Legged robots have always been a focal point of research for scholars domestically and internationally.Compared to other types of robots,quadruped robots exhibit superior balance and stability,enabling them to adapt e...Legged robots have always been a focal point of research for scholars domestically and internationally.Compared to other types of robots,quadruped robots exhibit superior balance and stability,enabling them to adapt effectively to diverse environments and traverse rugged terrains.This makes them well-suited for applications such as search and rescue,exploration,and transportation,with strong environmental adaptability,high flexibility,and broad application prospects.This paper discusses the current state of research on quadruped robots in terms of development status,gait trajectory planning methods,motion control strategies,reinforcement learning applications,and control algorithm integration.It highlights advancements in modeling,optimization,control,and data-driven approaches.The study identifies the adoption of efficient gait planning algorithms,the integration of reinforcement learning-based control technologies,and data-driven methods as key directions for the development of quadruped robots.The aim is to provide theoretical references for researchers in the field of quadruped robotics.展开更多
The wheeled bipedal robots have great application potential in environments with a mixture of structured and unstructured terrain. However, wheeled bipedal robots have problems such as poor balance ability and low mov...The wheeled bipedal robots have great application potential in environments with a mixture of structured and unstructured terrain. However, wheeled bipedal robots have problems such as poor balance ability and low movement level on rough roads. In this paper, a novel and low-cost wheeled bipedal robot with an asymmetrical five-link mechanism is proposed, and the kinematics of the legs and the dynamics of the Wheeled Inverted Pendulum (WIP) are modeled. The primary balance controller of the wheeled bipedal robot is built based on the Linear Quadratic Regulator (LQR) and the compensation method of the virtual pitch angle adjusting the Center of Mass (CoM) position, then the whole-body hybrid torque-position control is established by combining attitude and leg controllers. The stability of the robot’s attitude control and motion is verified with simulations and prototype experiments, which confirm the robot’s ability to pass through complex terrain and resist external interference. The feasibility and reliability of the proposed control model are verified.展开更多
Robotic manipulators increasingly operate in complex three-dimensional workspaces where accuracy and strict limits on position,velocity,and acceleration must be satisfied.Conventional geometric planners emphasize path...Robotic manipulators increasingly operate in complex three-dimensional workspaces where accuracy and strict limits on position,velocity,and acceleration must be satisfied.Conventional geometric planners emphasize path smoothness but often ignore dynamic feasibility,motivating control-aware trajectory generation.This study presents a novel model predictive control(MPC)framework for three-dimensional trajectory planning of robotic manipulators that integrates second-order dynamic modeling and multi-objective parameter optimization.Unlike conventional interpolation techniques such as cubic splines,B-splines,and linear interpolation,which neglect physical constraints and system dynamics,the proposed method generates dynamically feasible trajectories by directly optimizing over acceleration inputs while minimizing both tracking error and control effort.A key innovation lies in the use of Pareto front analysis for tuning prediction horizon and sampling time,enabling a systematic balance between accuracy and motion smoothness.Comparative evaluation using simulated experiments demonstrates that the proposed MPC approach achieves a minimum mean absolute error(MAE)of 0.170 and reduces maximum acceleration to 0.0217,compared to 0.0385 in classical linear methods.The maximum deviation error was also reduced by approximately 27.4%relative to MPC configurations without tuned parameters.All experiments were conducted in a simulation environment,with computational times per control cycle consistently remaining below 20 milliseconds,indicating practical feasibility for real-time applications.Thiswork advances the state-of-the-art inMPC-based trajectory planning by offering a scalable and interpretable control architecture that meets physical constraints while optimizing motion efficiency,thus making it suitable for deployment in safety-critical robotic applications.展开更多
