This article provides a comprehensive exploration of the current research landscape in the field of soft actuation technology applied to bio-inspired soft robots. In sharp contrast to their conventional rigid counterp...This article provides a comprehensive exploration of the current research landscape in the field of soft actuation technology applied to bio-inspired soft robots. In sharp contrast to their conventional rigid counterparts, bio-inspired soft robots are primarily constructed from flexible materials, conferring upon them remarkable adaptability and flexibility to execute a multitude of tasks in complex environments. However, the classification of their driving technology poses a significant challenge owing to the diverse array of employed driving mechanisms and materials. Here, we classify several common soft actuation methods from the perspectives of the sources of motion in bio-inspired soft robots and their bio-inspired objects, effectively filling the classification system of soft robots, especially bio-inspired soft robots. Then, we summarize the driving principles and structures of various common driving methods from the perspective of bionics, and discuss the latest developments in the field of soft robot actuation from the perspective of driving modalities and methodologies. We then discuss the application directions of bio-inspired soft robots and the latest developments in each direction. Finally, after an in-depth review of various soft bio-inspired robot driving technologies in recent years, we summarize the issues and challenges encountered in the advancement of soft robot actuation technology.展开更多
In complex water environments,search tasks often involve multiple Autonomous Underwater Vehicles(AUVs),and a single centralized control cannot handle the complexity and computational burden of large-scale systems.Targ...In complex water environments,search tasks often involve multiple Autonomous Underwater Vehicles(AUVs),and a single centralized control cannot handle the complexity and computational burden of large-scale systems.Target search in complex water environments has always been a major challenge in the field of underwater robots.To address this problem,this paper proposes a multi-biomimetic robot fish collaborative target search method based on Distributed Model Predictive Control(DMPC).First,we established a bionic robot fish kinematic model and a multi-biomimetic robot fish communication model;second,this paper proposed a distributed model predictive control algorithm based on the distributed search theory framework,so that the bionic robot fish can dynamically adjust their search path according to each other’s position information and search status,avoid repeated coverage or missing areas,and thus improve the search efficiency;third,we conducted simulation experiments based on DMPC,and the results showed that the proposed method has a target search success rate of more than 90%in static targets,dynamic targets,and obstacle environments.Finally,we compared this method with Centralized Model Predictive Control(CMPC)and Random Walk(RW)algorithms.The DMPC approach demonstrates significant advantages,achieving a remarkable target search success rate of 94.17%.These findings comprehensively validate the effectiveness and superiority of the proposed methodology.It can be seen that DMPC can effectively dispatch multiple bionic robot fish to work together to achieve efficient search of vast waters.It can significantly improve the flexibility,scalability,robustness and cooperation efficiency of the system and has broad application prospects.展开更多
This paper investigates the motion control of the heavy-duty Bionic Caterpillar-like Robot(BCR)for the maintenance of the China Fusion Engineering Test Reactor(CFETR).Initially,a comprehensive nonlinear mathematical m...This paper investigates the motion control of the heavy-duty Bionic Caterpillar-like Robot(BCR)for the maintenance of the China Fusion Engineering Test Reactor(CFETR).Initially,a comprehensive nonlinear mathematical model for the BCR system is formulated using a physics-based approach.The nonlinear components of the model are compensated through nonlinear feedback linearization.Subsequently,a fuzzy-based regulator is employed to enhance the receding horizon opti-mization process for achieving optimal results.A Deep Neural Network(DNN)is trained to address disturbances.Conse-quently,a novel hybrid controller incorporating Nonlinear Model Predictive Control(NMPC),the Fuzzy Regulator(FR),and Deep Neural Network Feedforward(DNNF),named NMPC-FRDNNF is developed.Finally,the efficacy of the control system is validated through simulations and experiments.The results indicate that the Root Mean Square Error(RMSE)of the controller with FR and DNNF decreases by 33.2 and 48.9%,respectively,compared to the controller without these enhancements.This research provides a theoretical foundation and practical insights for ensuring the future highly stable,safe,and efficient maintenance of blankets.展开更多
