Control strategy of central pattern generator gait movement under condition of attention selection

As a typical rhythmic movement, human being＇s rhythmic gait movement can be generated by a central pattern generator （CPG） located in a spinal cord by self- oscillation. Some kinds of gait movements are caused by gait frequency and amplitude variances. As an important property of human being＇s motion vision, the attention selection mechanism plays a vital part in the regulation of gait movement. In this paper, the CPG model is amended under the condition of attention selection on the theoretical basis of Matsuoka neural oscillators. Regulation of attention selection signal for the CPG model parameters and structure is studied, which consequentially causes the frequency and amplitude changes of gait movement output. Further, the control strategy of the CPG model gait movement under the condition of attention selection is discussed, showing that the attention selection model can regulate the output model of CPG gait movement in three different ways. The realization of regulation on the gait movement frequency and amplitude shows a variety of regulation on the CPG gait movement made by attention selection and enriches the controllability of CPG gait movement, which demonstrates potential influence in engineering applications.

Monoaminergic and catecholaminergic activation of the central pattern generator for locomotion following spinal cord injury Innovative therapeutic approaches

The development of secondary health complications following spinal cord injury has been increasingly recognized by healthcare professionals as a major concern. These problems most specifically affect complete or near-complete spinal cord injury patients （e.g., those with minimal mobility）, who are not typically rehabilitated with treadmill training approaches, because motor control and leg movements are largely impaired. However, recent pharmaceutical advances in central pattern generator activation may provide new therapeutic hopes for these spinal cord injury patients. This article provides a comprehensive overview, for the non-specialist, of the most recent advances in this field.

Arm motion control model based on central pattern generator

According to the theory of Matsuoka neural oscillators and with the con- sideration of the fact that the human upper arm mainly consists of six muscles, a new kind of central pattern generator （CPG） neural network consisting of six neurons is pro- posed to regulate the contraction of the upper arm muscles. To verify effectiveness of the proposed CPG network, an arm motion control model based on the CPG is established. By adjusting the CPG parameters, we obtain the neural responses of the network, the angles of joint and hand of the model with MATLAB. The simulation results agree with the results of crank rotation experiments designed by Ohta et al., showing that the arm motion control model based on a CPG network is reasonable and effective.

Study on dynamics of central pattern generator for a quadrupedal robot

Based on Matsuoka＇s central pattern generator （CPG） model and taking quadruped as an example, the dynamics of CPG model was investigated through the single-parameter-analysis method and the numerical simulation technique. Simulation results indicate that the CPG model exhibits complex dynamics, while each parameter has specifically definitive influence trends on the CPG output. These conclusions were applied to control a quadrupedal robot to walk in different gaits, clear obstacle, and walk up- and down-slope successfully.

Real-time generation of circular patterns in electron beam lithography

Electron beam lithography(EBL)involves the transfer of a pattern onto the surface of a substrate byfirst scanning a thin layer of organicfilm(called resist)on the surface by a tightly focused and precisely controlled electron beam(exposure)and then selectively removing the exposed or nonexposed regions of the resist in a solvent(developing).It is widely used for fabrication of integrated cir-cuits,mask manufacturing,photoelectric device processing,and otherfields.The key to drawing circular patterns by EBL is the graphics production and control.In an EBL system,an embedded processor calculates and generates the trajectory coordinates for movement of the electron beam,and outputs the corresponding voltage signal through a digital-to-analog converter(DAC)to control a deflector that changes the position of the electron beam.Through this procedure,it is possible to guarantee the accuracy and real-time con-trol of electron beam scanning deflection.Existing EBL systems mostly use the method of polygonal approximation to expose circles.A circle is divided into several polygons,and the smaller the segmentation,the higher is the precision of the splicing circle.However,owing to the need to generate and scan each polygon separately,an increase in the number of segments will lead to a decrease in the overall lithography speed.In this paper,based on Bresenham’s circle algorithm and exploiting the capabilities of afield-programmable gate array and DAC,an improved real-time circle-producing algorithm is designed for EBL.The algorithm can directly generate cir-cular graphics coordinates such as those for a single circle,solid circle,solid ring,or concentric ring,and is able to effectively realizes deflection and scanning of the electron beam for circular graphics lithography.Compared with the polygonal approximation method,the improved algorithm exhibits improved precision and speed.At the same time,the point generation strategy is optimized to solve the blank pixel and pseudo-pixel problems that arise with Bresenham’s circle algorithm.A complete electron beam deflection system is established to carry out lithography experiments,the results of which show that the error between the exposure results and the preset pat-terns is at the nanometer level,indicating that the improved algorithm meets the requirements for real-time control and high precision of EBL.