The dynamic motion capability of humanoid robots is a key indicator for evaluating their performance.Jumping,as a typical dynamic motion,is of great significance for enhancing the robot’s flexibility and terrain adap...The dynamic motion capability of humanoid robots is a key indicator for evaluating their performance.Jumping,as a typical dynamic motion,is of great significance for enhancing the robot’s flexibility and terrain adaptability in unstructured environments.However,achieving high-dynamic jumping control of humanoid robots has become a challenge due to the high degree of freedom and strongly coupled dynamic characteristics.The idea for this paper originated from the human response process to jumping commands,aiming to achieve online trajectory optimization and jumping motion control of humanoid robots.Firstly,we employ nonlinear optimization in combination with the Single Rigid Body Model(SRBM)to generate a robot’s Center of Mass(CoM)trajectory that complies with physical constraints and minimizes the angular momentum of the CoM.Then,a Model Predictive Controller(MPC)is designed to track and control the CoM trajectory,obtaining the required contact forces at the robot’s feet.Finally,a Whole-Body Controller(WBC)is used to generate full-body joint motion trajectories and driving torques,based on the prioritized sequence of tasks designed for the jumping process.The control framework proposed in this paper considers the dynamic characteristics of the robot’s jumping process,with a focus on improving the real-time performance of trajectory optimization and the robustness of controller.Simulation and experimental results demonstrate that our robot successfully executed high jump motions,long jump motions and continuous jump motions under complex working conditions.展开更多
Image acquisition stands as a prerequisite for scrutinizing surfaces inspection in industrial high-end manufacturing.Current imaging systems often exhibit inflexibility,being confined to specific objects and encounter...Image acquisition stands as a prerequisite for scrutinizing surfaces inspection in industrial high-end manufacturing.Current imaging systems often exhibit inflexibility,being confined to specific objects and encountering difficulties with diverse industrial structures lacking standardized computer-aided design(CAD)models or in instances of deformation.Inspired by the multidimensional observation of humans,our study introduces a universal image acquisition paradigm tailored for robotics,seamlessly integrating multi-objective optimization trajectory planning and control scheme to harness measured point clouds for versatile,efficient,and highly accurate image acquisition across diverse structures and scenarios.Specifically,we introduce an energybased adaptive trajectory optimization(EBATO)method that combines deformation and deviation with dual-threshold optimization and adaptive weight adjustment to improve the smoothness and accuracy of imaging trajectory and posture.Additionally,a multi-optimization control scheme based on a meta-heuristic beetle antennal olfactory recurrent neural network(BAORNN)is proposed to track the imaging trajectory while addressing posture,obstacle avoidance,and physical constraints in industrial scenarios.Simulations,real-world experiments,and comparisons demonstrate the effectiveness and practicality of the proposed paradigm.展开更多
The contour error was analyzed based on CNC multi-axis motion control, the contour error model was obtained focused on beeline and different radius of curvature and common contour of curve, for a CNC biaxial motion co...The contour error was analyzed based on CNC multi-axis motion control, the contour error model was obtained focused on beeline and different radius of curvature and common contour of curve, for a CNC biaxial motion control system and the mechanism of producing contour error and the relationship between tracking error and contour error were presented. The theoretical and practical significance of modeling error and controlling error in motion control systems was carried out.展开更多
Performing diverse motor skills with a universal controller has been a longstanding challenge for legged robots.While motion imitation-based reinforcement learning(RL)has shown remarkable performance in reproducing de...Performing diverse motor skills with a universal controller has been a longstanding challenge for legged robots.While motion imitation-based reinforcement learning(RL)has shown remarkable performance in reproducing designed motor skills,the trained controller is only suitable for one specific type of motion.Motion synthesis has been well developed to generate a variety of different motions for character animation,but those motions only contain kinematic information and cannot be used for control.In this study,we introduce a control pipeline combining motion synthesis and motion imitation-based RL for generic motor skills.We design an animation state machine to synthesize motion from various sources and feed the generated kinematic reference trajectory to the RL controller as part of the input.With the proposed method,we show that a single policy is able to learn various motor skills simultaneously.Further,we notice the ability of the policy to uncover the correlations lurking behind the reference motions to improve control performance.We analyze this ability based on the predictability of the reference trajectory and use the quantified measurements to optimize the design of the controller.To demonstrate the effectiveness of our method,we deploy the trained policy on hardware and,with a single control policy,the quadruped robot can perform various learned skills,including automatic gait transitions,high kick,and forward jump.展开更多
