Bionic Control Research Articles

Hybrid bionic control system for prostheses: a review

The legs and hands are the most susceptible to loss and this is due to the fact that they are prominent external organs in the human body. With increasing disasters, accidents, wars and diseases the loss of limbs is increasing, making the individual restricted in freedom and movement and pursuing to find alternatives to improve the individual's life is extremely important. Modern bionic prostheses are the best alternatives to replace amputated ones to perform both aesthetic and functional tasks. On this basis and by analyzing the most common and used methods in prosthetics management as the electroencephalography (EEG), electromyography (EMG), and functional near- infrared spectroscopy (fNIRS) methods, knowing their advantages and disadvantages, comparing them and documenting their results from the outputs of literature and previous experimental studies, whether in individual use or hybrid use.In the light of these data, this article highlights the most common technologies and considers their superiority and insuperiority, which can be suitable for the formation of a hybrid bionic control system for prostheses or rehabilitation and restoration of lost functions. Based on the most important studies that have dealt with these technologies whereas individually or in their hybrid state. In addition, this article provides an encouraging outlook for those interested in scientific research to research, compare, identify and characterise superior hybrid systems related to exoskeletal control systems and in particular prostheses.

A Bionic Control Method for Human–Exoskeleton Coupling Based on CPG Model

Exoskeleton robots are functioning in contexts with more complicated motion control needs as a result of the technology and applications for these robots rapidly developing. This calls for novel control techniques to accommodate their employment in a range of real-world settings. This paper proposes a bionic control method for a human–exoskeleton coupling dynamic model based on the CPG model, utilizing a model on the dynamics of the human–exoskeleton interaction. The CPG network is established as an oscillator by two neurons inhibiting one another, which approximates the torques simulated in the inverse dynamic analysis as the input to the exoskeleton robot. The findings of the simulation assessment suggest that the bionic control strategy may improve the robot’s ability to move quickly and steadily, as well as better adapt to challenging environments.

Thermal Soaring and Control Surface Dynamics of an Eagle and the Hummingbird’s Flapping Flight Aerodynamics

Abstract: This review tends to shed light on the eagle’s aerodynamic attributes along with its inbuilt structural control surfaces that facilitate its high maneuverability. Apart from this, few aspects of the eagle’s wing morphing techniques, its aerofoil, and its aerodynamic stability are also being highlighted. The aim is to highlight the bio-mimicable traits of an eagle which can be incorporated into bionic UAVs. This work acts as a base for current and future works involving slotted wingtips and bionic control surfaces. The traits discussed are being used to design mechanical control surfaces and wingtips that resemble the eagle’s slotted wings and control surfaces. These works when combined with compliant mechanisms can help improve roll and yaw control of a UAV along with drag reduction. This review also highlights the aerodynamics of flapping; specifically of the hummingbird. From the hummingbird’s aerodynamics to its hovering techniques; all of its main features are being highlighted. These birds have demonstrated a wide range of aerodynamic traits which if mimicked to near perfection could pave the way for new-age drones. Maneuverability and enhanced aerodynamic optimality could be the outset of extreme sustainability measures with these birds paving the way with their evolutionary flight measures. Apart from their aerodynamic traits, a few aspects of their wing morphing techniques and their evolutionary hereditary traits are also being highlighted.

Robot Bionic Vision Technologies: A Review

The visual organ is important for animals to obtain information and understand the outside world; however, robots cannot do so without a visual system. At present, the vision technology of artificial intelligence has achieved automation and relatively simple intelligence; however, bionic vision equipment is not as dexterous and intelligent as the human eye. At present, robots can function as smartly as human beings; however, existing reviews of robot bionic vision are still limited. Robot bionic vision has been explored in view of humans and animals’ visual principles and motion characteristics. In this study, the development history of robot bionic vision equipment and related technologies are discussed, the most representative binocular bionic and multi-eye compound eye bionic vision technologies are selected, and the existing technologies are reviewed; their prospects are discussed from the perspective of visual bionic control. This comprehensive study will serve as the most up-to-date source of information regarding developments in the field of robot bionic vision technology.

