47 results about "Central pattern generator" patented technology

An artificial Central Pattern Generator (CPG) based on the naturally-occuring central pattern generator locomotor controller for walking, running, swimming, and flying animals may be constructed to be self-adaptive, by providing for the artificial CPG, which may be a chip, to tune its behavior based on sensory feedback. It is believed that this is the first instance of an adaptive CPG chip. Such a sensory feedback-using system with an artificial CPG may be used in mechanical applications such as a running robotic leg, in walking, flying and swimming machines, and in miniature and larger robots, and also in biological systems, such as a surrogate neural system for patients with spinal damage.

The invention relates to a movement control method of pectoral fin impelling type machine fish, which comprises the following steps: using a plurality of centrum mode generators for forming a movement control network of the machine fish, and forming each centrum mode generator by adding input saturation functions and output amplification functions to single oscillation nerve cell; sending actuating signals into the first input saturation function and the second input saturation function, and carrying out frequency conversion on the actuating signals by the first input saturation function to obtain the natural frequency of the centrum mode generators; carrying out oscillation amplitude conversion on the actuating signals by the second input saturation function to obtain the natural oscillation amplitude; carrying out mutual inhabitation between state variables and coupling processing between oscillation nerve cells on the natural frequency and the natural oscillation amplitude to generate membrane potential signals; sending the membrane potential signals into the output amplification functions; carrying out proportional amplification and amplitude limiting processing on the membrane potential signals by the output amplification functions; and generating synapse connection signals, and sending the synapse connection signals onto a steering engine of a pectoral fin so that the pectoral fin can be driven to do reciprocating movement in a range between 0 and 360 degrees by a pectoral fin driving shaft.

The invention relates to a method for constructing central pattern generator (CPG) control network topology structure of biped robot. The method comprises the steps of separating a CPG control network into a body network portion for controlling hip joints and a leg network portion for controlling leg joints to achieve symmetry of control signals for left and right leg joints and control over reasonable phase relations of left and right legs; optimizing coupling connection modes among neuron units in the CPG control network to reduce the complexity of the CPG control network; and performing parameters setting on the CPG control network to construct an optimal network topology structure. Compared with the prior art, the method has the advantages of being low in complexity, reasonable in control network structure and the like.

The invention discloses a backward swimming control method of a biomimetic carangiform robot fish, based on a CPG (Central Pattern Generator) to control the robot fish to swim. The backward swimming control method comprises the following steps: firstly, building a CPG chain type network topology according to the characteristics of fish swimming to reduce a CPG parameter number and reduce the complexity of a model; secondly, by reasonably regulating parameters of the CPG model, enabling an output signal of the CPG model to satisfy the following condition, in a direction from the head to the tail of the robot fish, phases of the control signal of a steering engine of the robot fish sequentially lag, and amplitudes are sequentially reduced, so that backward propelling force is produced, and backward swimming of the robot fish is realized. The backward swimming control method has the promotion action in deeply understanding a backward swimming motion mechanism of fishes and also provides guidance for enriching motion modals of underwater robots and improving the maneuvering ability of the underwater robots.

The invention discloses an implementation method for the rapid great pitch angle change motion of a pectoral fin paddling type robotic fish, which includes the following steps: (Step 1) a rapid pitch kinematics model is created; (Step 2) a phase oscillator model with the characteristic of time and spatial asymmetry is created; (Step 3) a CPG (Central Pattern Generator) control network structure is created; (Step 4) a rapid pitch motion control system is created. The implementation method adopts multi-drive coordinated pectoral fin and tail motion, the robotic fish can generate pitch moment far greater than moment generated by the deflection of a swimming bladder or a single tail fin by means of the kinetic characteristic of spatial and time asymmetry, consequently, the implementation method can realize the rapid pitch (pitch angle change is greater than 60 degrees) motion of the pectoral fin paddling type robotic fish, and the obstacle-crossing and obstacle-avoiding ability of the robotic fish facing vertical wall type obstacles underwater is greatly enhanced.

This invention relates to one robot with easy module, which comprises match module, central mode generator in steering control formula, wherein, the match module comprises left and right bottom boards, steering machine and its supportive ear slices, steer rotation output slice, outer slice and inside supportive ear slices; steer machine one side rotation axis is fixed with rotation disc; the steer machine supportive ear slices and outer slices are connected to right bottom board; the outer supportive ear slice is connected to right bottom board; the steering machine rotation outputs ear slices, outer supportive ear slices and left bottom board.