In order to analyze underwater robot control system dynamics features, a system 6-DOF dynamics model was founded. Underwater robot linear and nonlinear hydrodynamics were analyzed by Taylor series, based on general mo...In order to analyze underwater robot control system dynamics features, a system 6-DOF dynamics model was founded. Underwater robot linear and nonlinear hydrodynamics were analyzed by Taylor series, based on general motion equation. Special control system motion equation was deduced by cluster of inertial items and non-inertial items. For program convenience, motion equation matrix format was presented. Experimental principles of screw propellers, rudders and wings were discussed. Experimental data least-square curve fitting, interpolation and their corresponding traditional equation helped us to obtain the whole system dynamic response procedure. A series of simulation experiments show that the dynamics model is correct and reliable. The model can provide theory proof for analyzing underwater robot motion control system physics characters and provide a mathematic model for traditional control method.展开更多
This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm ha...This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.展开更多
This paper presents a novel hybrid task priority-based motion planning algorithm of a space robot. The satellite attitude control task is defined as the primary task, while the leastsquares-based non-strict task prior...This paper presents a novel hybrid task priority-based motion planning algorithm of a space robot. The satellite attitude control task is defined as the primary task, while the leastsquares-based non-strict task priority solution of the end-effector plus the multi-constraint task is viewed as the secondary task. Furthermore, a null-space task compensation strategy in the joint space is proposed to derive the combination of non-strict and strict task-priority motion planning,and this novel combination is termed hybrid task priority control. Thus, the secondary task is implemented in the primary task＇s null-space. Besides, the transition of the state of multiple constraints between activeness and inactiveness will only influence the end-effector task without any effect on the primary task. A set of numerical experiments made in a real-time simulation system under Linux/RTAI shows the validity and feasibility of the proposed methodology.展开更多
This paper presents a dynamic model and performance constraint control of a line-driven soft robotic arm.The dynamics model of the soft robotic arm is established by combining the screw theory and the Cosserat theory....This paper presents a dynamic model and performance constraint control of a line-driven soft robotic arm.The dynamics model of the soft robotic arm is established by combining the screw theory and the Cosserat theory.The unmodeled dynamics of the system are considered,and an adaptive neural network controller is designed using the backstepping method and radial basis function neural network.The stability of the closed-loop system and the boundedness of the tracking error are verified using Lyapunov theory.The simulation results show that our approach is a good solution to the motion constraint problem of the line-driven soft robotic arm.展开更多
A compliant landing strategy for a trotting quadruped robot on unknown rough terrains based on contact force control is presented. Firstly, in order to lower the disturbance caused by the landing impact force, a landi...A compliant landing strategy for a trotting quadruped robot on unknown rough terrains based on contact force control is presented. Firstly, in order to lower the disturbance caused by the landing impact force, a landing phase is added between the swing phase and the stance phase, where the desired contact force is set as a small positive constant. Secondly, the joint torque optimization of the stance legs is formulated as a quadratic programming(QP) problem subject to equality and inequality/bound constraints. And a primal-dual dynamical system solver based on linear variational inequalities(LVI) is applied to solve this QP problem. Furthermore, based on the optimization results, a hybrid motion/force robust controller is designed to realize the tracking of the contact force, while the constraints of the stance feet landing angles are fulfilled simultaneously. Finally, the experiments are performed to validate the proposed methods.展开更多
