The lower limb exoskeletons are used to assist wearers in various scenarios such as medical and industrial settings.Complex modeling errors of the exoskeleton in different application scenarios pose challenges to the ...The lower limb exoskeletons are used to assist wearers in various scenarios such as medical and industrial settings.Complex modeling errors of the exoskeleton in different application scenarios pose challenges to the robustness and stability of its control algorithm.The Radial Basis Function(RBF)neural network is used widely to compensate for modeling errors.In order to solve the problem that the current RBF neural network controllers cannot guarantee the asymptotic stability,a neural network robust control algorithm based on computed torque method is proposed in this paper,focusing on trajectory tracking.It innovatively incorporates the robust adaptive term while introducing the RBF neural network term,improving the compensation ability for modeling errors.The stability of the algorithm is proved by Lyapunov method,and the effectiveness of the robust adaptive term is verified by the simulation.Experiments wearing the exoskeleton under different walking speeds and scenarios were carried out,and the results show that the absolute value of tracking errors of the hip and knee joints of the exoskeleton are consistently less than 1.5°and 2.5°,respectively.The proposed control algorithm effectively compensates for modeling errors and exhibits high robustness.展开更多
The goal of this paper is to develop a unified online motion generation scheme for quadruped lateral-sequence walk and trot gaits based on a linear model predictive control formulation.Specifically,the dynamics of the...The goal of this paper is to develop a unified online motion generation scheme for quadruped lateral-sequence walk and trot gaits based on a linear model predictive control formulation.Specifically,the dynamics of the linear pendulum model is formulated over a predictive horizon by dimensional analysis.Through gait pattern conversion,the lateral-sequence walk and trot gaits of the quadruped can be regarded as unified biped gaits,allowing the dynamics of the linear inverted pendulum model to serve quadruped motion generation.In addition,a simple linearization of the center of pressure constraints for these quadruped gaits is developed for linear model predictive control problem.Furthermore,the motion generation problem can be solved online by quadratic programming with foothold adaptation.It is demonstrated that the proposed unified scheme can generate stable locomotion online for quadruped lateral-sequence walk and trot gaits,both in simulation and on hardware.The results show significant performance improvements compared to previous work.Moreover,the results also suggest the linearly simplified scheme has the ability to robustness against unexpected disturbances.展开更多
This paper proposes a unified trajectory optimization approach that simultaneously optimizes the trajectory of the center of mass and footholds for legged locomotion.Based on a generic point-mass model,the approach is...This paper proposes a unified trajectory optimization approach that simultaneously optimizes the trajectory of the center of mass and footholds for legged locomotion.Based on a generic point-mass model,the approach is formulated as a nonlinear optimization problem,incorporating constraints such as robot kinematics,dynamics,ground reaction forces,obstacles,and target location.The unified optimization approach can be applied to both long-term motion planning and the reactive online planning through the use of model predictive control,and it incorporates vector field guidance to converge to the long-term planned motion.The effectiveness of the approach is demonstrated through simulations and physical experiments,showing its ability to generate a variety of walking and jumping gaits,as well as transitions between them,and to perform reactive walking in obstructed environments.展开更多
In the era of big data and the Internet of Things,the digital information of athletes is particularly significant in sports competitions.Here,an intelligent self-powered take-off board sensor(TBS)based on triboelectri...In the era of big data and the Internet of Things,the digital information of athletes is particularly significant in sports competitions.Here,an intelligent self-powered take-off board sensor(TBS)based on triboelectric nanogenerator(TENG)with a solid-wooden substrate is provided for precise detection of athletes’take-off status in the sport of triple-jumping,which is sufficient for triplejumping training judgment with a high accuracy of 1 mm.Meanwhile,a foul alarm system and a distance between the athlete’s foot and take-off line(GAP)measurement system are further developed to provide take-off data for athletes and referees.The induced charges are formed by the TBS during taking-off,and then the real-time exercise data is acquired and processed via the test program.This work presents a self-powered sports sensor for intelligent sports monitoring and promotes the application of TENG-based sensors in intelligent sports.展开更多