The bionic mechanical reptile consists of one head module and one tail module without autokinetic motion function and basic trunk modules with one rotating freedom. The present invention adopts automatic passive sucker adsorption, multiple sensor fusion, and central mode generator motion control algorithm. The present invention has the advantages of capacity of crawling in vertical and inclined wall of different materials, capacity of crossing obstacle and face-to-face converting, etc.

The invention relates to a method for controlling motion of a bionic long-fin undulatory propeller. The method comprises the following steps: aiming at different motion modes of the long-fin undulatory propeller, setting a corresponding control parameter and an initial value; iteratively solving a differential equation of a central pattern generator model by utilizing an Euler method according to the input control parameter and the initial value; calculating a swinging angle of each fin on the long-fin undulatory propeller by utilizing an output amplitude value of the central pattern generator model in the iterative calculation process; and converting the swinging angle into the control quantity of a steering engine for coordinating and controlling a plurality of steering engines on the long-fin undulatory propeller through a pulse width modulation wave generator to enable the long-fin undulatory propeller to generate undulatory motion with stable and continuous rhythm and realize forward, backward, emergent stop, turning and rapid startup. The method is simple, reliable and easy to realize, has small calculation quantity and can meet the real-time requirement of coordinating and controlling a plurality of circuits of the steering engines of the long-fine undulatory propeller.

A synthetic nervous system (10) capable of rudimental learning and self-organization for robotic applications having a control circuit (190) and servo actuators (224) using oscillating continuously variable analog voltages to mimic natural bio-neural processes. Simple oscillators (1-8) capable of being modulated in frequency, phase, amplitude, and DC offset act as analog processing elements or oscillating infinite state machines. A central pattern generator (140) utilizing periodic, quasi-periodic, or chaotic oscillators or phase shifters, or a combination thereof, along with a basic motor neuron circuit (314) enables multiple servos to coordinate their behavior to enable bio-inspired locomotion such as walking, swimming, flapping, crawling, and the like. Sensors (200) interfaced to the control circuit (190) provide a wide range of adaptive behavior such as following a light source, avoiding an obstacle, and shifting balance point. Overlapping or concurrent sensor input can provide complex behavior with minimal circuitry.

The invention relates to a snake imitation search and rescue robot multi-gait control method, comprising: according to natural, wheel type and chaotic motion gaits, inputting a consistent relation by utilizing the output of a Hopfiled Neural Network (HNN) and the need of three types of motion gaits; adjusting the weighting parameter of the HNN to obtain a corresponding gait signal; using the output signal of the HNN as the input signal of a snake imitation search and rescue robot dynamics controller; and controlling the snake imitation search and rescue robot to generate a corresponding gait. In a non stable state, i.e., at an initial time and a gait conversion time, the motion shape code technique (MSCT) is utilized to generate the initial shape of a corresponding gait, and a linear shape is used as an intermediate process state to perform gait conversion. A traditional central pattern generator (CPG) method does not consider non period gait and chaotic gait problems in gait control, while the snake imitation search and rescue robot multi-gait control method solves the problem, is more practical, and allows a snake imitation search and rescue robot to be better applied to search and rescue tasks.

An artificial Central Pattern Generator (CPG) based on the naturally-occuring central pattern generator locomotor controller for walking, running, swimming, and flying animals may be constructed to be self-adaptive, by providing for the artificial CPG, which may be a chip, to tune its behavior based on sensory feedback. It is believed that this is the first instance of an adaptive CPG chip. Such a sensory feedback-using system with an artificial CPG may be used in mechanical applications such as a running robotic leg, in walking, flying and swimming machines, and in miniature and larger robots, and also in biological systems, such as a surrogate neural system for patients with spinal damage.

The invention discloses a central mode generator-based quadruped robot gait planning method. The method comprises the following steps: B1, reference oscillation signals are adjusted correspondingly inview of a different joint, the attitude angle, the angular velocity and the position of the trunk during the movement process of the quadruped robot are measured, and feedback signals are generated accordingly; according to the oscillation signals and the feedback signals after adjustment, control signals of each joint are outputted; the control signals of a side-swing joint contain the oscillation signals; control signals for a hip joint pair in swing and standing phases are different, control signals for a knee joint in the standing phase are adjusted, and thus, the angle of the knee jointis thus adjusted; and B2, the control signals control the quadruped robot to perform diagonal gaits, that is, a left foreleg and a right rear leg move together, and a right foreleg and a left rear legmove together. Different joints are adjusted differently, the pitch angle and the roll angle when the quadruped robot moves are reduced, and the stability of the quadruped robot during the motion process is improved.