Control of coordinated motion between the base attitude and the arm joints of a free-floating dual-arm space robot with uncertain parameters is discussed. By combining the relation of system linear momentum conversati...Control of coordinated motion between the base attitude and the arm joints of a free-floating dual-arm space robot with uncertain parameters is discussed. By combining the relation of system linear momentum conversation with the Lagrangian approach, the dynamic equation of a robot is established. Based on the above results, the free-floating dual-arm space robot system is modeled with RBF neural networks, the GL matrix and its product operator. With all uncertain inertial system parameters, an adaptive RBF neural network control scheme is developed for coordinated motion between the base attitude and the arm joints. The proposed scheme does not need linear parameterization of the dynamic equation of the system and any accurate prior-knowledge of the actual inertial parameters. Also it does not need to train the neural network offline so that it would present real-time and online applications. A planar free-floating dual-arm space robot is simulated to show feasibility of the proposed scheme.展开更多
Aircraft skin health concerns whether the aircraft can fly safely.In this paper,an improved mechanical structure of the aircraft skin inspection robot was introduced.Considering that the aircraft skin surface is a cur...Aircraft skin health concerns whether the aircraft can fly safely.In this paper,an improved mechanical structure of the aircraft skin inspection robot was introduced.Considering that the aircraft skin surface is a curved environment,we assume that the curved environment is equivalent to an inclined plane with a change in inclination.Based on this assumption,the Cartesian dynamics model of the robot is established using the Lagrange method.In order to control the robot’s movement position accurately,a position backstepping control scheme for the aircraft skin inspection robot was presented.According to the dynamic model and taking into account the problems faced by the robot during its movement,a position constrained controller of the aircraft skin inspection robot is designed using the barrier Lyapunov function.Aiming at the disturbances in the robot,we adopt a fuzzy system to approximate the unknown dynamics related with system states.Finally,the simulation results of the designed position constrained controller were compared with the sliding mode controller,and prove the validity of the position constrained controller.展开更多
Robotic manipulators are widely used in applications that require fast and precise motion.Such devices,however,are prompt to nonlinear control issues due to the flexibility in joints and the friction in the motors wit...Robotic manipulators are widely used in applications that require fast and precise motion.Such devices,however,are prompt to nonlinear control issues due to the flexibility in joints and the friction in the motors within the dynamics of their rigid part.To address these issues,the Linear Matrix Inequalities(LMIs)and Parallel Distributed Compensation(PDC)approaches are implemented in the Takagy–Sugeno Fuzzy Model(T-SFM).We propose the following methodology;initially,the state space equations of the nonlinear manipulator model are derived.Next,a Takagy–Sugeno Fuzzy Model(T-SFM)technique is used for linearizing the state space equations of the nonlinear manipulator.The T-SFM controller is developed using the Parallel Distributed Compensation(PDC)method.The prime concept of the designed controller is to compensate for all the fuzzy rules.Furthermore,the Linear Matrix Inequalities(LMIs)are applied to generate adequate cases to ensure stability and control.Convex programming methods are applied to solve the developed LMIs problems.Simulations developed for the proposed model show that the proposed controller stabilized the system with zero tracking error in less than 1.5 s.展开更多
A practical motion control strategy for a radio-controlled, 4-link and free-swimmingbiomimetic robot fish is presented. Based on control performance of the fish the fish s motion controltask is decomposed into on-line...A practical motion control strategy for a radio-controlled, 4-link and free-swimmingbiomimetic robot fish is presented. Based on control performance of the fish the fish s motion controltask is decomposed into on-line speed control and orientation control. The speed control algorithm isimplemented by using piecewise control, and orientation control is realized by fuzzy logic. Combiningwith step control and fuzzy control, a point-to-point (PTP) control algorithm is proposed and appliedto the closed-loop experimental system that uses a vision-based position sensing subsystem to providefeedback. Experiments confirm the reliability and e?ectiveness of the presented algorithms.展开更多
Taking a six-DOF hydraulic parallel experimental robot designed and manufactured by the authors as the object of study, we researched the track plan, special track producing method, place(position) and velocity contro...Taking a six-DOF hydraulic parallel experimental robot designed and manufactured by the authors as the object of study, we researched the track plan, special track producing method, place(position) and velocity control algorithm of parallel robot,etc. All researches have been verified by experimental prototype.展开更多
基金funded by the Natural Science Basis Research Plan in Shaanxi Province of China(Program No.2023-JC-QN-0659)General Specialized Scientific Research Program of the Shaanxi Provincial Department of Education(Program 23JK0349).