Simulation Platform for the Underwater Snake-Like Robot Swimming Based on Kane's Dynamic Model and Central Pattern Generator

A systematic method for swimming control of the underwater snake-like robot is still lacking. We construct a simulation platform of the underwater snake-like robot swimming based on Kane's dynamic model and central pattern generator(CPG). The partial velocity is deduced. The forces which contribute to dynamics are determined by Kane's approach. Hydrodynamic coefficients are determined by experiments. Then, we design a CPG-based control architecture implemented as the system of coupled nonlinear oscillators. The CPG, like its biological counterpart, can produce coordinated patterns of rhythmic activity while being modulated by simple control parameters. The relations between the CPG parameters and the speed of the underwater snake-like robot swimming are investigated. Swimming in a straight line, turning, and switching between swimming modes are implemented in our simulation platform to prove the feasibility of the proposed simulation platform. The results show that the simulation platform can imitate different swimming modes of the underwater snake-like robot.

Central Pattern Generator Based Gait Control for Planar Quadruped Robots

In this paper, a gait control scheme is presented for planar quadruped robots based on a biologic concept, namely central pattern generator(CPG). A CPG is modeled as a group of the coupled nonlinear oscillators with an interaction weighting matrix which determines the gait patterns. The CPG model, mapping functions and a proportional-diffierential(PD) joint controller compose the basic gait generator. By using the duty factor of gait patterns as a tonic signal, the activity of the CPG model can be modulated, and as a result, a smooth transition between diffierent gait patterns is achieved. Moreover, by tuning the parameters of the CPG model and mapping functions, the proposed basic gait generator can realize adaptive workspace trajectories for the robot to suit diffierent terrains. Simulation results illustrate and validate the effiectiveness of the proposed gait controllers.

Relationship between the brain and the central pattern generator based on recurrent neural network

In animals,the command centers in the brain can drive the locomotion.However,it remains unclear how the brain modulates the locomotor central pattern generator(CPG).In this paper,a novel model is established to describe the relation between the brain and the CPG with time delay.The artificial recurrent neural network(RNN)consists of various computational modules that are used to model the brain.The brain synchronization under amplitude and frequency variations of the CPG and the effect of the RNN parameters variations on the CPG are investigated.In the paper,the excitatory neuron probability and average connections number are parameter space of RNN and the parameter space of CPG,which include frequency and amplitude.According to the simulation results,the best RNN synchronization could be obtained by finding the optimum parameters space between the RNN and the CPG.I propose that the parameter space of some CPGs is related to the parameter space of the brain.This leads to a brain load decrement that facilities the control action.The results are meaningful to investigate how to study the relationship between the brain and the locomotion.

Central pattern generation underlying Limulus rhythmic behavior patterns

Many behavioral activities of the horseshoe crab Limulus are rhythmic, and most of these are produced in large part by central pattern generators within the CNS. The chain of opisthosomal （‘abdominal＇） ganglia controls gill movements of ventilation and gill cleaning, and the prosomal ring of fused ganglia （brain and segmental ‘thoracic＇ ganglia） controls generation of feeding and locomotor movements of the legs. Both the opisthosomal CNS and the prosomal CNS can generate behaviorally ap- propriate patterns of motor output in isolation, without movements or sensory input. Preparations of the isolated opisthosomal CNS generate rhythmic output patterns of motor activity characterized as fictive ventilatory and gill cleaning rhythms. Moreover, CNS preparations also express longer-term patterns, such as intermittent ventilation or sequential bouts of ventilation and gill cleaning. Such longer-term patterns are commonly observed in intact animals. The isolated prosomal CNS does not spontaneously generate the activity patterns characteristic of walking, swimming, and feeding. However, perfusion of octopamine in the isolated prosomal CNS activates central pattern generators underlying rhythmic chewing movements, and injection of octopamine into in- tact Limulus promotes the chewing pattern of feeding, whether or not food is presented. Our understanding of the ability of neu-romodulators such as octopamine to elicit or alter central motor programs may help to clarify the central neural circuits of pattern generation that oroduce and coordinate these rhythmic behaviors

