfaces of moving hosts to optimize adhesion positions. We found that remora achieve skimming and sliding motions through coordinated movement of the suction disc’s lamellae and lip locomotion through live animal observations. We implemented an integrated biomimetic remora suction disc based on morphological and kinematic data of biological remoras. With soft actuators enabling ‘compression–rotation’ and ‘compression–extension’, the biomimetic disc controls the disc lip and lamellar movement under driving with only one degree of freedom, and can switch freely between three states: zero, low-friction, and robust adhesion. Then we investigate the effects of the biomimetic suction-disc soft-lip material, preload, and lamellar movement on the tangential friction force (both forward and backward) under different adhesion states. This biomimetic suction disc with a low-modulus soft lip can adhere to a smooth surface under 0.1 N preload and achieve normal adhesion-force and tangential frictional-force control ranges spanning ∼10−1 to ∼102 N and ∼10−1 to ∼101 N, respectively. The results reveal how remora disc achieved fast, tunable adhesion for skimming and sliding on surfaces. Furthermore, we demonstrate a bio-inspired robot capable of attachment, detachment, skimming, and sliding motions with the aiding of simple biomimetic pectoral-fin flapping. This study lays a foundation for future integrated applications of underwater adhesion robots and related biomechanical exploration.

Design, Modeling, and Visual Learning-Based Control of Soft Robotic Fish Driven by Super-Coiled Polymers.

A rapidly growing field of aquatic bio-inspired soft robotics takes advantage of the underwater animals’ bio-mechanisms, where its applications are foreseen in a vast domain such as underwater exploration, environmental monitoring, search and rescue, oil-spill detection, etc. Improved maneuverability and locomotion of such robots call for designs with higher level of biomimicry, reduced order of complex modeling due to continuum elastic dynamics, and challenging robust nonlinear controllers. This paper presents a novel design of a soft robotic fish actively actuated by a newly developed kind of artificial muscles—super-coiled polymers (SCP) and passively propelled by a caudal fin. Besides SCP exhibiting several advantages in terms of flexibility, cost and fabrication duration, this design benefits from the SCP’s significantly quicker recovery due to water-based cooling. The soft robotic fish is approximated as a 3-link representation and mathematically modeled from its geometric and dynamic perspectives to constitute the combined system dynamics of the SCP actuators and hydrodynamics of the fish, thus realizing two-dimensional fish-swimming motion. The nonlinear dynamic model of the SCP driven soft robotic fish, ignoring uncertainties and unmodeled dynamics, necessitates the development of robust/intelligent control which serves as the motivation to not only mimic the bio-mechanisms, but also mimic the cognitive abilities of a real fish. Therefore, a learning-based control design is proposed to meet the yaw control objective and study its performance in path following via various swimming patterns. The proposed learning-based control design employs the use of deep-deterministic policy gradient (DDPG) reinforcement learning algorithm to train the agent. To overcome the limitations of sensing the soft robotic fish’s states by designing complex embedded sensors, overhead image-based observations are generated and input to convolutional neural networks (CNNs) to deduce the curvature dynamics of the soft robot. A linear quadratic regulator (LQR) based multi-objective reward is proposed to reinforce the learning feedback of the agent during training. The DDPG-based control design is simulated and the corresponding results are presented.

Real-time parametric estimation of periodic wake-foil interactions using bioinspired pressure sensing and machine learning

Periodic wake-foil interactions occur in the collective swimming of bio-inspired robots. Wake interaction pattern estimation (and control) is crucial to thrust enhancement and propulsive efficiency optimization. In this paper, we study the wake interaction pattern estimation of two flapping foils in tandem configurations. The experiments are conducted at a Reynolds number of 1.41 × 104 in a water channel. A modified wake-foil phase parameter Φ, which unifies the influences of inter-foil distance L x , motion phase difference Δφ and wake convection velocity U v , is introduced to describe the wake interaction patterns parametrically. We use a differential pressure sensor on the downstream foil to capture wake interaction characteristics. Data sets at different tandem configurations are collected. The wake-foil phase Φ is used to label the pressure signals. A one-dimensional convolutional neural networks (1D-CNN) model is used to learn an end-to-end mapping between the raw pressure measurements and the wake-foil phase Φ. The trained 1D-CNN model shows accurate estimations (average error 3.5%) on random wake interaction patterns and is fast enough (within 40 ms). Then the trained 1D-CNN model is applied to online thrust enhancement control of a downstream foil swimming in a periodic wake. Synchronous force monitoring and flow visualization demonstrate the effectiveness of the 1D-CNN model. The limitations of the model are discussed. The proposed approach can be applied to the online estimation and control of wake interactions in the collective swimming and flying of biomimetic robots.