文摘Legged robots have always been a focal point of research for scholars domestically and internationally.Compared to other types of robots,quadruped robots exhibit superior balance and stability,enabling them to adapt effectively to diverse environments and traverse rugged terrains.This makes them well-suited for applications such as search and rescue,exploration,and transportation,with strong environmental adaptability,high flexibility,and broad application prospects.This paper discusses the current state of research on quadruped robots in terms of development status,gait trajectory planning methods,motion control strategies,reinforcement learning applications,and control algorithm integration.It highlights advancements in modeling,optimization,control,and data-driven approaches.The study identifies the adoption of efficient gait planning algorithms,the integration of reinforcement learning-based control technologies,and data-driven methods as key directions for the development of quadruped robots.The aim is to provide theoretical references for researchers in the field of quadruped robotics.
基金supported in part by the National Natural Science Foundationof China under Grant(61801122)Natural Science Foundation of FujianProvince(2022J01542).
文摘The wheeled bipedal robots have great application potential in environments with a mixture of structured and unstructured terrain. However, wheeled bipedal robots have problems such as poor balance ability and low movement level on rough roads. In this paper, a novel and low-cost wheeled bipedal robot with an asymmetrical five-link mechanism is proposed, and the kinematics of the legs and the dynamics of the Wheeled Inverted Pendulum (WIP) are modeled. The primary balance controller of the wheeled bipedal robot is built based on the Linear Quadratic Regulator (LQR) and the compensation method of the virtual pitch angle adjusting the Center of Mass (CoM) position, then the whole-body hybrid torque-position control is established by combining attitude and leg controllers. The stability of the robot’s attitude control and motion is verified with simulations and prototype experiments, which confirm the robot’s ability to pass through complex terrain and resist external interference. The feasibility and reliability of the proposed control model are verified.
基金funded by the research project“BR24992947—Development of Robots,Scientific,Technical,and Software for Flexible Robotization and Industrial Automation(RPA)in Automotive Industrial Enterprises in Kazakhstan Using Artificial Intelligence”.
文摘Robotic manipulators increasingly operate in complex three-dimensional workspaces where accuracy and strict limits on position,velocity,and acceleration must be satisfied.Conventional geometric planners emphasize path smoothness but often ignore dynamic feasibility,motivating control-aware trajectory generation.This study presents a novel model predictive control(MPC)framework for three-dimensional trajectory planning of robotic manipulators that integrates second-order dynamic modeling and multi-objective parameter optimization.Unlike conventional interpolation techniques such as cubic splines,B-splines,and linear interpolation,which neglect physical constraints and system dynamics,the proposed method generates dynamically feasible trajectories by directly optimizing over acceleration inputs while minimizing both tracking error and control effort.A key innovation lies in the use of Pareto front analysis for tuning prediction horizon and sampling time,enabling a systematic balance between accuracy and motion smoothness.Comparative evaluation using simulated experiments demonstrates that the proposed MPC approach achieves a minimum mean absolute error(MAE)of 0.170 and reduces maximum acceleration to 0.0217,compared to 0.0385 in classical linear methods.The maximum deviation error was also reduced by approximately 27.4%relative to MPC configurations without tuned parameters.All experiments were conducted in a simulation environment,with computational times per control cycle consistently remaining below 20 milliseconds,indicating practical feasibility for real-time applications.Thiswork advances the state-of-the-art inMPC-based trajectory planning by offering a scalable and interpretable control architecture that meets physical constraints while optimizing motion efficiency,thus making it suitable for deployment in safety-critical robotic applications.
