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 el...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.展开更多
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 centra...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.展开更多
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 con...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展开更多
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 a...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.展开更多
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 g...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.展开更多
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-...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.展开更多
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 c...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.展开更多
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 tec...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.展开更多
In order to strike a balance between achieving desired velocities and minimizing energy consumption,legged animals have the ability to adopt the appropriate gait pattern and seamlessly transition to another if needed....In order to strike a balance between achieving desired velocities and minimizing energy consumption,legged animals have the ability to adopt the appropriate gait pattern and seamlessly transition to another if needed.This ability makes them more versatile and efficient when traversing natural terrains,and more suitable for long treks.In the same way,it is meaningful and important for quadruped robots to master this ability.To achieve this goal,we propose an effective gait-heuristic reinforcement learning framework in which multiple gait locomotion and smooth gait transitions automatically emerge to reach target velocities while minimizing energy consumption.We incorporate a novel trajectory generator with explicit gait information as a memory mechanism into the deep reinforcement learning framework.This allows the quadruped robot to adopt reliable and distinct gait patterns while benefiting from a warm start provided by the trajectory generator.Furthermore,we investigate the key factors contributing to the emergence of multiple gait locomotion.We tested our framework on a closed-chain quadruped robot and demonstrated that the robot can change its gait patterns,such as standing,walking,and trotting,to adopt the most energy-efficient gait at a given speed.Lastly,we deploy our learned controller to a quadruped robot and demonstrate the energy efficiency and robustness of our method.展开更多
Fish in nature exhibit a variety of swimming modes such as forward swimming,backward swimming,turning,pitching,etc.,enabling them to swim in complex scenes such as coral reefs.It is still difficult for a robotic fish ...Fish in nature exhibit a variety of swimming modes such as forward swimming,backward swimming,turning,pitching,etc.,enabling them to swim in complex scenes such as coral reefs.It is still difficult for a robotic fish to swim autonomously in a confined area as a real fish.Here,we develop an untethered robotic manta as an experimental platform,which consists of two flexible pectoral fins and a tail fin,with three infrared sensors installed on the front,left,and right sides of the head to sense the surrounding obstacles.To generate multiple swimming modes of the robotic manta and online switching of different modes,we design a closed-loop Central Pattern Generator(CPG)controller based on distance information and use a combination of phase difference and amplitude of the CPG model to achieve stable and rapid adjustment of yaw angle.To verify the autonomous swimming ability of the robotic manta in complex scenes,we design an experimental scenario with a concave obstacle.The experimental results show that the robotic manta can achieve forward swimming,backward swimming,in situ turning within the concave obstacle,and finally exit from the area safely while relying on the perception of external obstacles,which can provide insight into the autonomous exploration of complex scenes by the biomimetic robotic fish.Finally,the swimming ability of the robotic manta is verified by field tests.展开更多
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）....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.展开更多
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, ...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.展开更多
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 mec...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.展开更多
In rolling experiments,the performances of spider-like robot are limited greatly by its motors’driving ability;meanwhile,the ground reaction forces are so great that they damaged the rods.In this paper,we solve above...In rolling experiments,the performances of spider-like robot are limited greatly by its motors’driving ability;meanwhile,the ground reaction forces are so great that they damaged the rods.In this paper,we solve above problems both mechanically and by control.Firstly,we design the parameters of the central pattern generator(CPG)network based on the kinematics of the robot to enable a smooth rolling trajectory.And we also analyze the kinematic rolling and dynamic rolling briefly.Secondly,we add torsion springs to the passive joints of the spider-like robot aiming to make use of its energy storage capacity to compensate the insufficient torque.The simulation results show that the optimized CPG control parameters can reduce the fluctuation of the mass center and the ground reaction forces.The torsion spring can reduce the peak torque requirements of the actuated joints by 50%.展开更多
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 environmen...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.展开更多
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 limite...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.展开更多
This paper presents a study on bioinspired closed-loop Central Pattern Generator(CPG)based control of a robot fish for obstacle avoidance and direction tracking.The biomimetic robot fish is made of a rigid head with a...This paper presents a study on bioinspired closed-loop Central Pattern Generator(CPG)based control of a robot fish for obstacle avoidance and direction tracking.The biomimetic robot fish is made of a rigid head with a pair of pectoral fins,a wire-driven active body covered with soft skin,and a compliant tail.The CPG model consists of four input parameters:the flapping amplitude,the flapping angular velocity,the flapping offset,and the time ratio between the beat phase and the restore phase in flapping.The robot fish is equipped with three infrared sensors mounted on the left,front and right of the robot fish,as well as an inertial measurement unit,from which the surrounding obstacles and moving direction can be sensed.Based on these sensor signals,the closed-loop CPG-based control can drive the robot fish to avoid obstacles and to track designated directions.Four sets of experiments are presented,including avoiding a static obstacle,avoiding a moving obstacle,tracking a designated direction and tracking a designated direction with an obstacle in the path.The experiment results indicated that the presented control strategy worked well and the robot fish can accomplish the obstacle avoidance and direction tracking effectively.展开更多
基金supported by the Focused Ion Beam/Electron Beam Double Beam Microscopy(Grant No.2021YFF0704702).
文摘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.
基金the National Natural Science Foundation of China(No.51009091)the Special Research Fund for the Doctoral Program of Higher Education of China(No.20100073120016)
文摘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.
基金the U.S. Public Health Service for research grant funding for much of the work in my laboratory
文摘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
基金the National High Technology Research and Development(863)Program of China(No.2007AA09Z215)the National Natural Science Foundation of China(No.51009091)the Research Fund for the Doctoral Program of Higher Education of China(No.20100073120016)
文摘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.