High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

Hydrodynamical Fingerprint of a Neighbour in a Fish Lateral Line.

For fish, swimming in group may be favorable to individuals. Several works reported that in a fish school, individuals sense and adjust their relative position to prevent collisions and maintain the group formation. Also, from a hydrodynamic perspective, relative-position and kinematic synchronisation between adjacent fish may considerably influence their swimming performance. Fish may sense the relative-position and tail-beat phase difference with their neighbors using both vision and the lateral-line system, however, when swimming in dark or turbid environments, visual information may become unavailable. To understand how lateral-line sensing can enable fish to judge the relative-position and phase-difference with their neighbors, in this study, based on a verified three-dimensional computational fluid dynamics approach, we simulated two fish swimming adjacently with various configurations. The lateral-line signal was obtained by sampling the surface hydrodynamic stress. The sensed signal was processed by Fast Fourier Transform (FFT), which is robust to turbulence and environmental flow. By examining the lateral-line pressure and shear-stress signals in the frequency domain, various states of the neighboring fish were parametrically identified. Our results reveal that the FFT-processed lateral-line signals in one fish may potentially reflect the relative-position, phase-differences, and the tail-beat frequency of its neighbor. Our results shed light on the fluid dynamical aspects of the lateral-line sensing mechanism used by fish. Furthermore, the presented approach based on FFT is especially suitable for applications in bioinspired swimming robotics. We provide suggestions for the design of artificial systems consisting of multiple stress sensors for robotic fish to improve their performance in collective operation.

The Need for and Feasibility of Alternative Ground Robots to Traverse Sandy and Rocky Extraterrestrial Terrain

Robotic spacecrafts have helped expand the reach for many planetary exploration missions. Most ground mobile planetary exploration robots use wheeled or modified wheeled platforms. Although extraordinarily successful at completing intended mission goals, because of the limitations of wheeled locomotion, they have been largely limited to benign, solid terrain and avoided extreme terrain with loose soil/sand and large rocks. Unfortunately, such challenging terrain is often scientifically interesting for planetary geology. Although many animals traverse such terrain at ease, robots have not matched their performance and robustness. This is in major part due to a lack of fundamental understanding of how effective locomotion can be generated from controlled interaction with complex terrain on the same level of flight aerodynamics and underwater vehicle hydrodynamics. Early fundamental understanding of legged and limbless locomotor–ground interaction has already enabled stable and efficient bioinspired robot locomotion on relatively flat ground with small obstacles. Recent progress in the new field of terradynamics of locomotor–terrain interaction begins to reveal the principles of bioinspired locomotion on loose soil/sand and over large obstacles. Multilegged and limbless platforms using terradynamics insights hold the promise for serving as robust alternative platforms for traversing extreme extraterrestrial terrain and expanding the reach in planetary exploration.

Design method of a single degree-of-freedom planar linkage bionic mechanism based on continuous position constraints

Single degree-of-freedom (DOF) planar linkage mechanism has been widely used in bio-inspired robots because of its simple control. However, designing a single DOF mechanism to meet the complex motion law of creatures is difficult, and the multiple variables of six- or eight-bar mechanism further increase the design difficulty. A design method of single DOF planar linkage bionic mechanism is proposed in this paper. Through the continuous constraints on the position of all reference points with constraint descent method, the requirements of the bionic mechanism in shape, motion trajectory, and posture are met. As for the mechanism by which reference point coordinates cannot be expressed as the analytical solution of the driving angle, a single DOF mechanism is equivalent to a double DOF mechanism containing additional optimization variables, which further improves the design efficiency. For example, the design process of six- and eight-bar bionic mechanisms is given, confirming the feasibility of the method. Then, the effects of the constraint conditions on the design process are analyzed in detail. This study provides a reference for the design of bio-inspired robots.

Undulatory Swimming Performance Explored With a Biorobotic Fish and Measured by Soft Sensors and Particle Image Velocimetry.