基金supported in part by the National Key Research and Development Program of China(2020YFB13134)Major Project of National Natural Science Foundation of China(U2013602)+2 种基金The National Nature Science Foundation of China(52075115)HIT Major Campus Cultivation Project(2023FRFK01001)National independent project(SKLRS202301A12).
文摘The dynamic motion capability of humanoid robots is a key indicator for evaluating their performance.Jumping,as a typical dynamic motion,is of great significance for enhancing the robot’s flexibility and terrain adaptability in unstructured environments.However,achieving high-dynamic jumping control of humanoid robots has become a challenge due to the high degree of freedom and strongly coupled dynamic characteristics.The idea for this paper originated from the human response process to jumping commands,aiming to achieve online trajectory optimization and jumping motion control of humanoid robots.Firstly,we employ nonlinear optimization in combination with the Single Rigid Body Model(SRBM)to generate a robot’s Center of Mass(CoM)trajectory that complies with physical constraints and minimizes the angular momentum of the CoM.Then,a Model Predictive Controller(MPC)is designed to track and control the CoM trajectory,obtaining the required contact forces at the robot’s feet.Finally,a Whole-Body Controller(WBC)is used to generate full-body joint motion trajectories and driving torques,based on the prioritized sequence of tasks designed for the jumping process.The control framework proposed in this paper considers the dynamic characteristics of the robot’s jumping process,with a focus on improving the real-time performance of trajectory optimization and the robustness of controller.Simulation and experimental results demonstrate that our robot successfully executed high jump motions,long jump motions and continuous jump motions under complex working conditions.
基金supported in part by the National Natural Science Foundation of China(62303457,U21A20482)China Postdoctoral Science Foundation(2023M733737)the National Key Research and Development Program of China(2022YFB3303800)。
文摘Image acquisition stands as a prerequisite for scrutinizing surfaces inspection in industrial high-end manufacturing.Current imaging systems often exhibit inflexibility,being confined to specific objects and encountering difficulties with diverse industrial structures lacking standardized computer-aided design(CAD)models or in instances of deformation.Inspired by the multidimensional observation of humans,our study introduces a universal image acquisition paradigm tailored for robotics,seamlessly integrating multi-objective optimization trajectory planning and control scheme to harness measured point clouds for versatile,efficient,and highly accurate image acquisition across diverse structures and scenarios.Specifically,we introduce an energybased adaptive trajectory optimization(EBATO)method that combines deformation and deviation with dual-threshold optimization and adaptive weight adjustment to improve the smoothness and accuracy of imaging trajectory and posture.Additionally,a multi-optimization control scheme based on a meta-heuristic beetle antennal olfactory recurrent neural network(BAORNN)is proposed to track the imaging trajectory while addressing posture,obstacle avoidance,and physical constraints in industrial scenarios.Simulations,real-world experiments,and comparisons demonstrate the effectiveness and practicality of the proposed paradigm.
基金supported by the Science Foundation of the Education Office of Gansu Province of Chinaunder Grant No.0914-01
文摘The contour error was analyzed based on CNC multi-axis motion control, the contour error model was obtained focused on beeline and different radius of curvature and common contour of curve, for a CNC biaxial motion control system and the mechanism of producing contour error and the relationship between tracking error and contour error were presented. The theoretical and practical significance of modeling error and controlling error in motion control systems was carried out.
基金supported by the National Natural Science Foundation of China(No.12132013).
文摘Performing diverse motor skills with a universal controller has been a longstanding challenge for legged robots.While motion imitation-based reinforcement learning(RL)has shown remarkable performance in reproducing designed motor skills,the trained controller is only suitable for one specific type of motion.Motion synthesis has been well developed to generate a variety of different motions for character animation,but those motions only contain kinematic information and cannot be used for control.In this study,we introduce a control pipeline combining motion synthesis and motion imitation-based RL for generic motor skills.We design an animation state machine to synthesize motion from various sources and feed the generated kinematic reference trajectory to the RL controller as part of the input.With the proposed method,we show that a single policy is able to learn various motor skills simultaneously.Further,we notice the ability of the policy to uncover the correlations lurking behind the reference motions to improve control performance.We analyze this ability based on the predictability of the reference trajectory and use the quantified measurements to optimize the design of the controller.To demonstrate the effectiveness of our method,we deploy the trained policy on hardware and,with a single control policy,the quadruped robot can perform various learned skills,including automatic gait transitions,high kick,and forward jump.