The soft robotics field is on the rise. The highly adaptive robots provide the opportunity to bridge the gap between machines and people. However, their elastomeric nature poses significant challenges to the perceptio...The soft robotics field is on the rise. The highly adaptive robots provide the opportunity to bridge the gap between machines and people. However, their elastomeric nature poses significant challenges to the perception, control, and signal processing. Hydrogels and machine learning provide promising solutions to the problems above. This review aims to summarize this recent trend by first assessing the current hydrogel-based sensing and actuation methods applied to soft robots. We outlined the mechanisms of perception in response to various external stimuli. Next, recent achievements of machine learning for soft robots’ sensing data processing and optimization are evaluated. Here we list the strategies for implementing machine learning models from the perspective of applications. Last, we discuss the challenges and future opportunities in perception data processing and soft robots’ high level tasks.展开更多
This paper focuses on a bionic ray-inspired amphibious robot(BRAR), which is modeled through the differential steering approach. A nonlinear model predictive control(NMPC) obstacle avoidance method is proposed for tra...This paper focuses on a bionic ray-inspired amphibious robot(BRAR), which is modeled through the differential steering approach. A nonlinear model predictive control(NMPC) obstacle avoidance method is proposed for trajectory planning. First, a BRAR's differential drive system is designed, followed by kinematic and dynamic modeling. Subsequently, an NMPC-based obstacle avoidance trajectory planning method is developed to constitute safe trajectories in complex workspaces.Further, a dead zone compensation method is proposed to improve control precision. Finally, the effectiveness of the proposed method is validated through both simulations and experiments. Simulation and experimental results demonstrate the feasibility and effectiveness of the proposed methods.展开更多
In this paper,a bionic mantis shrimp amphibious soft robot based on a dielectric elastomer is proposed to realize highly adaptive underwater multimodal motion.Under the action of an independent actuator,it is not only...In this paper,a bionic mantis shrimp amphibious soft robot based on a dielectric elastomer is proposed to realize highly adaptive underwater multimodal motion.Under the action of an independent actuator,it is not only able to complete forward/backwards motion on land but also has the ability of cyclically controllable transition motion from land to water surface,from water surface to water bottom and from water bottom to land.The fastest speed of the soft robot on land is 170 mm/s,and it can crawl while carrying up to 4.6 times its own weight.The maximum speeds on the water surface and the water bottom are 30 mm/s and 14.4 mm/s,respectively.Furthermore,the soft robot can climb from the water bottom with a 9°slope transition to land.Compared with other similar soft robots,this soft robot has outstanding advantages,such as agile speed,large load-carrying capacity,strong body flexibility,multiple motion modes and strong underwater adaptability.Finally,nonlinear motion models of land crawling and water swimming are proposed to improve the environmental adaptability under multiple modalities,and the correctness of the theoretical model is verified by experiments.展开更多
Spinning gait is valuable for quadruped robot,which can be used to avoid obstacles quickly for robot walking in unstructured environment. A kind of bionic flexible body is presented for quadruped robot to perform the ...Spinning gait is valuable for quadruped robot,which can be used to avoid obstacles quickly for robot walking in unstructured environment. A kind of bionic flexible body is presented for quadruped robot to perform the spinning gait. The spinning gait can be achieved by coordinated movement of body laterally bending and legs swing,which can improve the mobility of robot walking in the unstructured environments. The coordinated movement relationship between the body and the leg mechanism is presented. The stability of quadruped robot with spinning gait is analyzed based on the center of gravity( COG) projection method. The effect of different body bending angle on the stability of quadruped robot with spinning gait is mainly studied. For the quadruped robot walking with spinning gait,during one spinning gait cycle,the supporting polygon and the trajectory of COG projection point under different body bending angle are calculated. Finally,the stability margin of quadruped robot with spinning gait under different body bending angle is determined,which can be used to evaluate reasonableness of spinning gait parameters.展开更多