Chx10+V2a interneurons in spinal motor regulation and spinal cord injury

Chx10-expressing V2 a(Chx10+V2 a) spinal interneurons play a large role in the excitatory drive of motoneurons. Chemogenetic ablation studies have demonstrated the essential nature of Chx10+V2 a interneurons in the regulation of locomotor initiation, maintenance, alternation, speed, and rhythmicity. The role of Chx10+V2 a interneurons in locomotion and autonomic nervous system regulation is thought to be robust, but their precise role in spinal motor regulation and spinal cord injury have not been fully explored. The present paper reviews the origin, characteristics, and functional roles of Chx10+V2 a interneurons with an emphasis on their involvement in the pathogenesis of spinal cord injury. The diverse functional properties of these cells have only been substantiated by and are due in large part to their integration in a variety of diverse spinal circuits. Chx10+V2 a interneurons play an integral role in conferring locomotion, which integrates various corticospinal, mechanosensory, and interneuron pathways. Moreover, accumulating evidence suggests that Chx10+V2 a interneurons also play an important role in rhythmic patterning maintenance, leftright alternation of central pattern generation, and locomotor pattern generation in higher order mammals, likely conferring complex locomotion. Consequently, the latest research has focused on postinjury transplantation and noninvasive stimulation of Chx10+V2 a interneurons as a therapeutic strategy, particularly in spinal cord injury. Finally, we review the latest preclinical study advances in laboratory derivation and stimulation/transplantation of these cells as a strategy for the treatment of spinal cord injury. The evidence supports that the Chx10+V2 a interneurons act as a new therapeutic target for spinal cord injury. Future optimization strategies should focus on the viability, maturity, and functional integration of Chx10+V2 a interneurons transplanted in spinal cord injury foci.

Adaptive Swimming of Underwater Snake-like Robot in Different Underwater Environment

Hydrodynamic force is an important factor that affects the performance of underwater vehicle.Adapting to the current underwater environment by changing its shape is an important feature of underwater snake-like robots(USLR).An experiment was implemented to verify the swimming along the straight line of USLR.A simulation platform is also established for the analysis of the swimming of USLR.To figure out adaptive swimming of USLR to different underwater environments,the relationships between CPG parameters and maximum swimming speed have been discussed,and the switching between different swimming modes has been implemented.

Design of a novel modular self-reconfigurable robot capable of self-turning

To solve the problem of inaccurate angle adjustment in the self-assembly process, a new homogenous hybrid modular self-reconfigurable robot-Xmobot is designed. Each module has four rotary joints and a self-turning mechanism. With the proposed self-turning mechanism, the angle adjusting accuracy of the module is increased to 2°, and the relative position adjusting efficiency of the module in the self-assembly process is also improved. The measured maximum moving distance of the proposed module in a gait cycle is 11.0 cm. Aiming at the multiple degree of freedom （MDOF） feature of the proposed module, a motion controller based on the central pattern generator （CPG） is proposed. The control of five joints of the module only requires two CPG oscillators. The CPG-based motion controller has three basic output modes, i. e. the oscillation, the rotation, and the fixed modes. The serpentine and the wheeled movements of the H-shaped robot are simulated, respectively. The results show that the average velocities of the two movements are 15. 2 and 20. 1 m/min, respectively. The proposed CPG-based motion controller is evaluated to be effective.