Experimental and theorical investigation on energy dissipation capacity of the viscoelastic limb-like-structure devices

The bionics design method has been proverbially applied at vibration control field, and how to make bionic vibration control device possess excellent mechanical property and stable energy dissipation capacity is an important subject. In this paper, a bionic viscoelastic limb-like-structure (VE-LLS) device is proposed in conjunction with the viscoelastic (VE) damper and the limb-like-structure (LLS) device together, and the proposed device simultaneously possesses excellent mechanical propriety and energy dissipation capacity. Firstly, the mechanical property test of the VE-LLS device is conducted to investigate the effect of ambient temperature, excitation amplitude and frequency on its dynamic mechanical property and energy dissipation capacity. The energy dissipation contribution caused by the LLS joint friction for the VE-LLS device is discussed. Then, the energy dissipation model of the VE-LLS device is established by simultaneously considering the viscoelastic and friction factors, and the comparison result indicates that the established energy dissipation model can accurately describe the energy dissipation capacity of the VE-LLS device under different ambient temperature, exaction amplitude and frequency. Finally, to further promote the stability of energy dissipation capacity of the VE-LLS device at different temperature and frequency, an energy dissipation compensation strategy is proposed by increasing the energy dissipation of the LLS joint friction to compensate for the energy dissipation attenuation of the VE damper caused by high temperature and low frequency, and the results shows that the compensation strategy expresses excellent effect for the energy dissipation stability of the VE-LLS device.

TALBOT: A Track-Leg Transformable Robot.

This article introduces a tracked-leg transformable robot, TALBOT. The mechanical and electrical design, control method, and environment perception based on LiDAR are discussed. The original tracked-leg transformable structure allows the robot to switch between the tracked and legged mode to achieve all-terrain adaptation. In the tracked mode, TALBOT is controlled by the method of differential speed between the two tracked feet. In the legged mode, TALBOT is controlled based on a bionic control strategy of the central pattern generator to realize the generation and conversion of gait. In addition, the robot is equipped with a LiDAR, through sensor preprocessing and optimization of the slam mapping algorithm, so that the robot achieves a better mapping effect. We tested the robot’s motion performance and the slam mapping effect, including going straight and turning in tracked and legged modes and building a map in an indoor environment.

A TD-Learning Based Bionic Cerebellar Model Controller For Humanoid Robots

The cerebellum is a crucial component of the human body that plays a vital role in human walking. To design a robot gait controller by referring the working mechanism of the cerebellum is one of the hotspots in the bionic control field. This paper designs a bionic cerebellar motion control model to control the slope gait of a humanoid robot. The cerebellum model refers to the connection method between neurons in a human cerebellum, and expresses from a bionic perspective how the neurons in the cerebellum process external information and generate control commands during walking. Inspired by how human walking is learned, this model employs reinforcement learning in the learning process of the bionic cerebellar model. A corresponding simulation environment is also designed to train and test the cerebellar control model's effectiveness when regulating a robot's slope walking stability. The simulation experimental results demonstrate that the cerebellum model can achieve stable control of the walking motion of the humanoid robot after training, verifying its effectiveness, and laying a foundation for further realization of human-like artificial intelligence.

A Way of Bionic Control Based on EI, EMG, and FMG Signals.

Creating highly functional prosthetic, orthotic, and rehabilitation devices is a socially relevant scientific and engineering task. Currently, certain constraints hamper the development of such devices. The primary constraint is the lack of an intuitive and reliable control interface working between the organism and the actuator. The critical point in developing these devices and systems is determining the type and parameters of movements based on control signals recorded on an extremity. In the study, we investigate the simultaneous acquisition of electric impedance (EI), electromyography (EMG), and force myography (FMG) signals during basic wrist movements: grasping, flexion/extension, and rotation. For investigation, a laboratory instrumentation and software test setup were made for registering signals and collecting data. The analysis of the acquired signals revealed that the EI signals in conjunction with the analysis of EMG and FMG signals could potentially be highly informative in anthropomorphic control systems. The study results confirm that the comprehensive real-time analysis of EI, EMG, and FMG signals potentially allows implementing the method of anthropomorphic and proportional control with an acceptable delay.

Determination of the Geometric Parameters of Electrode Systems for Electrical Impedance Myography: A Preliminary Study.

The electrical impedance myography method is widely used in solving bionic control problems and consists of assessing the change in the electrical impedance magnitude during muscle contraction in real time. However, the choice of electrode systems sizes is not always properly considered when using the electrical impedance myography method in the existing approaches, which is important in terms of electrical impedance signal expressiveness and reproducibility. The article is devoted to the determination of acceptable sizes for the electrode systems for electrical impedance myography using the Pareto optimality assessment method and the electrical impedance signals formation model of the forearm area, taking into account the change in the electrophysical and geometric parameters of the skin and fat layer and muscle groups when performing actions with a hand. Numerical finite element simulation using anthropometric models of the forearm obtained by volunteers’ MRI 3D reconstructions was performed to determine a sufficient degree of the forearm anatomical features detailing in terms of the measured electrical impedance. For the mathematical description of electrical impedance relationships, a forearm two-layer model, represented by the skin-fat layer and muscles, was reasonably chosen, which adequately describes the change in electrical impedance when performing hand actions. Using this model, for the first time, an approach that can be used to determine the acceptable sizes of electrode systems for different parts of the body individually was proposed.

