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The purpose of this paper is to review recent progress in electronic nose technologies, focusing on hybrid systems combining biological elements with physical transducers.

Electronic nose technologies are moving rapidly towards hybrid bioelectronic systems, where biological odour-recognition elements from the olfactory pathways of vertebrates and insects are being utilised to construct new “bionic noses” that can be used in industrial applications.

With the increased understanding of how chemical senses and the brain function in biology, an emerging field of “neuromorphic olfaction” has arisen.

Important components are olfactory receptor proteins and soluble proteins found at the periphery of olfaction called odorant-binding proteins. The idea is that these proteins can be incorporated into transducers and function as biorecognition elements for volatile compounds of interest.

Major drivers are the security, environmental and medical applications, and the internet of things will be a major factor in implementing low-cost chemical sensing in networked applications for the future.

Widespread take up of new technologies that are cheap will minimise the impact of environmental pollution, increase food safety and may potentially help in non-invasive screening for medical ailments.

This review brings together diverse threads of research leading to a common theme that will inform a non-expert of recent developments in the field.

The purpose of this paper is to understand the effect of airflow dynamics on vortices for different flow rates using the human nose three-dimensional model.

Olfaction originates with air particles travelling from an external environment to the upper segment of the human nose. This phenomenon is generally understood by using the nasal airflow dynamics, which enhances the olfaction by creating the vortices in the human nose. An anatomical three-dimensional model of the human nasal cavity from computed tomography (CT) scan images using the MIMICS software (Materialise, USA) was developed in this study. Grid independence test was performed through volume flow rate, pressure drop from nostrils and septum and average velocity near the nasal valve region using a four computational mesh model. Computational fluid dynamics (CFD) was used to examine the flow pattern and influence of airflow dynamics on vortices in the nasal cavity. Numerical simulations were conducted for the flow rates of 7.5, 10, 15 and 20 L/min using numerical finite volume methods.

At coronal cross-sections, dissimilar nasal airflow patterns were observed for 7.5, 10, 15 and 20 L/min rate of fluid flow in the human nasal cavity. Vortices that are found at the boundaries with minimum velocity creates deceleration zone in the nose vestibule region, which is accompanied by flow segregation. Maximum vortices were observed in the nasal valve region and the posterior end of the turbinate region, which involves mixing and recirculation and is responsible for enhancing the smelling process.

The proposed analysis is applicable to design the sensor chamber for electronic noses.

In this paper, the influence of airflow dynamics on vortices in the human nasal cavity is discussed through numerical simulations.

The purpose of this paper is to design and validate an electronic nose (E-nose) prototype using commercially available metal oxide gas sensors (MOX). This prototype has a sensor array board that integrates eight different MOX gas sensors to handle multi-purpose applications. The number of sensors can be adapted to match different requirements and classification cases. The paper presents the validation of this E-nose prototype when used to identify three gas samples, namely, alcohol, butane and cigarette smoke. At the same time, it discusses the discriminative abilities of the prototype for the identification of alcohol, acetone and a mixture of them. In this respect, the selection of the appropriate type and number of gas sensors, as well as obtaining excellent discriminative abilities with a miniaturized design and minimal computation time, are all drivers for such implementation.

The suggested prototype contains two main parts: hardware (low-cost components) and software (Machine Learning). An interconnection printed circuit board, a Raspberry Pi and a sensor chamber with the sensor array board make up the first part. Eight sensors were put to the test to see how effective and feasible they were for the classification task at hand, and then the bare minimum of sensors was chosen. The second part consists of machine learning algorithms designed to ensure data acquisition and processing. These algorithms include feature extraction, dimensionality reduction and classification. To perform the classification task, two features taken from the sensors’ transient response were used.

Results reveal that the system presents high discriminative ability. The K-nearest neighbor (KNN) and support vector machine radial basis function based (SVM-RBF) classifiers both achieved 97.81% and 98.44% mean accuracy, respectively. These results were obtained after data dimensionality reduction using linear discriminant analysis, which is more effective in terms of discrimination power than principal component analysis. A repeated stratified K-cross validation was used to train and test five different machine learning classifiers. The classifiers were each tested on sets of data to determine their accuracy. The SVM-RBF model had high, stable and consistent accuracy over many repeats and different data splits. The total execution time for detection and identification is about 10 s.

Using information extracted from transient response of the sensors, the system proved to be able to accurately classify the gas types only in three out of the eight MQ-X gas sensors. The training and validation results of the SVM-RBF classifier show a good bias-variance trade-off. This proves that the two transient features are sufficiently efficient for this classification purpose. Moreover, all data processing tasks are performed by the Raspberry Pi, which shows real-time data processing with miniaturized architecture and low prices.

The paper aims to present a dynamic model of flexible oscillating pectoral fin for further study on its propulsion mechanism.

The chordwise and spanwise motions of cow-nosed ray’s pectoral fin are first analyzed based on the mechanism of active/passive flexible deformation. The kinematic model of oscillating pectoral fin is established by introducing the flexible deformation. Then, the dynamic model of the oscillating pectoral fin is developed based on the quasi-steady blade element theory. A series of hydrodynamic experiments on the oscillating pectoral fin are carried out to investigate the influences of motion parameters on the propulsion performance of the oscillating pectoral fin.