Variable Stiffness Actuation(VSA)is an efficient,safe,and robust actuation technology for bionic robotic joints that have emerged in recent decades.By introducing a variable stiffness elastomer in the actuation system...Variable Stiffness Actuation(VSA)is an efficient,safe,and robust actuation technology for bionic robotic joints that have emerged in recent decades.By introducing a variable stiffness elastomer in the actuation system,the mechanical-electric energy conversion between the motor and the load could be adjusted on-demand,thereby improving the performance of the actuator,such as the peak power reduction,energy saving,bionic actuation,etc.At present,the VSA technology has achieved fruitful research results in designing the actuator mechanism and the stiffness adjustment servo,which has been widely applied in articulated robots,exoskeletons,prostheses,etc.However,how to optimally control the stiffness of VSAs in different application scenarios for better actuator performance is still challenging,where there is still a lack of unified cognition and viewpoints.Therefore,from the perspective of optimal VSA performance,this paper first introduces some typical structural design and servo control techniques of common VSAs and then explains the methods and applications of the Optimal Variable Stiffness Control(OVSC)approaches by theoretically introducing different types of OVSC mathematical models and summarizing OVSC methods with varying optimization goals and application scenarios or cases.In addition,the current research challenges of OVSC methods and possible innovative insights are also presented and discussed in-depth to facilitate the future development of VSA control.展开更多
A simplified model of the thrust force is proposed based on a caudal fin oscillation of an underwater bionic robot. The caudal fin oscillation is generalized by cen- tral pattern generators （CPGs）. In this model, th...A simplified model of the thrust force is proposed based on a caudal fin oscillation of an underwater bionic robot. The caudal fin oscillation is generalized by cen- tral pattern generators （CPGs）. In this model, the drag coefficient and lift coefficient are the two critical parameters which are obtained by the digital particle image velocimetry （DPIV） and the force transducer experiment. Numerical simulation and physical experi- ments have been performed to verify this dynamic model.展开更多
Although traditional position-controlled industrial robots can be competent for most assembly tasks,they cannot complete complex tasks that frequently interact with the external environment.The current research on exo...Although traditional position-controlled industrial robots can be competent for most assembly tasks,they cannot complete complex tasks that frequently interact with the external environment.The current research on exoskeleton robots also has problems such as excessive inertia of exoskeleton robots,poor system integration and difficult human–computer interaction control.To solve these problems,this paper independently develops a tendon driving robotic system composed of a tendon driving robotic arm and an upper limb exoskeleton,and studies its control technology.First,the robot system is selected,configured,and constructed.Second,the kinematics of the robot is analyzed,and then the dynamics are studied,and the parameter identification experiment of single degree of freedom is completed.Finally,the research on zero-force control and impedance control of the robot has effectively improved the robot’s human–machine integration ability,ensured the flexibility and compliance in the process of human–computer interaction.The compliant control problem expands the usage scenarios and application scope of robots and contributes to the realization of complex operations of this group of robots in unstructured environments.展开更多
Stingrays can undulate their wide pectoral fins to thrust themselves and swim freely underwater.Many researchers have used bionics to directly imitate their undulating mechanism and manufacture undulatory underwater r...Stingrays can undulate their wide pectoral fins to thrust themselves and swim freely underwater.Many researchers have used bionics to directly imitate their undulating mechanism and manufacture undulatory underwater robots.Based on the limitations of the existing undulatory underwater robots,this paper proposes a novel undulatory propulsion strategy,which aims to use the stingray undulating mechanism more thoroughly.First,the mathematical models of both traditional and novel structures are established to accurately describe their undulating mechanism.Then,based on the dynamic mesh technology,the flow field vortex structure they generated is analyzed through fluid-structure interaction simulation,and the thrust force and lateral force generated by them are calculated,which verified that this novel propulsion strategy is indeed more effective.Finally,a prototype robot based on the improved propulsion strategy is manufactured.Compared with the existing stingray robots,the prototype has obvious advantages,thus verifying the accuracy of the simulation results.展开更多
In order to reduce the labor intensity of high-altitude workers and realize the cleaning and maintenance of high-rise building exteriors,this paper proposes a design for a 4-DOF bipedal wall-climbing bionic robot insp...In order to reduce the labor intensity of high-altitude workers and realize the cleaning and maintenance of high-rise building exteriors,this paper proposes a design for a 4-DOF bipedal wall-climbing bionic robot inspired by the inchworm’s movement.The robot utilizes vacuum adsorption for vertical wall attachment and legged movement for locomotion.To enhance the robot’s movement efficiency and reduce wear on the adsorption device,a gait mimicking an inchworm’s movement is planned,and foot trajectory planning is performed using a quintic polynomial function.Under velocity constraints,foot trajectory optimization is achieved using an improved Particle Swarm Optimization(PSO)algorithm,determining the quintic polynomial function with the best fitness through simulation.Finally,through comparative experiments,the climbing time of the robot closely matches the simulation results,validating the trajectory planning method’s accuracy.展开更多