Conversion of Body Muscle Signal to Control a Gripper using Surface Electromyography

Measuring muscle activation via electric potential, referred to as electromyography (EMG), has traditionally been used for medical research and diagnosis of neuromuscular disorders. However, with the advent of powerful integrated circuits and micro-controllers, the EMG circuits and sensors can find their way into prosthetics, robotics and control systems. Surface electromyography and needle electromyography are two general methods of recording the electrical activities of muscle tissue. In this paper, surface electromyography is used to analyse the human arm muscle nerve signals and convert the obtained nerve signal into mechanical movement in a motor. This kind of bionic control module finds its greatest use in prosthetics. The surface detection of the nerve signals reduces the risk of operation on the amputated part of the patient and gives a proper control to the person in movement of the prosthetic arm/leg. The module has the advantage of being small and simple, and easily manageable when compared to the other available options. Further development in the module can lead to fully developed and human safe prosthetic limbs that are very much alike and do all the functions as the actual human limbs. Index Terms: Electromyography, Surface electromyography, Bio electrodes, Bionic Control, non-invasive technique, aphasia

Stochastic recruitment limited control of shape memory alloy based on Markov chain model

A new control method of Shape Memory Alloy (SMA) actuators based on stochastic recruitment is proposed. From the perspective of bionic control, the physiological basis of stochastic recruitment limited feedback control of artificial muscle is explained. The limited feedback control system of two-state cells and multi-state cells are established, and the limited feedback control law is deduced for these two kinds of systems. In the Simulink environment, two kinds of limited feedback control algorithms are simulated and compared, which verifies the feasibility of the algorithm. Aiming at the key problem of scaling coefficient in the system, the longitudinal and transverse comparative experiments are carried out to analyze the influence of the scaling coefficient on the system.

Aerodynamic Performance of a Passive Pitching Model on Bionic Flapping Wing Micro Air Vehicles.

Reducing weight and increasing lift have been an important goal of using flapping wing micro air vehicles (FWMAVs). However, FWMAVs with mechanisms to limit the angle of attack (α) artificially by active force cannot meet specific requirements. This study applies a bioinspired model that passively imitates insects' pitching wings to resolve this problem. In this bionic passive pitching model, the wing root is equivalent to a torsional spring. α obtained by solving the coupled dynamic equation is similar to that of insects and exhibits a unique characteristic with two oscillated peaks during the middle of the upstroke/downstroke under the interaction of aerodynamic, torsional, and inertial moments. Excess rigidity or flexibility deteriorates the aerodynamic force and efficiency of the passive pitching wing. With appropriate torsional stiffness, passive pitching can maintain a high efficiency while enhancing the average lift by 10% than active pitching. This observation corresponds to a clear enhancement in instantaneous force and a more concentrated leading edge vortex. This phenomenon can be attributed to a vorticity moment whose component in the lift direction grows at a rapid speed. A novel bionic control strategy of this model is also proposed. Similar to the rest angle in insects, the rest angle of the model is adjusted to generate a yaw moment around the wing root without losing lift, which can assist to change the attitude and trajectory of a FWMAV during flight. These findings may guide us to deal with various conditions and requirements of FWMAV designs and applications.

Bionic control of exoskeleton robot based on motion intention for rehabilitation training

ABSTRACTAs the complexity of obtaining irregular daily motion trajectory during upper limb rehabilitation training, this paper proposes the bionic control method for the presented exoskeleton robot arm based on motion intention. Firstly, the collected motion signal is pre-processing by filtering. Then the motion intention and motion mode of the processed signal are classified by using the hierarchical multi-classification support vector machine. Meanwhile, the adaptive Hopf oscillator network based on dynamic learning is used for offline learning of joint motion trajectory, and the parameters of the reproduced signal in different motion modes are obtained. Finally, the corresponding parameters are transferred according to the user’s intention, and the oscillator network is reconstructed to realize the periodic motion control of rehabilitation training. With experimental verification, the proposed method can follow the human body’s motion intention and reproduce the daily motion trajectory of the upper limb. The results show it can be used to conduct rehabilitation training for the patient.

Design and Research of a Multi-functional Robot Arm for Automatically Grabbing Fans

This program solves the problems of manpower demand and low efficiency in the manufacturing process of ready-to-eat fan blocks by designing the three processes of ready-to-eat fan blocks, namely, grasping, weighing and forming problems. First of all, for the fans’ crawling problem, this product will be designed and solved from two aspects: 1. Visual recognition: In this design scheme, the visual recognition uses OpenMV3 system, and the OV7725 model camera is used first. The free integrated development environment (IDE) is used to debug the program. The SIFT algorithm is used to achieve visual target positioning and accurately identify the position of the fans to facilitate the grasping of the robot arm. 2. Path control of the manipulator: Through the RBF neural network algorithm, a large amount of training is performed on the manipulator, and the robot arm path is automatically controlled to realize the process of grabbing the fan and putting it into the fixed container. Secondly, in response to the weighing problem of fans, this product will incorporate a gravity sensor to realize the gravity sensing of the robot arm to capture fans, and convert the quality of the fans into digital signals for system processing and analysis. The use of constant temperature town empty warehouse not only ensures the quality and safety of fans, but also maintains the precision of each weighing quality. Finally, the robotic claws of the robot arm are used to control the rotation of the robot by multiple bionic control.