文摘In order to analyze underwater robot control system dynamics features, a system 6-DOF dynamics model was founded. Underwater robot linear and nonlinear hydrodynamics were analyzed by Taylor series, based on general motion equation. Special control system motion equation was deduced by cluster of inertial items and non-inertial items. For program convenience, motion equation matrix format was presented. Experimental principles of screw propellers, rudders and wings were discussed. Experimental data least-square curve fitting, interpolation and their corresponding traditional equation helped us to obtain the whole system dynamic response procedure. A series of simulation experiments show that the dynamics model is correct and reliable. The model can provide theory proof for analyzing underwater robot motion control system physics characters and provide a mathematic model for traditional control method.
文摘This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.
基金supported in part by the National Program on Key Basic Research Project (No. 2013CB733103)the Program for New Century Excellent Talents in University (No. NCET-10-0058)
文摘This paper presents a novel hybrid task priority-based motion planning algorithm of a space robot. The satellite attitude control task is defined as the primary task, while the leastsquares-based non-strict task priority solution of the end-effector plus the multi-constraint task is viewed as the secondary task. Furthermore, a null-space task compensation strategy in the joint space is proposed to derive the combination of non-strict and strict task-priority motion planning,and this novel combination is termed hybrid task priority control. Thus, the secondary task is implemented in the primary task＇s null-space. Besides, the transition of the state of multiple constraints between activeness and inactiveness will only influence the end-effector task without any effect on the primary task. A set of numerical experiments made in a real-time simulation system under Linux/RTAI shows the validity and feasibility of the proposed methodology.
基金supported by the National Natural Science Foundation of China(62103039,62073030)the Scientific and Technological Innovation Foundation of Shunde Graduate School+8 种基金University of Science and Technology Beijing(USTB)(BK21BF003)the Korea Institute of Energy Technology Evaluation and Planning through the Auspices of the Ministry of TradeIndustry and EnergyRepublic of Korea(20213030020160)the Science and Technology Planning Project of Guangzhou City(202102010398,202201010758)the Guangzhou University-Hong Kong University of Science and Technology Joint Research Collaboration Fund(YH202205)Beijing Top Discipline for Artificial Intelligent Science and EngineeringUniversity of Science and Technology Beijing。
文摘This paper presents a dynamic model and performance constraint control of a line-driven soft robotic arm.The dynamics model of the soft robotic arm is established by combining the screw theory and the Cosserat theory.The unmodeled dynamics of the system are considered,and an adaptive neural network controller is designed using the backstepping method and radial basis function neural network.The stability of the closed-loop system and the boundedness of the tracking error are verified using Lyapunov theory.The simulation results show that our approach is a good solution to the motion constraint problem of the line-driven soft robotic arm.
基金Project(61473304)supported by the National Natural Science Foundation of ChinaProject(2015AA042202)supported by Hi-tech Research and Development Program of China
文摘A compliant landing strategy for a trotting quadruped robot on unknown rough terrains based on contact force control is presented. Firstly, in order to lower the disturbance caused by the landing impact force, a landing phase is added between the swing phase and the stance phase, where the desired contact force is set as a small positive constant. Secondly, the joint torque optimization of the stance legs is formulated as a quadratic programming(QP) problem subject to equality and inequality/bound constraints. And a primal-dual dynamical system solver based on linear variational inequalities(LVI) is applied to solve this QP problem. Furthermore, based on the optimization results, a hybrid motion/force robust controller is designed to realize the tracking of the contact force, while the constraints of the stance feet landing angles are fulfilled simultaneously. Finally, the experiments are performed to validate the proposed methods.