Due to the difficulty of manipulating muscle activation in live, freely swimming fish, a thorough examination of the body kinematics, propulsive performance, and muscle activity patterns in fish during undulatory swimming motion has not been conducted. We propose to use soft robotic model animals as experimental platforms to address biomechanics questions and acquire understanding into subcarangiform fish swimming behavior. We extend previous research on a bio-inspired soft robotic fish equipped with two pneumatic actuators and soft strain sensors to investigate swimming performance in undulation frequencies between 0.3 and 0.7 Hz and flow rates ranging from 0 to 20 in a recirculating flow tank. We demonstrate the potential of eutectic gallium–indium (eGaIn) sensors to measure the lateral deflection of a robotic fish in real time, a controller that is able to keep a constant undulatory amplitude in varying flow conditions, as well as using Particle Image Velocimetry (PIV) to characterizing swimming performance across a range of flow speeds and give a qualitative measurement of thrust force exerted by the physical platform without the need of externally attached force sensors. A detailed wake structure was then analyzed with Dynamic Mode Decomposition (DMD) to highlight different wave modes present in the robot’s swimming motion and provide insights into the efficiency of the robotic swimmer. In the future, we anticipate 3D-PIV with DMD serving as a global framework for comparing the performance of diverse bio-inspired swimming robots against a variety of swimming animals.

Axial force transmission in flexible bowtie dielectric elastomer actuators

A long strip of a pre-stretched dielectric elastomer actuator (DEA) is necessary for strain accumulation, but it relaxes laterally and thickens non-uniformly. As compared to a short strip under the same voltage activation, the long relaxed strip is subjected to a less electric field and, thus, undergoes less active strain. Here, we developed a flexible ladder frame to reinforce and divide the long DEA in a bowtie series. When being pulled, the ladder frame unbuckled; it, in turn, helped to pre-stretch tautly the DEA membrane. Interestingly, its flanges enhance force transmissions, acting like tensioning cables for a suspension bridge. Hence, the maximum isometric stress of this bowtie series was 24% higher than the short pure-shear one and 6.5 times the long uniaxial one. With 2.2 times enhanced dielectric strength across a taut DEA membrane, the bowtie series generated an isotonic strain 3.2 times that a long non-reinforced and relaxed DEA did. Hence, the reinforced DEAs can provide a more forceful drive for bio-inspired robots.

Curriculum-based reinforcement learning for path tracking in an underactuated nonholonomic system

Underactuated mechanical systems with nonholonomic constraints find applications in bioinspired robotics, such as snake-like robots and more recently in fish-like aquatic robots. Animal locomotion suggests that in such bioinspired robots, gaits or cyclic changes in kinematics or shape variables lead to efficient and agile motion. Path tracking in such nonholonomic systems that are not purely kinematic can be a challenging problem. In this paper we consider the problem of path tracking by a modified Chaplygin sleigh with a ‘tail’ which is a four degree of freedom nonholonomic system, possessing a single internal reaction wheel as an actuator. We develop a curriculum based deep Reinforcement Learning (RL) optimal control approach for simultaneous velocity and path tracking for this system. The curriculum based learning approach first leads to a policy for optimal tracking of limit cycles in a reduced velocity space and then in a next step to track a path. This curriculum approach allows an RL agent to learn the ’mechanics on invariant manifolds’ of the system and can be a useful approach in the motion control of high degree of freedom robots with increasing model complexity.