The present invention belongs to the humanoid robot technical field and relates to a CPG (Central Pattern Generator) model-based humanoid robot gait planning method. The method includes the following steps that: (1) a corresponding coupled oscillator model is established according to specific hardware parameters of a robot; (2) the model is improved by adding a centroid offset control item, so that an improved oscillator model can be obtained; and (3) with velocity adopted as an input condition, genetic algorithm optimization is used to obtain the optimal values of parameters in step (2), and the obtained optimal values of the parameters are substituted into the model in step (2). With the planning method adopted, the robot is not prone to vibrating forwards and backwards and tumble when the robot rapidly accelerates to move or moves rapidly.

The invention discloses a multi-industrial-manipulator controller based on a double-layer CPG (central pattern generator). A structure similar to a layered neural network, which the ganglion controlling activities of invertebrates has and which a central nervous system controlling activities of vertebrates has, is adopted, features of a multi-industrial-manipulator control system and those of a single industrial manipulator are combined, and collective coordination and information interaction of multiple industrial manipulators are efficiently synergic. Flexible joints and a rich sensor system are adopted, information utilization rate of the multiple industrial manipulators is increased, and the joints of the industrial manipulators are effectively controlled, so that the system has high reliability and stability. The sensor system has the ability of autokinetic movement while the industrial-manipulator is enabled to have sufficient dynamic performance and degree of freedom. The multi-industrial-manipulator controller is composed of a phase coordination layer and a motion pattern generation layer; the phase coordination layer allows phase sequence locking for each industrial manipulator; the motion pattern generation layer allows trajectory planning and attitude adjustment for each industrial manipulator.

The invention relates to a control method for a bionic dual-feet robot walking on the water and provides a CPG (Central Pattern Generator)-fuzzy combination control carried on a robot. The CPG generates an oscillation signal for realizing the control over rhythmic exercises of robot dual feet. The fuzzy control is used for compensating dynamic balance of the dual-feet robot walking on the water in the left and right direction; and a feedback signal output by an angle measuring module can be used for carrying out feedback control on a CPG module and a fuzzy control module. The CPG-fuzzy combination control provided by the invention can provide reference for the control theory of walking on the water of the dual-feet robot and achieve the function of walking on the water.

The invention discloses construction of a propulsion motion control equation of a bionic undulatory fin and a parameter setting optimization method thereof, wherein an improved particle swarm algorithm is used for setting and optimizing parameters of the propulsion motion control equation of the bionic undulatory fin based on a central pattern generator. The motion control equation based on the central pattern generator can generate various rhythm signals with variable phase difference, frequency and amplitude, can resist the influence of sudden change of control parameters on the continuity of output signals, and can realize flexible transition of a bionic undulatory fin underwater robot under the switching of different swimming modes; and a method of CPG parameter setting optimization based on the improved particle swarm algorithm by taking a kinematic equation of a simplified ruled surface of a wave motion of a bionic object black ghost fish as a reference is proposed,. An inertia factor of the particle swarm algorithm is improved, and decreases linearly with the iteration of the algorithm, the accuracy of CPG parameter setting optimization is improved, and the performance of the bionic undulatory fin underwater robot is improved from a control algorithm level.

The invention discloses a method for realizing a self-adaptive walking framework of an anthropomorphic robot based on a CPG (Central Pattern Generator) model. The method comprises the following stepsof firstly, enabling a CPG network to output a reasonable rhythm control signal, so as to enable the anthropomorphic robot to walk on flat ground; designing a learning module based on a neural network, wherein the learning module is used for learning and outputting an expected rhythm compensation signal to act on the output of original CPG; finally, designing the reasonable robot feedback, so as to enable the whole control framework to output the expected rhythm control signal according to environments, thereby being suitable for various ramp environments. The method has the advantages that the problem of difficulty in production of precise and diversified rhythm signals by the CPG model in the field of bionic control of robots is solved; the practicality of the CPG model in the field of robot control is improved; the important meaning is realized for the designing of the more self-adaptive anthropomorphic robot system.

The invention relates to the technical field of robot control, and discloses a spiking neural network-based robot control method, which comprises the following steps of: preprocessing collected multi-modal data to obtain an emotion pulse signal; inputting the emotion pulse signal into a pre-constructed emotion pulse neural network, and outputting a comprehensive emotion pulse; inputting the comprehensive emotion pulse into a central pattern generator, and outputting a behavior rhythm; acquiring an environment feedback signal generated by executing the behavior rhythm, and adjusting a connection weight according to the environment feedback signal; optimizing the comprehensive emotion pulse according to the connection weight, and converting the optimized comprehensive emotion pulse into emotion interaction voice information; and adjusting the emotion intensity according to the optimized comprehensive emotion pulse and the multi-modal data. According to the method, data are collected through the multi-mode sensor to generate emotion pulses, the emotion pulses are input into the central mode generator to generate behavior rhythms after SNN processing, weight optimization, emotional speech generation and emotional steady-state control setting are combined with the STDP algorithm, and the efficiency of a robot service scene is improved.