基金the National Natural Science Foundation of China (Nos. 10672040 and10372022)the Natural Science Foundation of Fujian Province of China (No. E0410008)
文摘Control of coordinated motion between the base attitude and the arm joints of a free-floating dual-arm space robot with uncertain parameters is discussed. By combining the relation of system linear momentum conversation with the Lagrangian approach, the dynamic equation of a robot is established. Based on the above results, the free-floating dual-arm space robot system is modeled with RBF neural networks, the GL matrix and its product operator. With all uncertain inertial system parameters, an adaptive RBF neural network control scheme is developed for coordinated motion between the base attitude and the arm joints. The proposed scheme does not need linear parameterization of the dynamic equation of the system and any accurate prior-knowledge of the actual inertial parameters. Also it does not need to train the neural network offline so that it would present real-time and online applications. A planar free-floating dual-arm space robot is simulated to show feasibility of the proposed scheme.
基金This work was supported by the National Natural Science Foundation of China(Grant No.61573185)JiangSu Scientific Support Program of China(Grant No.BE2010190).
文摘Aircraft skin health concerns whether the aircraft can fly safely.In this paper,an improved mechanical structure of the aircraft skin inspection robot was introduced.Considering that the aircraft skin surface is a curved environment,we assume that the curved environment is equivalent to an inclined plane with a change in inclination.Based on this assumption,the Cartesian dynamics model of the robot is established using the Lagrange method.In order to control the robot’s movement position accurately,a position backstepping control scheme for the aircraft skin inspection robot was presented.According to the dynamic model and taking into account the problems faced by the robot during its movement,a position constrained controller of the aircraft skin inspection robot is designed using the barrier Lyapunov function.Aiming at the disturbances in the robot,we adopt a fuzzy system to approximate the unknown dynamics related with system states.Finally,the simulation results of the designed position constrained controller were compared with the sliding mode controller,and prove the validity of the position constrained controller.
文摘Robotic manipulators are widely used in applications that require fast and precise motion.Such devices,however,are prompt to nonlinear control issues due to the flexibility in joints and the friction in the motors within the dynamics of their rigid part.To address these issues,the Linear Matrix Inequalities(LMIs)and Parallel Distributed Compensation(PDC)approaches are implemented in the Takagy–Sugeno Fuzzy Model(T-SFM).We propose the following methodology;initially,the state space equations of the nonlinear manipulator model are derived.Next,a Takagy–Sugeno Fuzzy Model(T-SFM)technique is used for linearizing the state space equations of the nonlinear manipulator.The T-SFM controller is developed using the Parallel Distributed Compensation(PDC)method.The prime concept of the designed controller is to compensate for all the fuzzy rules.Furthermore,the Linear Matrix Inequalities(LMIs)are applied to generate adequate cases to ensure stability and control.Convex programming methods are applied to solve the developed LMIs problems.Simulations developed for the proposed model show that the proposed controller stabilized the system with zero tracking error in less than 1.5 s.
文摘A practical motion control strategy for a radio-controlled, 4-link and free-swimmingbiomimetic robot fish is presented. Based on control performance of the fish the fish s motion controltask is decomposed into on-line speed control and orientation control. The speed control algorithm isimplemented by using piecewise control, and orientation control is realized by fuzzy logic. Combiningwith step control and fuzzy control, a point-to-point (PTP) control algorithm is proposed and appliedto the closed-loop experimental system that uses a vision-based position sensing subsystem to providefeedback. Experiments confirm the reliability and e?ectiveness of the presented algorithms.
文摘Taking a six-DOF hydraulic parallel experimental robot designed and manufactured by the authors as the object of study, we researched the track plan, special track producing method, place(position) and velocity control algorithm of parallel robot,etc. All researches have been verified by experimental prototype.