Bio-Inspired Ocean Exploration

Substantial efforts have been made to expand our knowledge of the physics, biology, chemistry, and geography of the ocean using state-of-the-art measurement tools. With new global projects and technological advances, the collaborative efforts of the Ocean Decade (2021–2030) are well on the way to revolutionizing our knowledge of ocean sciences and sustainability. Yet even today, over three-quarters of the seafloor is still unmapped, more than 90% of marine life still awaits discovery and classification, and the number of ocean sensors required to study global phenomena at sufficient temporal and spatial resolutions is seemingly intractable. To address this challenge, new approaches such as bio-inspired robotics can expand our existing toolbox and bridge this knowledge gap. The concept of biology-inspired engineering has emerged as a powerful tool to complement traditional engineering approaches to technology development. For example, specific swimming features of jellyfish and fish have been applied to a variety of fields, from vehicular propulsion to wind energy to medical diagnostics. In particular, jellyfish are advantageous model organisms because of their energy efficiency, with the lowest known cost of transport compared to other animals, as well as their ubiquity and survivability in various ocean environments. In this article we highlight the evolution of research into jellyfish-inspired robotic constructs and their potential applications in ocean exploration. After initial projects using entirely engineered materials (i.e., jellyfish-​inspired submarine propellers) and tissue engineering methods (i.e., rat cardiac cells seeded on flexible films), recent work to integrate microelectronic systems onto live jellyfish demonstrates that their swimming speeds can be increased (up to three times compared to their baselines) and their energy efficiency can be improved (up to four times compared to their baselines). This shows promise for the robotic control of jellyfish in real-world oceanic environments, where the animals are already distributed globally. Future work can improve the maneuverability of these bio-hybrid jellyfish robots, incorporate miniaturized sensors to profile regions of interest, and ultimately deploy swarms of these low-power, low-cost robots to obtain high-resolution data and improve ocean climate models. The synergy of bio-inspired technologies with existing ocean measurement tools holds promise to push the frontiers of ocean exploration and stewardship.

Underwater motion control of a bio-inspired father-son robot based on hydrodynamics analysis

Underwater motion control of a bio-inspired father-son robot based on hydrodynamics analysis

Underwater motion control of a bio-inspired father-son robot based on hydrodynamics analysis

Underwater motion control of a bio-inspired father-son robot based on hydrodynamics analysis

MECHANICAL DESIGN, ACTUATION AND CONTROL OF BIOINSPIRED SOFT SURGICAL ROBOTS

The design of surgical soft robots is one of the most challenging problems in modern robotics. In addition to the still pending problems of general soft robotics i.e. selection/design of materials, actuators, and mechanical structures, there are serious limitations in terms of their operating environment and conditions: interaction with biological tissues, the effect of sterilization and cleaning liquids, the shape and dimensions of the working space, as well as often occurring accidents during the surgery which poses new robotic control problems to be studied. As it is known, each object of bioinspiration (elephant trunk, octopus leg, etc.) has its own type of motion, kinematic structure, and control, therefore the comparative analysis of soft robots according to different objects of bioinspiration will facilitate their selection and application in minimally invasive surgery (MIS), taking into account, of course, the limitations associated with the surgery. A review of modern literature on mechanical design, methods and technical means of actuation and control of the main types of bioinspired soft surgical robots is presented.The design and development problems, including material selection, mechanical design and optimization, actuation, and bioinspired control for each type of the existing soft surgical robots are discussed. The results and recommendations of this study will help to develop new samples of soft surgical robotic devices with task-specific functional characteristics necessary for MIS applications.

Merging pruning and neuroevolution: towards robust and efficient controllers for modular soft robots

AbstractArtificial neural networks (ANNs) can be employed as controllers for robotic agents. Their structure is often complex, with many neurons and connections, especially when the robots have many sensors and actuators distributed across their bodies and/or when high expressive power is desirable. Pruning (removing neurons or connections) reduces the complexity of the ANN, thus increasing its energy efficiency, and has been reported to improve the generalization capability, in some cases. In addition, it is well-known that pruning in biological neural networks plays a fundamental role in the development of brains and their ability to learn. In this study, we consider the evolutionary optimization of neural controllers for the case study of Voxel-based soft robots, a kind of modular, bio-inspired soft robots, applying pruning during fitness evaluation. For a locomotion task, and for centralized as well as distributed controllers, we experimentally characterize the effect of different forms of pruning on after-pruning effectiveness, life-long effectiveness, adaptability to new terrains, and behavior. We find that incorporating some forms of pruning in neuroevolution leads to almost equally effective controllers as those evolved without pruning, with the benefit of higher robustness to pruning. We also observe occasional improvements in generalization ability.

Multiple Bio-Inspired Father-Son Underwater Robot for Underwater Target Object Acquisition and Identification.

