Precise control of the contact force is crucial in the application of non-wearable defecation smart care(DSC)robot.A deformable shield equipped with a pressure sensing function is designed,with a bending angle that ca...Precise control of the contact force is crucial in the application of non-wearable defecation smart care(DSC)robot.A deformable shield equipped with a pressure sensing function is designed,with a bending angle that can be adjusted according to pressure feedback,thus enabling it to adapt to various body shapes.To improve the force tracking accuracy and prevent obvious force overshoot in the initial contact stage,a contact force control strategy based on fuzzy adaptive variable impedance is proposed.The proposed contact force control strategy achieves an average root-mean-square error of 0.024 and an average overshoot of 1.74%.Experimental results demonstrate that the designed deformable shield can fit the human body well,while the proposed control strategy enhances the contact force management and realizes the precise control of human-robot contact force.展开更多
This paper presents a learning-based control framework for fast(<1.5 s)and accurate manipulation of a flexible object,i.e.,whip targeting.The framework consists of a motion planner learned or optimized by an algori...This paper presents a learning-based control framework for fast(<1.5 s)and accurate manipulation of a flexible object,i.e.,whip targeting.The framework consists of a motion planner learned or optimized by an algorithm,Online Impedance Adaptation Control(OIAC),a sim2real mechanism,and a visual feedback component.The experimental results show that a soft actor-critic algorithm outperforms three Deep Reinforcement Learning(DRL),a nonlinear optimization,and a genetic algorithm in learning generalization of motion planning.It can greatly reduce average learning trials(to<20 of others)and maximize average rewards(to>3 times of others).Besides,motion tracking errors are greatly reduced to 13.29 and 22.36 of constant impedance control by the OIAC of the proposed framework.In addition,the trajectory similarity between simulated and physical whips is 89.09.The presented framework provides a new method integrating data-driven and physics-based algorithms for controlling fast and accurate arm manipulation of a flexible object.展开更多
Continuum manipulators can conform to curvilinear paths and manipulate objects in complex environments,which makes it emerging to be applied in minimally invasive surgery(MIS).However,different and controllable operat...Continuum manipulators can conform to curvilinear paths and manipulate objects in complex environments,which makes it emerging to be applied in minimally invasive surgery(MIS).However,different and controllable operating stiffness of the continuum manipulator is required during different stages of surgery to achieve safe access or stable and precise operation.This work proposes an operating stiffness controller(OSC)for the typical tendon-driven continuum manipulator based on the variable impedance control method with Lagrangian dynamic modeling.This controller can adjust the operating stiffness by modifying the driving forces along the driving tendons of the continuum manipulator without changing its material or structure.The proposed OSC converts the damping and stiffness matrices of the impedance control into variable parameters.This merit allows it to dynamically adjust the operating stiffness of the continuum manipulator according to the desired constant or time-varying stiffness.Furthermore,the OSC stability can be proven based on a Lyapunov function,and its stiffness control performances have been analyzed and evaluated in both simulations and experiments.The OSC controller generated average relevant error values of 7.82%and 3.09%for the operating stiffness control experiments with constant and time-varying desired stiffness,respectively.These experimental results indicate that the OSC has high accuracy,stability,and strong robustness in the operating stiffness control tasks.展开更多
Recent demographic shifts,including global population aging and rising disability prevalence,have significantly increased demand for robot-assisted rehabilitation technologies.These systems enable repetitive motor tra...Recent demographic shifts,including global population aging and rising disability prevalence,have significantly increased demand for robot-assisted rehabilitation technologies.These systems enable repetitive motor training to enhance neuromuscular recovery and functional mobility.This study presents an assist-as-needed(AAN)control framework featuring a performance assessment index derived from dynamic similarity metrics between actual and reference velocity trajectories,along with adaptive impedance modulation based on real-time patient performance evaluation.A higher index indicates greater patient ability,prompting the robot to apply resistance to augment task difficulty and training efficacy.Conversely,a low index suggests an unexpected situation,prompting the robot to become fully compliant to prevent injury.In intermediate scenarios,the robot either provides assistance to facilitate task completion or withholds assistance to encourage greater patient initiative.Additionally,a Lyapunov function is proposed to evaluate the stability of the AAN strategy,which confirms the bounded-input-bounded-output stability of the closed-loop system.Experimental outcomes demonstrate the efficacy of the proposed framework in dynamically adjusting assistance levels to meet patient needs during robot-assisted therapy sessions.展开更多
Variable Impedance control allows robots and humans to safely and efficiently interact with unknown external environments.This tutorial introduces online impedance adaptation control(OIAC)for variable compliant joint ...Variable Impedance control allows robots and humans to safely and efficiently interact with unknown external environments.This tutorial introduces online impedance adaptation control(OIAC)for variable compliant joint motions in a range of control tasks:rapid(<1 s)movement control(i.e.,whipping to hit),arm and finger impedance quantification,multifunctional exoskeleton control,and robot-inspired human arm control hypothesis.The OIAC has been introduced as a feedback control,which can be integrated into a feedforward control,e.g.,learned by data-driven methods.This integration facilitates the understanding of human and robot arm control,closing a research loop between biomechanics and robotics.It shows not only a research way from biomechanics to robotics,but also another reserved one.This tutorial aims at presenting research examples and Python codes for advancing the understanding of variable impedance adaptation in human and robot motor control.It contributes to the state-of-the-art by providing an online impedance adaptation controller for wearable robots(i.e.,exoskeletons)which can be used in robotic and biomechanical applications.展开更多
基金supported by grants from the National Key R and D Program of China(2022YFB4703300).