基金supported by the National Natural Science Foundation of China(Nos.11232005 and11472104)the Doctoral Fund of Ministry of Education of China(No.20120074110020)
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China(Nos.11232005 and11472104)
文摘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.
文摘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.
文摘In order to strike a balance between achieving desired velocities and minimizing energy consumption,legged animals have the ability to adopt the appropriate gait pattern and seamlessly transition to another if needed.This ability makes them more versatile and efficient when traversing natural terrains,and more suitable for long treks.In the same way,it is meaningful and important for quadruped robots to master this ability.To achieve this goal,we propose an effective gait-heuristic reinforcement learning framework in which multiple gait locomotion and smooth gait transitions automatically emerge to reach target velocities while minimizing energy consumption.We incorporate a novel trajectory generator with explicit gait information as a memory mechanism into the deep reinforcement learning framework.This allows the quadruped robot to adopt reliable and distinct gait patterns while benefiting from a warm start provided by the trajectory generator.Furthermore,we investigate the key factors contributing to the emergence of multiple gait locomotion.We tested our framework on a closed-chain quadruped robot and demonstrated that the robot can change its gait patterns,such as standing,walking,and trotting,to adopt the most energy-efficient gait at a given speed.Lastly,we deploy our learned controller to a quadruped robot and demonstrate the energy efficiency and robustness of our method.
基金supported by the National Key Research and Development Program(Grant No.2020YFB1313200,2022YFC2805200)the National Natural Science Foundation of China(Grant No.52001260,52201381)Ningbo Natural Science Foundation(Grant No.2022J062).
文摘Fish in nature exhibit a variety of swimming modes such as forward swimming,backward swimming,turning,pitching,etc.,enabling them to swim in complex scenes such as coral reefs.It is still difficult for a robotic fish to swim autonomously in a confined area as a real fish.Here,we develop an untethered robotic manta as an experimental platform,which consists of two flexible pectoral fins and a tail fin,with three infrared sensors installed on the front,left,and right sides of the head to sense the surrounding obstacles.To generate multiple swimming modes of the robotic manta and online switching of different modes,we design a closed-loop Central Pattern Generator(CPG)controller based on distance information and use a combination of phase difference and amplitude of the CPG model to achieve stable and rapid adjustment of yaw angle.To verify the autonomous swimming ability of the robotic manta in complex scenes,we design an experimental scenario with a concave obstacle.The experimental results show that the robotic manta can achieve forward swimming,backward swimming,in situ turning within the concave obstacle,and finally exit from the area safely while relying on the perception of external obstacles,which can provide insight into the autonomous exploration of complex scenes by the biomimetic robotic fish.Finally,the swimming ability of the robotic manta is verified by field tests.
文摘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.
基金supported by National Natural Science Foundation of China (Grant No. 60875057)National Hi-tech Research and Development Program of China(863 Program, Grant No. 2009AA04Z213)
文摘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.
基金The National Natural Science Foundation of China(No.61375076)Research&Innovation Program for Graduate Student in Universities of Jiangsu Province(No.CXLX13-085)the Scientific Research Foundation of Graduate School of Southeast University(No.YBJJ1350)
文摘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.
基金the Fundamental Research Funds for the Central Universities of China(No.M15JB00250)。
文摘In rolling experiments,the performances of spider-like robot are limited greatly by its motors’driving ability;meanwhile,the ground reaction forces are so great that they damaged the rods.In this paper,we solve above problems both mechanically and by control.Firstly,we design the parameters of the central pattern generator(CPG)network based on the kinematics of the robot to enable a smooth rolling trajectory.And we also analyze the kinematic rolling and dynamic rolling briefly.Secondly,we add torsion springs to the passive joints of the spider-like robot aiming to make use of its energy storage capacity to compensate the insufficient torque.The simulation results show that the optimized CPG control parameters can reduce the fluctuation of the mass center and the ground reaction forces.The torsion spring can reduce the peak torque requirements of the actuated joints by 50%.
基金supported by National Natural Science Foundation of China (Grant No. 50905012)the Fundamental Research Funds for the Central Universities of China (Grant No. 2012JBM088)
文摘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.
基金supported by National Natural Science Foundation of China(Grant No.60535020)National Natural Science Funds for Distinguished Young Scholars of China(Grant No.60525314)
文摘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.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(class A)(Grant No.XDA22040203)the Fundamental Research Funds for the Central Universities(Grant No.2019XX01)+1 种基金GDNRC[2020]031the Natural Science Foundation of Guangdong Province(Grant No.2020A1515010621).
文摘This paper presents a study on bioinspired closed-loop Central Pattern Generator(CPG)based control of a robot fish for obstacle avoidance and direction tracking.The biomimetic robot fish is made of a rigid head with a pair of pectoral fins,a wire-driven active body covered with soft skin,and a compliant tail.The CPG model consists of four input parameters:the flapping amplitude,the flapping angular velocity,the flapping offset,and the time ratio between the beat phase and the restore phase in flapping.The robot fish is equipped with three infrared sensors mounted on the left,front and right of the robot fish,as well as an inertial measurement unit,from which the surrounding obstacles and moving direction can be sensed.Based on these sensor signals,the closed-loop CPG-based control can drive the robot fish to avoid obstacles and to track designated directions.Four sets of experiments are presented,including avoiding a static obstacle,avoiding a moving obstacle,tracking a designated direction and tracking a designated direction with an obstacle in the path.The experiment results indicated that the presented control strategy worked well and the robot fish can accomplish the obstacle avoidance and direction tracking effectively.