Underwater target acquisition and identification performed by manipulators having broad application prospects and value in the field of marine development. Conventional manipulators are too heavy to be used for small target objects and unsuitable for shallow sea working. In this paper, a bio-inspired Father–Son Underwater Robot System (FURS) is designed for underwater target object image acquisition and identification. Our spherical underwater robot (SUR), as the father underwater robot of the FURS, has the ability of strong dynamic balance and good maneuverability, can realize approach the target area quickly, and then cruise and surround the target object. A coiling mechanism was installed on SUR for the recycling and release of the son underwater robot. A Salamandra-inspired son underwater robot is used as the manipulator of the FURS, which is connected to the spherical underwater robot by a tether. The son underwater robot has multiple degrees of freedom and realizes both swimming and walking movement modes. The son underwater robot can move to underwater target objects. The vision system is installed to enable the FURS to acquire the image information of the target object with the aid of the camera, and also to identify the target object. Finally, verification experiments are conducted in an indoor water tank and outdoor swimming pool conditions to verify the effectiveness of the proposed in this paper.

Об одной реализации стайного поведения в группе подводных роботов

This paper discusses underwater robotic networks from the standpoint of stealthy surveillance by means of bio-inspired drones. “Bio-inspired” means that various hardware, software and technology solutions implemented in a robot have biological basis and rely on the studies in ethology and morphology of living organisms. In underwater robotics, this approach makes it possible to develop the vehicles that resemble sea life in terms of appearance and behavior and therefore are harder to detect for both animal and human observer, which facilitates the tasks of water area surveillance and fauna research observations. This work is meant to develop and refine a number of basic collective behavior patterns for this kind of robots, which is necessary to make robots as similar to the sea life in their operation area as possible to reduce their chances of being detected. Basic behavior algorithms for robots were developed as per the findings of ichthyological and ethological studies and also relying on certain points of the automata theory. A number of functions for the lower-level control systems were developed through simulation. The experiments were mostly performed in Robotic Test Tank of the Kurchatov Institute on a real shoal of underwater robots developed under this project. The results of this study made it possible to develop one of the basic patterns in shoaling behavior of robots, i.e. schooling after a non-established leader whose position is disputed. In real environment, this pattern was tested on three fish-like underwater robots with two-level control system. Another output of the study is a short-range infrared communication system for limited data exchange between drones. Experimental validation of this system and the pattern of schooling after a non-established leader implemented at the top level of robot control system have confirmed the viability of suggested solutions. This mechanisms, as well as technical and technological solutions yielded by this work will become the basis for further efforts towards development of a bio-inspired underwater robot. The algorithm of schooling after a non-established leader plays a key role in further improvement of collective behavior patterns for drones, like shoaling.

Impact of Biologically Inspired Robotics on Business Performance

In the current times modern robotic technologies have the capability to enable robots to work and operate in not so developed and unstructured and dynamically changing work environments. Various sectors and in the business organisations employees and managers are now transforming their workplace from a more traditionally structured ambience to a more technologically advanced environment. This way, robots have become an integral part in making such progress in the business world. One important approach to build these types of intelligent and automated robotic technologies is to take inspiration from biological systems. It can be very convenient as biological mechanisms, structures, and other underlying principles have the ability to provide new ideas to assist the improvement of existing robotic control, design and operation systems. This paper analyses the importance of biologically inspired robotic technologies in the business world. In this research article both secondary qualitative and quantitative data has been collected and analysed to develop the study. The research study reveals that for improving the efficiency and productivity in the business performance the influences of these Bio-inspired robots is huge. Keywords : Bio-inspired robots, technology, global business, technological revolution, business performance

Bio-inspired robotics enabled schemes in blockchain-fog-cloud assisted IoMT environment

Due to emerging developments in sports games, the usage of bio-ankle sensors has been growing progressively. Whereas, Internet of Medical Things (IoMT) is an emerging network that boosts bio-inspired sensors’ performances onto the fog-cloud network. However, a sequence of processes is required to complete the healthcare process for one sportsman. Therefore, workflow-enabled bio-inspired sensors tasks scheduled in IoMT postures different challenges. For instance, cost-efficient scheduling, security, and data validation in distributed hospitals to share their data. In this paper, we devise bio-inspired robotics-enabled schemes in the blockchain-fog-cloud-assisted IoMT environment. The goal is to minimize execution cost and blockchain of applications. Based on the proposed system, the study devises bio-inspired robotics function blockchain task scheduling (BIR-FBTS) schemes, determining the optimal assignment of tasks to the available nodes. The simulation results show that the proposed methods minimized 50% of the service cost and 40% of mined cost in the system compared to all existing bio-inspired healthcare systems.