This paper proposes a new upper-limb exoskeleton to reduce worker physical strain.The proposed design is based on a novel PRRRP(P-Prismatic;R-Revolute)kinematic chain with 5 passive Degrees of Freedom(DoF).Utilizing a...This paper proposes a new upper-limb exoskeleton to reduce worker physical strain.The proposed design is based on a novel PRRRP(P-Prismatic;R-Revolute)kinematic chain with 5 passive Degrees of Freedom(DoF).Utilizing a magnetic spring,the proposed mechanism includes a specially designed locking mechanism that maintains any desired task posture.The proposed exoskeleton incorporates a balancing mechanism to alleviate discomfort and spinal torsional effects also helping in limb weight relief.This paper reports specific models and simulations to demonstrate the feasibility and effectiveness of the proposed design.An experimental characterization is performed to validate the performance of the mechanism in terms of forces and physical strain during a specific application consisting of ceiling-surface drilling tasks.The obtained results preliminarily validate the engineering feasibility and effectiveness of the proposed exoskeleton in the intended operation task thereby requiring the user to exert significantly less force than when not wearing it.展开更多
This paper proposed a novel humanoid robot eye, which is driven by six Pneumatic Artificial Muscles （PAMs） and rotates with 3 Degree of Freedom （DOF）. The design of the mechanism and motion type of the robot eye a...This paper proposed a novel humanoid robot eye, which is driven by six Pneumatic Artificial Muscles （PAMs） and rotates with 3 Degree of Freedom （DOF）. The design of the mechanism and motion type of the robot eye are inspired by that of human eyes. The model of humanoid robot eye is established as a parallel mechanism, and the inverse-kinematic problem of this flexible tendons driving parallel system is solved by the analytical geometry method. As an extension, the simulation result for saccadic movement is presented under three conditions. The design and kinematic analysis of the prototype could be a sig- nificant step towards the goal of building an autonomous humanoid robot eye with the movement and especially the visual functions similar to that of human.展开更多
In recent years,sEMG(surface electromyography)signals have been increasingly used to operate wearable devices.The development of mechanical lower limbs or exoskeletons controlled by the nervous system requires greater...In recent years,sEMG(surface electromyography)signals have been increasingly used to operate wearable devices.The development of mechanical lower limbs or exoskeletons controlled by the nervous system requires greater accuracy in recognizing lower limb activity.There is less research on devices to assist the human body in uphill movements.However,developing controllers that can accurately predict and control human upward movements in real-time requires the employment of appropriate signal pre-processing methods and prediction algorithms.For this purpose,this paper investigates the effects of various sEMG pre-processing methods and algorithms on the prediction results.This investigation involved ten subjects(five males and five females)with normal knee joints.The relevant data of the subjects were collected on a constructed ramp.To obtain feature values that reflect the gait characteristics,an improved PCA algorithm based on the kernel method is proposed for dimensionality reduction to remove redundant information.Then,a new model(CNN+LSTM)was proposed to predict the knee joint angle.Multiple approaches were utilized to validate the superiority of the improved PCA method and CNN-LSTM model.The feasibility of the method was verified by analyzing the gait prediction results of different subjects.Overall,the prediction time of the method was 25 ms,and the prediction error was 1.34±0.25 deg.By comparing with traditional machine learning methods such as BP(backpropagation)neural network,RF(random forest),and SVR(support vector machine),the improved PCA algorithm processed data performed the best in terms of convergence time and prediction accuracy in CNN-LSTM model.The experimental results demonstrate that the proposed method(improved PCA+CNN-LSTM)effectively recognizes lower limb activity from sEMG signals.For the same data input,the EMG signal processed using the improved PCA method performed better in terms of prediction results.This is the first step toward myoelectric control of aided exoskeleton robots using discrete decoding.The study results will lead to the future development of neuro-controlled mechanical exoskeletons that will allow troops or disabled individuals to engage in a greater variety of activities.展开更多
基金Fundamental Research Funds for the Central Universities(No.2024JBMC011)Aeronautical Science Foundation of China(No.2024Z0560M5001).