The fabrication of optical and magnetic responsive deforming multilayered film

ABSTRACTOptical and magnetic responsive deforming multilayered films with rapid deforming recovery property were successfully fabricated by electrospinning technology. Polyvinyl alcohol (PVA)/liquid crystal (LC) 5CB (4‐cyano‐4'pentylbiphenyl)/graphite fiber film was orderly collected on the thermoplastic polyurethanes (TPU) substrate film by parallel electrode electrospinning method. Graphite and nano‐magnetic particles had been added to endue it with optical and magnetic responsibility. Evaluated by a customized 3D‐printed platform, the deforming multilayered film shows its high deforming recovery speed. Therefore, the proposed deforming multilayered films can be applied in the field of bionic control with the advantage of rapid optical and magnetic responsibility, nontoxicity, and simple fabrication approach. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018, 135, 46884.

Robust control method for bionic gait of machine legs based on time delay feedback

The bionic machine leg is disturbed by the joint during the walking process, which is easy to produce time delay, which causes the robustness of the control of the machine leg is not good. In order to improve the robustness of the bionic gait control of the machine leg, a robust control method for the bionic gait of the machine leg based on time - delay feedback is proposed. The gait correlation parameters of robot leg are collected by sensor array, and the dynamic model of bionic gait is constructed. The fuzzy controller of bionic gait of robot leg is constructed by using time-delay coupling control method. The delayed feedback control error compensation method of machine leg correction is taken to improve the steady control performance of the robotic leg, reduce the steady-state error, improve the robustness of the control machine leg. The simulation results show that this method is robust to the bionic gait control of the machine leg. The output error of the gait parameter can quickly converge to zero, and the accurate estimation of the attitude parameter is stronger.

Indirect adaptive type-2 bionic fuzzy control

In this study, an indirect adaptive type-2 bionic fuzzy control method is proposed for a class of nonlinear systems. By regarding the niche of each species in an ecosystem as the antecedent, the fuzzy system with biological characteristics is constructed based on the niche “ecostate-ecorole” theory. In the actual system, we design a fuzzy control system using a type-2 bionic fuzzy system and provide both the adaptive law and constraint conditions of the system parameters. The stability of the closed-loop system is proved with all the state variables uniformly bounded in the Lyapunov sense. Additionally, the convergence of the bionic fuzzy control system is analyzed. Finally, the simulation results obtained for a permanent magnet direct current motor demonstrate the effectiveness and superiority of the designed method.

Hybrid Adaptive Bionic Fuzzy Control Method

The bionic fuzzy system embeds the biologically active adaptive strategy into the traditional T-S fuzzy system, which increases the active adaptability. On the basis of the researches, an identification model is added to the system, and a hybrid bionic adaptive fuzzy control method is proposed in this paper, which makes the system have biological adaptability and strong anti-interference ability. The adaptive law contains two items: the first one is the general term for adjusting system parameters by using the current state and the second one is a compensation item for the adjustment of system parameters based on the development trend. Lyapunov synthesis method is used to analyze the stability and convergence of system. The design method of fuzzy controller, adaptive laws, and parameter constraints are given. Finally, the effectiveness of the method is verified by simulation of inverted pendulum model.

Bionic control scheme based on muscle–tendon unit for electrohydraulic cylinder

Bionics researchers identify muscle–tendon unit to be effective in producing human-like walking, but seldom real actuators have same property like muscle–tendon unit. Here, a muscle–tendon control scheme for electrohydraulic cylinder is proposed. To achieve this goal, we develop a model of electrohydraulic cylinder to clarify the relationship between the input current and output force. Additionally, a controller based on muscle–tendon unit model is applied to realize compliant control. The results of muscle–tendon unit control scheme and conventional force–position control scheme are compared. By applying the proposed one, we find that the electrohydraulic cylinder generates compliant behavior and self-adapts to load disturbances, without scarifying its fast response property and stiffness. Besides, various compliances can be accomplished by simply changing maximum muscle–tendon unit force. The results suggest that hydraulic actuators with this bionic control scheme can meet the demand of robot applications, especially for legged robots and manipulators.

Skinner operant conditioning model and robot bionic self-learning control

Skinner operant conditioning model and robot bionic self-learning control