Adaptive Walking of a Quadrupedal Robot Based on Layered Biological Reflexes

A multiple-legged robot is traditionally controlled by using its dynamic model.But the dynamic-model-based approach fails to acquire satisfactory performances when the robot faces rough terrains and unknown environments.Referring animals＇ neural control mechanisms,a control model is built for a quadruped robot walking adaptively.The basic rhythmic motion of the robot is controlled by a well-designed rhythmic motion controller（RMC） comprising a central pattern generator（CPG） for hip joints and a rhythmic coupler（RC） for knee joints.CPG and RC have relationships of motion-mapping and rhythmic couple.Multiple sensory-motor models,abstracted from the neural reflexes of a cat,are employed.These reflex models are organized and thus interact with the CPG in three layers,to meet different requirements of complexity and response time to the tasks.On the basis of the RMC and layered biological reflexes,a quadruped robot is constructed,which can clear obstacles and walk uphill and downhill autonomously,and make a turn voluntarily in uncertain environments,interacting with the environment in a way similar to that of an animal.The paper provides a biologically inspired architecture,with which a robot can walk adaptively in uncertain environments in a simple and effective way,and achieve better performances.

Design and Analysis of Gecko-like Robot

Gecko-like robot（Geckobot）,an important branch of bionic robotics,is a robot that simulates gecko＇s capacity to climb walls and ceilings.The work environment of the traditional wall-climbing robot is greatly limited as the moving structure and adsorption principle of the robot have nothing to do with the real gecko.However,the adsorption principle and moving mode of the real gecko can provide a new way to break through the restrictions of the traditional wall-climbing robot.Inspired by the moving mechanism of geckos, this paper develops the Geckobot with motile body.Two types of Geckobots are addressed：one with compliant flat bar as the body,and the other with prismatic joint as the body.The compliant body not only resembles the moving mode of the real gecko body,but also simplifies the Geckobot＇s structure.The prismatic joint body is used to adapt the change of body length in ground-to-wall transition. The gait planning on the plane and the transition between perpendicular intersectional planes is discussed,with an emphasis on the analysis of the kinematics degree of freedom（DOF） and body posture.Central pattern generator（CPG） neural network is realized in LabVIEW and utilized to control Geckobot＇s movement.The CPG scheme in Lab VIEW is given,and how CPG is used to control Geckobot to turn or move forward is explored.Simulations are conducted in ADAMS to verify the feasibility of the structure design and gait planning and to acquire some parameters for practical Geckobot development.The experiment with Geckobot-Ⅰand Geckobot-Ⅱon their crawling capacity on the plane and the ground-to-wall transition finds that the robot can complete the crawling movement and ground-to-wall transition,verifying the feasibility of the structure design,gait planning and the CPG motion control.The Geckobot structure design approach,gait planning and the CPG motion control presented would be useful for the research on wall-climbing robots.

Semaphorin7A:its role in the control of serotonergic circuits and functional recovery following spinal cord injury

Serotonin is a monoamine neurotransmitter synthetized in various populations of brainstem neurons.In the spinal cord,descending serotonergic projections regulate postural muscle tone,locomotion and rhythm and coordination of movements via the Central Pattern Generator.Following a spinal cord injury,serotonergic projections to the lumbar spinal cord,where the Central Pattern Generators are located,are interrupted resulting in devastating locomotor impairments and changes in the expression and activation of serotonin and its spinal receptors.The molecular cues that control the precise patterning and targeting of serotonergic inputs onto Central Pattern Generator networks in healthy animals or after injury are still unknown.In our recent research work,we have been particularly interested in Semaphorin7A,which belongs to the Semaphorins family involved in guiding growing axons and controlling plasticity of synaptic connections.In this review,we discuss the role of Semaphorin7A signaling as an important molecular actor that instructs the patterning of serotonin inputs to spinal Central Pattern Generator networks.We show that Semaphorin7A controls the wiring of descending serotonin axons in the spinal cord.Our results reveal that mistargetting of serotonin fibers in the spinal cord is compensated in healthy uninjured Semaphorin7A deficient mice so that their gross locomotion proceeds accurately.We also demonstrate that when the system is challenged with a spinal lesion,the pattern of post-injury serotonin expression is significantly altered in Semaphorin7A deficient mice with specific ectopic targeting of serotonin fibers in the lumbar spinal cord.Compensatory mechanisms in place in uninjured Semaphorin7A deficient mice are lost and injured Semaphorin7A deficient mice exhibit a worsening of their post-injury locomotor abilities.Our findings identify Semaphorin7A as a critical determinant of serotonergic circuit formation in healthy or spinal cord injured mice.