文摘This article provides a comprehensive exploration of the current research landscape in the field of soft actuation technology applied to bio-inspired soft robots. In sharp contrast to their conventional rigid counterparts, bio-inspired soft robots are primarily constructed from flexible materials, conferring upon them remarkable adaptability and flexibility to execute a multitude of tasks in complex environments. However, the classification of their driving technology poses a significant challenge owing to the diverse array of employed driving mechanisms and materials. Here, we classify several common soft actuation methods from the perspectives of the sources of motion in bio-inspired soft robots and their bio-inspired objects, effectively filling the classification system of soft robots, especially bio-inspired soft robots. Then, we summarize the driving principles and structures of various common driving methods from the perspective of bionics, and discuss the latest developments in the field of soft robot actuation from the perspective of driving modalities and methodologies. We then discuss the application directions of bio-inspired soft robots and the latest developments in each direction. Finally, after an in-depth review of various soft bio-inspired robot driving technologies in recent years, we summarize the issues and challenges encountered in the advancement of soft robot actuation technology.
基金funded by National Natural Science Foundation of China(Nos.62473236,62073196).
文摘In complex water environments,search tasks often involve multiple Autonomous Underwater Vehicles(AUVs),and a single centralized control cannot handle the complexity and computational burden of large-scale systems.Target search in complex water environments has always been a major challenge in the field of underwater robots.To address this problem,this paper proposes a multi-biomimetic robot fish collaborative target search method based on Distributed Model Predictive Control(DMPC).First,we established a bionic robot fish kinematic model and a multi-biomimetic robot fish communication model;second,this paper proposed a distributed model predictive control algorithm based on the distributed search theory framework,so that the bionic robot fish can dynamically adjust their search path according to each other’s position information and search status,avoid repeated coverage or missing areas,and thus improve the search efficiency;third,we conducted simulation experiments based on DMPC,and the results showed that the proposed method has a target search success rate of more than 90%in static targets,dynamic targets,and obstacle environments.Finally,we compared this method with Centralized Model Predictive Control(CMPC)and Random Walk(RW)algorithms.The DMPC approach demonstrates significant advantages,achieving a remarkable target search success rate of 94.17%.These findings comprehensively validate the effectiveness and superiority of the proposed methodology.It can be seen that DMPC can effectively dispatch multiple bionic robot fish to work together to achieve efficient search of vast waters.It can significantly improve the flexibility,scalability,robustness and cooperation efficiency of the system and has broad application prospects.
基金supported by Comprehensive Research Facility for Fusion Technology Program of China under Contract No.2018-000052-73-01-001228the China Scholarship Council with No.202206340050National Natural Science Foundation of China with Grant No.11905147.
文摘This paper investigates the motion control of the heavy-duty Bionic Caterpillar-like Robot(BCR)for the maintenance of the China Fusion Engineering Test Reactor(CFETR).Initially,a comprehensive nonlinear mathematical model for the BCR system is formulated using a physics-based approach.The nonlinear components of the model are compensated through nonlinear feedback linearization.Subsequently,a fuzzy-based regulator is employed to enhance the receding horizon opti-mization process for achieving optimal results.A Deep Neural Network(DNN)is trained to address disturbances.Conse-quently,a novel hybrid controller incorporating Nonlinear Model Predictive Control(NMPC),the Fuzzy Regulator(FR),and Deep Neural Network Feedforward(DNNF),named NMPC-FRDNNF is developed.Finally,the efficacy of the control system is validated through simulations and experiments.The results indicate that the Root Mean Square Error(RMSE)of the controller with FR and DNNF decreases by 33.2 and 48.9%,respectively,compared to the controller without these enhancements.This research provides a theoretical foundation and practical insights for ensuring the future highly stable,safe,and efficient maintenance of blankets.
基金supported in part by the National Natural Science Foundation of China under Grant 62104034the Natural Science Foundation of Hebei Province under Grant F2020501033Fundamental Research Fund for Central University under grant N2223032.