文摘Precise control of the contact force is crucial in the application of non-wearable defecation smart care(DSC)robot.A deformable shield equipped with a pressure sensing function is designed,with a bending angle that can be adjusted according to pressure feedback,thus enabling it to adapt to various body shapes.To improve the force tracking accuracy and prevent obvious force overshoot in the initial contact stage,a contact force control strategy based on fuzzy adaptive variable impedance is proposed.The proposed contact force control strategy achieves an average root-mean-square error of 0.024 and an average overshoot of 1.74%.Experimental results demonstrate that the designed deformable shield can fit the human body well,while the proposed control strategy enhances the contact force management and realizes the precise control of human-robot contact force.
基金supported in part by the Brødrene Hartmanns(No.A36775)Thomas B.Thriges(No.7648-2106)+1 种基金Fabrikant Mads Clausens(No.2023-0210)EnergiFyn funds.
文摘This paper presents a learning-based control framework for fast(<1.5 s)and accurate manipulation of a flexible object,i.e.,whip targeting.The framework consists of a motion planner learned or optimized by an algorithm,Online Impedance Adaptation Control(OIAC),a sim2real mechanism,and a visual feedback component.The experimental results show that a soft actor-critic algorithm outperforms three Deep Reinforcement Learning(DRL),a nonlinear optimization,and a genetic algorithm in learning generalization of motion planning.It can greatly reduce average learning trials(to<20 of others)and maximize average rewards(to>3 times of others).Besides,motion tracking errors are greatly reduced to 13.29 and 22.36 of constant impedance control by the OIAC of the proposed framework.In addition,the trajectory similarity between simulated and physical whips is 89.09.The presented framework provides a new method integrating data-driven and physics-based algorithms for controlling fast and accurate arm manipulation of a flexible object.
基金supported in part by Technology Program Project of Shaoxing City under grant 2023A14016the National Natural Science Foundation of China under grants 62211530111 and 92148201+1 种基金Science and Royal Society under IEC\NSFC\211360Graduate Research Innovation Project by Tianjin Education Commission under grant 2022BKY075.
文摘Continuum manipulators can conform to curvilinear paths and manipulate objects in complex environments,which makes it emerging to be applied in minimally invasive surgery(MIS).However,different and controllable operating stiffness of the continuum manipulator is required during different stages of surgery to achieve safe access or stable and precise operation.This work proposes an operating stiffness controller(OSC)for the typical tendon-driven continuum manipulator based on the variable impedance control method with Lagrangian dynamic modeling.This controller can adjust the operating stiffness by modifying the driving forces along the driving tendons of the continuum manipulator without changing its material or structure.The proposed OSC converts the damping and stiffness matrices of the impedance control into variable parameters.This merit allows it to dynamically adjust the operating stiffness of the continuum manipulator according to the desired constant or time-varying stiffness.Furthermore,the OSC stability can be proven based on a Lyapunov function,and its stiffness control performances have been analyzed and evaluated in both simulations and experiments.The OSC controller generated average relevant error values of 7.82%and 3.09%for the operating stiffness control experiments with constant and time-varying desired stiffness,respectively.These experimental results indicate that the OSC has high accuracy,stability,and strong robustness in the operating stiffness control tasks.
基金supported by the National Key Research&Development Program of China(Grant No.2024YFB4709901)the National Natural Science Foundation of China(Grant No.62333023)+4 种基金Beijing Municipal Natural Science Foundation(Grant Nos.F2024201068,L243014,L232061)Beijing Nova Program(Grant No.20230484400)CAS Project for Young Scientists in Basic Research(Grant No.YSBR-034)74th China Postdoctoral Science Foundation(Grant No.2024M753499)the 2023 Postdoctoral Researchers Funding Program(Grant No.GZC20232997)。
文摘Recent demographic shifts,including global population aging and rising disability prevalence,have significantly increased demand for robot-assisted rehabilitation technologies.These systems enable repetitive motor training to enhance neuromuscular recovery and functional mobility.This study presents an assist-as-needed(AAN)control framework featuring a performance assessment index derived from dynamic similarity metrics between actual and reference velocity trajectories,along with adaptive impedance modulation based on real-time patient performance evaluation.A higher index indicates greater patient ability,prompting the robot to apply resistance to augment task difficulty and training efficacy.Conversely,a low index suggests an unexpected situation,prompting the robot to become fully compliant to prevent injury.In intermediate scenarios,the robot either provides assistance to facilitate task completion or withholds assistance to encourage greater patient initiative.Additionally,a Lyapunov function is proposed to evaluate the stability of the AAN strategy,which confirms the bounded-input-bounded-output stability of the closed-loop system.Experimental outcomes demonstrate the efficacy of the proposed framework in dynamically adjusting assistance levels to meet patient needs during robot-assisted therapy sessions.
基金supported by the Human Frontier Science Program(RGP0002/2017)the BrØrene Hartmanns Fund(A36775)the Thomas B.Thriges Fund(7648-2106).
文摘Variable Impedance control allows robots and humans to safely and efficiently interact with unknown external environments.This tutorial introduces online impedance adaptation control(OIAC)for variable compliant joint motions in a range of control tasks:rapid(<1 s)movement control(i.e.,whipping to hit),arm and finger impedance quantification,multifunctional exoskeleton control,and robot-inspired human arm control hypothesis.The OIAC has been introduced as a feedback control,which can be integrated into a feedforward control,e.g.,learned by data-driven methods.This integration facilitates the understanding of human and robot arm control,closing a research loop between biomechanics and robotics.It shows not only a research way from biomechanics to robotics,but also another reserved one.This tutorial aims at presenting research examples and Python codes for advancing the understanding of variable impedance adaptation in human and robot motor control.It contributes to the state-of-the-art by providing an online impedance adaptation controller for wearable robots(i.e.,exoskeletons)which can be used in robotic and biomechanical applications.