Under the requirement of the force controller of hydraulic quadruped robots,the goal of this work is to accurately track the force commands at the level of the hydraulic drive unit.The main contribution focuses on the...Under the requirement of the force controller of hydraulic quadruped robots,the goal of this work is to accurately track the force commands at the level of the hydraulic drive unit.The main contribution focuses on the development of a force-controlled compensation scheme,which is specifically aimed at the key issues affecting the hydraulic quadrupedal locomotion.With this idea,based on a P-Q valve-controlled asymmetric cylinder,we first establish a mathematical model for the hydraulic drive unit force control system.With the desired force commands,a force feed-forward algorithm is presented to improve the dynamic performance of the system.Meanwhile,we propose a disturbance compensation algorithm to reduce the influence induced by external disturbances due to foot-ground impacts.Afterwards,combining with a variable gain PI controller,a series of experiments are implemented on a force control performance test platform to verify the proposed scheme.The results demonstrate that the force-controlled compensation scheme has the ability to notably improve the force tracking accuracy,reduce the response time and redundant force.展开更多
The theft prevention for cultural relics in museums,field excavation sites,and temporary exhibition events is of extreme importance.However,traditional anti-theft technologies such as infrared monitoring and radio fre...The theft prevention for cultural relics in museums,field excavation sites,and temporary exhibition events is of extreme importance.However,traditional anti-theft technologies such as infrared monitoring and radio frequency identification are highly costly,power-consuming,and easy to break.Here,a transparent,ultrathin,and flexible triboelectric sensor(TUFS)with a simple and low-cost method is proposed.With a thickness,weight,and transmittance of 92μm,0.12 g,and 89.4%,the TUFS manifests superb concealment.Benefiting from the characteristic of triboelectric nanogenerators,the TUFS responds effectively to common cultural-relic materials.Moreover,distinguished electrical responses can be obtained even for very small weights(10 g)and areas(1 cm^(2)),proving the sensitivity and wide range of use of the TUFS.Finally,we construct a concealed cultural-relic anti-theft system that enables real-time alarming and accurate positioning of cultural relics,which is expected to strengthen the security level of the existing museum anti-theft systems.展开更多
基金Supported by National Key R&D Program of China(Grant No.2022YFB4701200)National Natural Science Foundation of China(NSFC)(Grant Nos.T2121003,52205004).
文摘The lower limb exoskeletons are used to assist wearers in various scenarios such as medical and industrial settings.Complex modeling errors of the exoskeleton in different application scenarios pose challenges to the robustness and stability of its control algorithm.The Radial Basis Function(RBF)neural network is used widely to compensate for modeling errors.In order to solve the problem that the current RBF neural network controllers cannot guarantee the asymptotic stability,a neural network robust control algorithm based on computed torque method is proposed in this paper,focusing on trajectory tracking.It innovatively incorporates the robust adaptive term while introducing the RBF neural network term,improving the compensation ability for modeling errors.The stability of the algorithm is proved by Lyapunov method,and the effectiveness of the robust adaptive term is verified by the simulation.Experiments wearing the exoskeleton under different walking speeds and scenarios were carried out,and the results show that the absolute value of tracking errors of the hip and knee joints of the exoskeleton are consistently less than 1.5°and 2.5°,respectively.The proposed control algorithm effectively compensates for modeling errors and exhibits high robustness.
基金supported by the National Natural Science Foundation of China(Nos.52305072 and 52122503)Natural Science Foundation of Hebei Province of China(No.E2022203095)+2 种基金University-Industry Collaborative Education Program(No.220603936245709)Cultivation Project for Basic Research and Innovation of Yanshan University(No.2021LGQN004)henzhen Special Fund for Future Industrial Development(No.KJZD20230923114222045).
文摘The goal of this paper is to develop a unified online motion generation scheme for quadruped lateral-sequence walk and trot gaits based on a linear model predictive control formulation.Specifically,the dynamics of the linear pendulum model is formulated over a predictive horizon by dimensional analysis.Through gait pattern conversion,the lateral-sequence walk and trot gaits of the quadruped can be regarded as unified biped gaits,allowing the dynamics of the linear inverted pendulum model to serve quadruped motion generation.In addition,a simple linearization of the center of pressure constraints for these quadruped gaits is developed for linear model predictive control problem.Furthermore,the motion generation problem can be solved online by quadratic programming with foothold adaptation.It is demonstrated that the proposed unified scheme can generate stable locomotion online for quadruped lateral-sequence walk and trot gaits,both in simulation and on hardware.The results show significant performance improvements compared to previous work.Moreover,the results also suggest the linearly simplified scheme has the ability to robustness against unexpected disturbances.