The experimental results are consistent with that obtained through analytical calculation within a certain range, which indicates that the developed dynamic model in this paper is applicable to describe the dynamic characteristics of the oscillating pectoral fin approximately. The experimental results show that the average thrust of an oscillating pectoral fin increases with the increasing oscillating amplitude and frequency. However, the relationship between the average thrust and the oscillating frequency is nonlinear. Moreover, the experimental results show that there is an optimal phase difference at which the oscillating pectoral fin achieves the maximum average thrust.

The developed dynamic model provides the theoretical basis for further research on propulsion mechanism of oscillating pectoral fins. It can also be used in the design of the bionic pectoral fins.

Cochlear's first product, the 22-channel Nucleus implant, was the result of a research programme that has been dated back to 1967, when Graeme Clark, an ear, nose and throat (ENT) surgeon, commenced doctoral work on the electrical stimulation of the hearing nerve. Following the completion of his PhD in 1969, Clark was appointed the inaugural Chair in Otolaryngology at the University of Melbourne. When he joined the university in 1970, his primary objective was the practical application of his PhD research: namely, the development of a ‘bionic ear’, an electronic device that would stimulate the hearing nerve in the profoundly deaf. He realised early on that lack of resources would be one of his major impediments:across the road [from my office] the experimental research laboratory was in a disused hospital mortuary. When I looked at the mortuary my heart sank. It was dilapidated and bare. There was a stone table in the centre, but little else. The walls needed painting, and the light diffused poorly through the high windows. Anyway, I had no money to buy equipment even if the laboratory itself were satisfactory. (Clark, 2000, p. 54)

This study aims to establish a bio-inspired controller for realizing the bounding gait of a quadruped robot system presented in this paper.

The bio-inspired controller is divided into three levels to mimic the biological patterns of animals. First, the high-level sub-controller is equivalent to the cerebellum, which could plan and control the motion of animals. Second, the effect of the middle-level sub-controller corresponds to the central nervous system. The central pattern generators in the spine generate the stable and cyclic signals as the fundamental rhythm for periodic motion of the leg and spine joints. Third, the low-level sub-controller is equal to the end effector, which adopts the simple proportional-derivative (PD) control to realize the specific motion trajectory of the legs and spine.

Combined with the stability criterion presented previously and the delayed feedback control method, the bounding gait of the cheetah virtual prototype could be actuated and stabilized by the bio-inspired controller. Moreover, the bio-inspired controller is applied to realize the bounding gait of an SQBot, which is a quadruped robot with a spine joint. Meanwhile, the validity and practicability of the bio-inspired controller for the control of quadruped robot have been verified against different forward velocities.

The bio-inspired controller and bionic quadruped robot system are instructive for the designing and actuating of the real quadruped robot.

In large equipment and highly complex confined workspaces, the maintenance is usually carried out by snake-arm robots with equal cross-sections. However, the equal cross-sectional design results in the snake arm suffering from stress concentration and restricted working space. The purpose of this paper is to design a variable cross-section elephant trunk robot (ETR) that can address these shortcomings through bionic principles.

This paper proposes a cable-driven ETR to explore the advantages and inspiration of variable cross-section features for hyper-redundant robot design. For the kinematic characteristics, the influence of the variable cross-section design on the maximum joint angle of the ETR is analysed using the control variables method and the structural parameters are selected. Based on the biological inspiration of the whole elephant trunk following the movement of the trunk tip, a trajectory-tracking algorithm is designed to solve the inverse kinematics of the ETR.

Simulation and test results show the unique advantages of the proposed variable cross-section ETR in kinematics and forces, which can reduce stress concentrations and increase the flexibility of movement.

This paper presents a design method for a variable cross-section ETR for confined working spaces, analyses the kinematic characteristics and develops a targeted trajectory control algorithm.

This paper aims to develop a robofish with oscillating pectoral fins, and control it to mimic the bionic prototype by central pattern generators (CPGs).

First, the oscillation characteristics of the cownose ray were analyzed quantitatively. Second, a robofish with multi-joint pectoral fins was developed according to the bionic morphology and kinematics. Third, the improved phase oscillator was established, which contains a spatial asymmetric coefficient and a temporal asymmetric coefficient. Moreover, the CPG network is created to mimic the cownose ray and accomplish three-dimensional (3D) motions. Finally, the experiments were done to test the authors ' works.

The results demonstrate that the CPGs is effective to control the robofish to imitate the cownose ray realistically. In addition, the robofish is able to accomplish 3D motions of high maneuverability, and change among different swimming modes quickly and smoothly.

The research provides the method to develop a robofish from both 3D morphology and kinematics. The motion analysis and CPG control make sure that the robofish has the features of high maneuverability and camouflage. It is useful for military underwater applications and underwater detections in narrow environments. Second, this work lays the foundation for the autonomous 3D control. Moreover, the robotic fish can be taken as a scientific tool for the fluid bionics research.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.