A Bionic Neural Network for Fish-Robot Locomotion

A bionic neural network for fish-robot locomotion is presented. The bionic neural network inspired from fish neural net- work consists of one high level controller and one chain of central pattern generators （CPGs）. Each CPG contains a nonlinear neural Zhang oscillator which shows properties similar to sine-cosine model. Simulation re, suits show that the bionic neural network presents a good performance in controlling the fish-robot to execute various motions such as startup, stop, forward swimming, backward swimming, turn right and turn left.

Dynamic Walking of AIBO with Hopf Oscillators

More and more biological evidences have been found that neural networks in the spinal cord, referred to as ＂central pattern generators＂ （CPGs）, govern locomotion. CPGs are capable of producing rhythmic movements, such as swimming, flying, and walking, even when isolated from the brain and sensory inputs. If we could build up any models that have similar functions as CPGs, it will be much easier to design better locomotion for robots. In this paper, a self-training environment is designed and through genetic algorithm （GA）, walking trajectories for every foot of AIBO are generated at first. With this acquired walking pattern, AIBO gets its fastest locomotion speed. Then, this walking pattern is taken as a reference to build CPGs with Hopf oscillators. By changing corresponding parameters, the frequencies and the amplitudes of CPGs＇ outputs can be adjusted online. The limit cycle behavior of Hopf oscillators ensures the online adjustment and the walking stability against perturbation as well. This property suggests a strong adaptive capacity to real environments for robots. At last, simulations are carried on in Webots and verify the proposed method.

Inter-limb and intra-limb coordination control of quadruped robots

To realize the coordinated and stable rhythmic motion of quadruped robots （QRs）, the locomotion control method of QRs based on central pattern generator （CPG） was explored. In tradi- tional control strategies based on CPG, few CPG models care about the intra-limb coordination of QRs, and the durations of stance phase and swing phase are always equal. In view of these deficien- cies, a new and simpler multi-joint coordinated control method for both inter-limb and intra-limb was proposed in this paper. A layered CPG control network to realize the locomotion control of QRs was constructed by using modified Hopf oscillators. The coupled relationships among hip joints of all limbs and between hip joint and knee joint within a limb were established. Using the co-simulation method of ADAMS and MATLAB/Simulink, various gait simulation experiments were carried out and the effectiveness of the designed control network was tested. Simulation results show that the pro- posed control method is effective for QRs and can meet the control requirements of QRs＇ gaits with different duty factors.

A vector inserting TPG for BIST design with low peak power consumption

A test pattern generator （TPG） which can highly reduce the peak power consumption during built-in self-test （BIST） application is proposed. The proposed TPG, called LPpe-TPG, consists of a linear feedback shift register （LFSR） and some control circuits. A procedure is presented firstly to make compare vectors between pseudorandom test patterns by adding some circuits to the original LFSR and secondly to insert some vectors between two successive pseudorandom test patterns according to the ordinal selection of every two bits of the compare vector. Then the changes between any successive test patterns of the test set generated by the LPpe-TPG are not more than twice. This leads to a decrease of the weighted switching activity （WSA） of the circuit under test （CUT） and therefore a reduction of the power consumption. Experimental results based on some ISCAS＇ 85 benchmark circuits show that the peak power consumption has been reduced by 25.25% to 64.46%. Also, the effectiveness of our approach to reduce the total and average power consumption is kept, without losing stuck-at fault coverage.

Continuous and smooth gait transition in a quadruped robot based on CPG

To improve the smoothness of motion control in a quadruped robot, a continuous and smooth gait transition method based on central pattern generator （CPG） was presented to solve the unsmooth or failed problem which may result in phase-locked or sharp point with direct replacement of the gait matrix. Through improving conventional weight matrix, a CPG network and a MATLAB/ Simulink model were constructed based on the Hopf oscillator for gait generation and transition in the quadruped robot. A co-simulation was performed using ADAMS/MATLAB for the gait transition between walk and trot to verify the correctness and effectiveness of the proposed CPG gait generation and transition algorithms. Related methods and conclusions can technically support the motion control technology of the quadruped robot.