基金supported by the Natural Science Foundation of Hebei Province of China(no.E2022203095)Cultivation Project for Basic Research and Innovation of Yanshan University(no.2021LGQN004)National Natural Science Foundation of China(no.51905465 and No.52122503).
文摘This paper proposes a unified trajectory optimization approach that simultaneously optimizes the trajectory of the center of mass and footholds for legged locomotion.Based on a generic point-mass model,the approach is formulated as a nonlinear optimization problem,incorporating constraints such as robot kinematics,dynamics,ground reaction forces,obstacles,and target location.The unified optimization approach can be applied to both long-term motion planning and the reactive online planning through the use of model predictive control,and it incorporates vector field guidance to converge to the long-term planned motion.The effectiveness of the approach is demonstrated through simulations and physical experiments,showing its ability to generate a variety of walking and jumping gaits,as well as transitions between them,and to perform reactive walking in obstructed environments.
基金supported by the National Natural Science Foundation of China(No.61503051).
文摘In the era of big data and the Internet of Things,the digital information of athletes is particularly significant in sports competitions.Here,an intelligent self-powered take-off board sensor(TBS)based on triboelectric nanogenerator(TENG)with a solid-wooden substrate is provided for precise detection of athletes’take-off status in the sport of triple-jumping,which is sufficient for triplejumping training judgment with a high accuracy of 1 mm.Meanwhile,a foul alarm system and a distance between the athlete’s foot and take-off line(GAP)measurement system are further developed to provide take-off data for athletes and referees.The induced charges are formed by the TBS during taking-off,and then the real-time exercise data is acquired and processed via the test program.This work presents a self-powered sports sensor for intelligent sports monitoring and promotes the application of TENG-based sensors in intelligent sports.
基金This work was supported by National Natural Science Foundation of China(No.61773139)Shenzhen Special Fund for Future Industrial Development(No.JCYJ20160425150757025)Shenzhen Science and Technology Program(No.KQTD2016112515134654).
文摘Under the requirement of the force controller of hydraulic quadruped robots,the goal of this work is to accurately track the force commands at the level of the hydraulic drive unit.The main contribution focuses on the development of a force-controlled compensation scheme,which is specifically aimed at the key issues affecting the hydraulic quadrupedal locomotion.With this idea,based on a P-Q valve-controlled asymmetric cylinder,we first establish a mathematical model for the hydraulic drive unit force control system.With the desired force commands,a force feed-forward algorithm is presented to improve the dynamic performance of the system.Meanwhile,we propose a disturbance compensation algorithm to reduce the influence induced by external disturbances due to foot-ground impacts.Afterwards,combining with a variable gain PI controller,a series of experiments are implemented on a force control performance test platform to verify the proposed scheme.The results demonstrate that the force-controlled compensation scheme has the ability to notably improve the force tracking accuracy,reduce the response time and redundant force.
基金the National Natural Science Foundation of China(No.61503051).
文摘The theft prevention for cultural relics in museums,field excavation sites,and temporary exhibition events is of extreme importance.However,traditional anti-theft technologies such as infrared monitoring and radio frequency identification are highly costly,power-consuming,and easy to break.Here,a transparent,ultrathin,and flexible triboelectric sensor(TUFS)with a simple and low-cost method is proposed.With a thickness,weight,and transmittance of 92μm,0.12 g,and 89.4%,the TUFS manifests superb concealment.Benefiting from the characteristic of triboelectric nanogenerators,the TUFS responds effectively to common cultural-relic materials.Moreover,distinguished electrical responses can be obtained even for very small weights(10 g)and areas(1 cm^(2)),proving the sensitivity and wide range of use of the TUFS.Finally,we construct a concealed cultural-relic anti-theft system that enables real-time alarming and accurate positioning of cultural relics,which is expected to strengthen the security level of the existing museum anti-theft systems.