文摘The soft robotics field is on the rise. The highly adaptive robots provide the opportunity to bridge the gap between machines and people. However, their elastomeric nature poses significant challenges to the perception, control, and signal processing. Hydrogels and machine learning provide promising solutions to the problems above. This review aims to summarize this recent trend by first assessing the current hydrogel-based sensing and actuation methods applied to soft robots. We outlined the mechanisms of perception in response to various external stimuli. Next, recent achievements of machine learning for soft robots’ sensing data processing and optimization are evaluated. Here we list the strategies for implementing machine learning models from the perspective of applications. Last, we discuss the challenges and future opportunities in perception data processing and soft robots’ high level tasks.
基金supported by the National Natural Science Foundation of China under Grants 52205019 and 62373198the Tianjin Science Fund for Distinguished Young Scholars under Grant 22JCJQJC00140+1 种基金the Guangdong Basic and Applied Basic Research Foundation under Grant 2023A1515012669the Fundamental Research Funds for the Central Universities under Grant 078-63243157
文摘This paper focuses on a bionic ray-inspired amphibious robot(BRAR), which is modeled through the differential steering approach. A nonlinear model predictive control(NMPC) obstacle avoidance method is proposed for trajectory planning. First, a BRAR's differential drive system is designed, followed by kinematic and dynamic modeling. Subsequently, an NMPC-based obstacle avoidance trajectory planning method is developed to constitute safe trajectories in complex workspaces.Further, a dead zone compensation method is proposed to improve control precision. Finally, the effectiveness of the proposed method is validated through both simulations and experiments. Simulation and experimental results demonstrate the feasibility and effectiveness of the proposed methods.
基金the National Natural Science Foundation of China,Natural Science Foundation of Shandong Province with Grant No.ZR2019MEE019Fundamental Research Funds for the Central University with Grant No.2019ZRJC006.
文摘In this paper,a bionic mantis shrimp amphibious soft robot based on a dielectric elastomer is proposed to realize highly adaptive underwater multimodal motion.Under the action of an independent actuator,it is not only able to complete forward/backwards motion on land but also has the ability of cyclically controllable transition motion from land to water surface,from water surface to water bottom and from water bottom to land.The fastest speed of the soft robot on land is 170 mm/s,and it can crawl while carrying up to 4.6 times its own weight.The maximum speeds on the water surface and the water bottom are 30 mm/s and 14.4 mm/s,respectively.Furthermore,the soft robot can climb from the water bottom with a 9°slope transition to land.Compared with other similar soft robots,this soft robot has outstanding advantages,such as agile speed,large load-carrying capacity,strong body flexibility,multiple motion modes and strong underwater adaptability.Finally,nonlinear motion models of land crawling and water swimming are proposed to improve the environmental adaptability under multiple modalities,and the correctness of the theoretical model is verified by experiments.
基金Supported by the National Natural Science Foundation of China(No.51375289)Shanghai Municipal National Natural Science Foundation of China(No.13ZR1415500)Innovation Fund of Shanghai Education Commission(No.13YZ020)
文摘Spinning gait is valuable for quadruped robot,which can be used to avoid obstacles quickly for robot walking in unstructured environment. A kind of bionic flexible body is presented for quadruped robot to perform the spinning gait. The spinning gait can be achieved by coordinated movement of body laterally bending and legs swing,which can improve the mobility of robot walking in the unstructured environments. The coordinated movement relationship between the body and the leg mechanism is presented. The stability of quadruped robot with spinning gait is analyzed based on the center of gravity( COG) projection method. The effect of different body bending angle on the stability of quadruped robot with spinning gait is mainly studied. For the quadruped robot walking with spinning gait,during one spinning gait cycle,the supporting polygon and the trajectory of COG projection point under different body bending angle are calculated. Finally,the stability margin of quadruped robot with spinning gait under different body bending angle is determined,which can be used to evaluate reasonableness of spinning gait parameters.
基金National Key Research and Development Program of China[Grant No.2020YFB1313000]National Natural Science Foundation of China[Grant No.62003060,62101086,51975070]+2 种基金China Postdoctoral Science Foundation[2021M693769]Natural Science Foundation of Chongqing,China[Grant No.cstc2021jcyj-bsh0180]Scientific and Technological Research Program of Chongqing Municipal Education Commission[Grant No.KJQN202100648].