The invention provides a movement control method for a quadruped robot based on a central pattern generator, and the method comprises a step of foot end locus planning which comprises the planning ofa locus of a foot end in a swinging state, a locus of the foot end in a support state and a locus of the foot end relative to a root joint. The method can achieve the independent control of the duty ratio, movement period and gait of a walking robot. Moreover, the method achieves the control of the gait of the robot through changing the phase of the robot, and the change interval of phase can be infinitely small, thereby enabling the robot to perform any gait, and guaranteeing the steady switching at any moment during the gait switching. The method can enable the robot to steadily move in a natural environment through the control of the gait of the robot.

The invention provides a CPG (Central Pattern Generator)-based cardiopulmonary rhythm synchronous control experimental platform. The CPG-based cardiopulmonary rhythm synchronous control experimental platform comprises two parts, namely an FPGA (Field Programmable Gate Array) development board and an upper computer, wherein the two parts are mutually connected through a USB (Universal Serial Bus) interface; the FPGA development board is used for realizing a cardiac muscle cell network model, a CPG model and an FFT (Fast Fourier Transform) algorithm; the upper computer is used for designing an upper computer software interface by adopting LabVIEW and is in communication with the FPGA development board. The CPG-based cardiopulmonary rhythm synchronous control experimental platform provided by the invention has the effects that through an FPGA neural network experimental platform based on high-speed computation which is used for carrying out non-animal testing on biological neural networks, regulation and control of a CPG on cardiopulmonary rhythm synchronization are realized, and the time-scale consistency with real biological neurons can be ensured; according to the CPG-based cardiopulmonary rhythm synchronous control experimental platform, a visual research platform which is more approximate to a real neural network is provided for researching a mechanism and control of the cardiopulmonary rhythm synchronization, and the CPG-based cardiopulmonary rhythm synchronous control experimental platform has the important practical value in researching and treating multiple cardiopulmonary diseases comprising a cardiovascular disease and the like.

Described is a system for controlling epidural spinal cord stimulation. Using an Unscented Kalman Filter (UKF), the system receives sensed physiological signals from a subject and, based on the sensed physiological signals, estimating an unobservable state of a target area on the subject. A central pattern generator is then used to generate a stimulation pattern based on the unobservable state. The stimulation pattern is applied to the target area (e.g., spinal cord) of the subject using an electrode array. Receiving feedback, the UKF continuously updates a model of the spinal cord, which results in adjustment of the stimulation pattern as necessary.

The invention relates to a movement control method of pectoral fin impelling type machine fish, which comprises the following steps: using a plurality of centrum mode generators for forming a movement control network of the machine fish, and forming each centrum mode generator by adding input saturation functions and output amplification functions to single oscillation nerve cell; sending actuating signals into the first input saturation function and the second input saturation function, and carrying out frequency conversion on the actuating signals by the first input saturation function to obtain the natural frequency of the centrum mode generators; carrying out oscillation amplitude conversion on the actuating signals by the second input saturation function to obtain the natural oscillation amplitude; carrying out mutual inhabitation between state variables and coupling processing between oscillation nerve cells on the natural frequency and the natural oscillation amplitude to generate membrane potential signals; sending the membrane potential signals into the output amplification functions; carrying out proportional amplification and amplitude limiting processing on the membrane potential signals by the output amplification functions; and generating synapse connection signals, and sending the synapse connection signals onto a steering engine of a pectoral fin so that the pectoral fin can be driven to do reciprocating movement in a range between 0 and 360 degrees by a pectoral fin driving shaft.

A method of generating an IRF pattern for testing an IC and a test pattern generator are disclosed. In one embodiment, the method includes: (1) identifying a path of the integrated circuit for inline resistive fault pattern generation, (2) determining if the path is a minimal slack path of the IC and (3) generating, when the path is the minimal slack path, a restricted inline resistive fault pattern for the path using only a capture polarity having a minimal inherent margin.

The invention provides a hexapod robot central pattern inverse control method. The method includes the following steps of 1, creating a D-H model of legs of a robot; 2, conducting foot end path planning on the robot on the basis of the D-H model; 3, conducting inverse kinematics analysis on foot end path planning to obtain a joint corner of each joint of the legs of the robot; 4, inputting the joint corner of each joint of the legs of the robot into a central pattern generator, wherein the central pattern generator outputs a control signal of each joint of the robot; 5, conducting signal coupling on the control signals of all the joints. By means of the method, the complexity of model control is effectively reduced, the gait of the robot is controlled conveniently, and the robot can move along a planned path.

The bionic mechanical reptile consists of one head module and one tail module without autokinetic motion function and basic trunk modules with one rotating freedom. The present invention adopts automatic passive sucker adsorption, multiple sensor fusion, and central mode generator motion control algorithm. The present invention has the advantages of capacity of crawling in vertical and inclined wall of different materials, capacity of crossing obstacle and face-to-face converting, etc.

The invention relates to a flexible mechanical arm and a central pattern generator-based control method. The flexible mechanical arm comprises a plurality of flexible modules which are connected in sequence in a set direction and a plurality of central pattern generators which are coupled with one another; each flexible module comprises an elastic shell; the inner cavity of each elastic shell is filled with a working medium; the volume of each flexible module does not change; the elastic shell comprises two transverse surfaces; the extending directions of the plurality of the flexible modulespenetrate through the transverse surfaces; the two transverse surfaces are connected to form the closed elastic shell through a longitudinal surface; and each central pattern generator can independently control the elastic deformation of each flexible module in the set direction and make the areas of the transverse surfaces and the corresponding longitudinal surface change in inverse proportion, so that the overall flexible mechanical arm moves in a set trajectory.

The invention discloses a quadruped robot motion control method and system based on spine and leg coordination, and the method comprises the steps: building a coupling relation model of spine torsion and four-limb swing, so as to describe a mathematical mapping relation between spine joint angles and four-limb joint angles; a spine-leg cooperative controller of a central mode generator (CPG) is formed by a plurality of nonlinear oscillators, and the nonlinear oscillators are mutually coupled to form a complete oscillator network so as to realize phase synchronization and amplitude coordination of spine torsion and four-limb swing; a self-adaptive coupling strength adjusting mechanism is constructed, and the coupling strength between the spine and the legs is dynamically adjusted according to external sensor information and the internal state; according to the current motion state and the environment information, coordinate control signals of spine joints and limb joints are generated, and the robot is driven to execute corresponding motion. Through the bionic spine-limb dynamic coupling and self-adaptive adjusting mechanism, the motion efficiency, stability and task adaptability of the robot in the unstructured environment are remarkably improved.

The invention discloses a safety constraint optimization gait planning method and device for a lower limb exoskeleton rehabilitation robot, and the method comprises the steps: designing an ACPG (adaptive central pattern generator) network topology for sagittal plane activity space limitation, and achieving the generation of a personalized gait track with a biological rhythm under human-computer interaction; on the basis of interaction torque and joint speed fed back by sensing, energy of human body active movement injected into the exoskeleton is calculated; constructing an intermediate variable according to the energy weighting, designing a gait adjustment model in combination with an admittance model, and outputting a self-adaptive smooth gait frequency and an amplitude modulation factor; based on the gait adjustment model, by using a control barrier function optimization theory, gait frequency and amplitude change are constrained within a safety range, so that the ACPG outputs rhythm gaits and meets safety requirements at the same time. According to the method, the energy change under the human-computer interaction effect is considered, and the personalized gait track with safety protection is generated.

The invention provides a CPG (Central Pattern Generator)-based cardiopulmonary rhythm synchronous control experimental platform. The CPG-based cardiopulmonary rhythm synchronous control experimental platform comprises two parts, namely an FPGA (Field Programmable Gate Array) development board and an upper computer, wherein the two parts are mutually connected through a USB (Universal Serial Bus) interface; the FPGA development board is used for realizing a cardiac muscle cell network model, a CPG model and an FFT (Fast Fourier Transform) algorithm; the upper computer is used for designing an upper computer software interface by adopting LabVIEW and is in communication with the FPGA development board. The CPG-based cardiopulmonary rhythm synchronous control experimental platform provided by the invention has the effects that through an FPGA neural network experimental platform based on high-speed computation which is used for carrying out non-animal testing on biological neural networks, regulation and control of a CPG on cardiopulmonary rhythm synchronization are realized, and the time-scale consistency with real biological neurons can be ensured; according to the CPG-based cardiopulmonary rhythm synchronous control experimental platform, a visual research platform which is more approximate to a real neural network is provided for researching a mechanism and control of the cardiopulmonary rhythm synchronization, and the CPG-based cardiopulmonary rhythm synchronous control experimental platform has the important practical value in researching and treating multiple cardiopulmonary diseases comprising a cardiovascular disease and the like.