文摘Variable Stiffness Actuation(VSA)is an efficient,safe,and robust actuation technology for bionic robotic joints that have emerged in recent decades.By introducing a variable stiffness elastomer in the actuation system,the mechanical-electric energy conversion between the motor and the load could be adjusted on-demand,thereby improving the performance of the actuator,such as the peak power reduction,energy saving,bionic actuation,etc.At present,the VSA technology has achieved fruitful research results in designing the actuator mechanism and the stiffness adjustment servo,which has been widely applied in articulated robots,exoskeletons,prostheses,etc.However,how to optimally control the stiffness of VSAs in different application scenarios for better actuator performance is still challenging,where there is still a lack of unified cognition and viewpoints.Therefore,from the perspective of optimal VSA performance,this paper first introduces some typical structural design and servo control techniques of common VSAs and then explains the methods and applications of the Optimal Variable Stiffness Control(OVSC)approaches by theoretically introducing different types of OVSC mathematical models and summarizing OVSC methods with varying optimization goals and application scenarios or cases.In addition,the current research challenges of OVSC methods and possible innovative insights are also presented and discussed in-depth to facilitate the future development of VSA control.
基金Project supported by the National Natural Science Foundation of China(Nos.61503008 and 51575005)the China Postdoctoral Science Foundation(No.2015M570013)
文摘A simplified model of the thrust force is proposed based on a caudal fin oscillation of an underwater bionic robot. The caudal fin oscillation is generalized by cen- tral pattern generators （CPGs）. In this model, the drag coefficient and lift coefficient are the two critical parameters which are obtained by the digital particle image velocimetry （DPIV） and the force transducer experiment. Numerical simulation and physical experi- ments have been performed to verify this dynamic model.
基金the National Key R&D Program of China(Grant No.2021YFB3201600).
文摘Although traditional position-controlled industrial robots can be competent for most assembly tasks,they cannot complete complex tasks that frequently interact with the external environment.The current research on exoskeleton robots also has problems such as excessive inertia of exoskeleton robots,poor system integration and difficult human–computer interaction control.To solve these problems,this paper independently develops a tendon driving robotic system composed of a tendon driving robotic arm and an upper limb exoskeleton,and studies its control technology.First,the robot system is selected,configured,and constructed.Second,the kinematics of the robot is analyzed,and then the dynamics are studied,and the parameter identification experiment of single degree of freedom is completed.Finally,the research on zero-force control and impedance control of the robot has effectively improved the robot’s human–machine integration ability,ensured the flexibility and compliance in the process of human–computer interaction.The compliant control problem expands the usage scenarios and application scope of robots and contributes to the realization of complex operations of this group of robots in unstructured environments.
基金This work is supported by the National Science Foundation of China(No.91748123)the Natural Science Foundation of Shaanxi Province(Grant No.2019JM-145).
文摘Stingrays can undulate their wide pectoral fins to thrust themselves and swim freely underwater.Many researchers have used bionics to directly imitate their undulating mechanism and manufacture undulatory underwater robots.Based on the limitations of the existing undulatory underwater robots,this paper proposes a novel undulatory propulsion strategy,which aims to use the stingray undulating mechanism more thoroughly.First,the mathematical models of both traditional and novel structures are established to accurately describe their undulating mechanism.Then,based on the dynamic mesh technology,the flow field vortex structure they generated is analyzed through fluid-structure interaction simulation,and the thrust force and lateral force generated by them are calculated,which verified that this novel propulsion strategy is indeed more effective.Finally,a prototype robot based on the improved propulsion strategy is manufactured.Compared with the existing stingray robots,the prototype has obvious advantages,thus verifying the accuracy of the simulation results.
基金supported by the Guangxi Science and Technology Base and Talent Project(AD23026115)the Special fund for centrally guided local science and technology development(2023JRZ0103)+1 种基金the Guangxi University of Science and Technology Doctoral Fund(2023KY0353)the Guangxi University of Science and Technology Doctoral Fund(22Z39).
文摘In order to reduce the labor intensity of high-altitude workers and realize the cleaning and maintenance of high-rise building exteriors,this paper proposes a design for a 4-DOF bipedal wall-climbing bionic robot inspired by the inchworm’s movement.The robot utilizes vacuum adsorption for vertical wall attachment and legged movement for locomotion.To enhance the robot’s movement efficiency and reduce wear on the adsorption device,a gait mimicking an inchworm’s movement is planned,and foot trajectory planning is performed using a quintic polynomial function.Under velocity constraints,foot trajectory optimization is achieved using an improved Particle Swarm Optimization(PSO)algorithm,determining the quintic polynomial function with the best fitness through simulation.Finally,through comparative experiments,the climbing time of the robot closely matches the simulation results,validating the trajectory planning method’s accuracy.
基金supported by the European Regional Development Fund and the Romanian Government through the Competitiveness Operational Programme 2014-2020project APOLLO,MySMIS code 155988,contract no.9/1.2.1-PTIap.2/23.02.2023.
文摘This paper proposes a new upper-limb exoskeleton to reduce worker physical strain.The proposed design is based on a novel PRRRP(P-Prismatic;R-Revolute)kinematic chain with 5 passive Degrees of Freedom(DoF).Utilizing a magnetic spring,the proposed mechanism includes a specially designed locking mechanism that maintains any desired task posture.The proposed exoskeleton incorporates a balancing mechanism to alleviate discomfort and spinal torsional effects also helping in limb weight relief.This paper reports specific models and simulations to demonstrate the feasibility and effectiveness of the proposed design.An experimental characterization is performed to validate the performance of the mechanism in terms of forces and physical strain during a specific application consisting of ceiling-surface drilling tasks.The obtained results preliminarily validate the engineering feasibility and effectiveness of the proposed exoskeleton in the intended operation task thereby requiring the user to exert significantly less force than when not wearing it.
基金the National Natural Science Foundation of China (Project no. 50875240)the Program for New Century Excellent Talents in University, Ministry of Education, P. R. China (Grant no.NCET-04-0545)
文摘This paper proposed a novel humanoid robot eye, which is driven by six Pneumatic Artificial Muscles （PAMs） and rotates with 3 Degree of Freedom （DOF）. The design of the mechanism and motion type of the robot eye are inspired by that of human eyes. The model of humanoid robot eye is established as a parallel mechanism, and the inverse-kinematic problem of this flexible tendons driving parallel system is solved by the analytical geometry method. As an extension, the simulation result for saccadic movement is presented under three conditions. The design and kinematic analysis of the prototype could be a sig- nificant step towards the goal of building an autonomous humanoid robot eye with the movement and especially the visual functions similar to that of human.
文摘In recent years,sEMG(surface electromyography)signals have been increasingly used to operate wearable devices.The development of mechanical lower limbs or exoskeletons controlled by the nervous system requires greater accuracy in recognizing lower limb activity.There is less research on devices to assist the human body in uphill movements.However,developing controllers that can accurately predict and control human upward movements in real-time requires the employment of appropriate signal pre-processing methods and prediction algorithms.For this purpose,this paper investigates the effects of various sEMG pre-processing methods and algorithms on the prediction results.This investigation involved ten subjects(five males and five females)with normal knee joints.The relevant data of the subjects were collected on a constructed ramp.To obtain feature values that reflect the gait characteristics,an improved PCA algorithm based on the kernel method is proposed for dimensionality reduction to remove redundant information.Then,a new model(CNN+LSTM)was proposed to predict the knee joint angle.Multiple approaches were utilized to validate the superiority of the improved PCA method and CNN-LSTM model.The feasibility of the method was verified by analyzing the gait prediction results of different subjects.Overall,the prediction time of the method was 25 ms,and the prediction error was 1.34±0.25 deg.By comparing with traditional machine learning methods such as BP(backpropagation)neural network,RF(random forest),and SVR(support vector machine),the improved PCA algorithm processed data performed the best in terms of convergence time and prediction accuracy in CNN-LSTM model.The experimental results demonstrate that the proposed method(improved PCA+CNN-LSTM)effectively recognizes lower limb activity from sEMG signals.For the same data input,the EMG signal processed using the improved PCA method performed better in terms of prediction results.This is the first step toward myoelectric control of aided exoskeleton robots using discrete decoding.The study results will lead to the future development of neuro-controlled mechanical exoskeletons that will allow troops or disabled individuals to engage in a greater variety of activities.
