Rehabilitation is the most effective way to reduce motor impairments in post-stroke patients.This process demands several hours with a specialized therapist.Given resources and personnel shortages,the literature repor...Rehabilitation is the most effective way to reduce motor impairments in post-stroke patients.This process demands several hours with a specialized therapist.Given resources and personnel shortages,the literature reports a high interest in robotic assisted rehabilitation solutions.Recently,cable-driven robotic architectures are attracting significant research interest for post-stroke rehabilitation.However,the existing cable-driven robots are mostly unilateral devices allowing the rehabilitation only of the most affected limb.This leaves unaddressed the rehabilitation of bimanual activities,which are predominant within the common Activities of Daily Living(ADL).Thus,this paper presents a specific novel design to achieve bimanual rehabilitation tasks that has been named as BiCAR robot.Specifically,this paper provides a full insight on the BiCAR system as well as on its dedicated developed software BiEval.In particular,BiEval software has been developed as based on a serious game strategy and a virtual reality environment to track the patient exercising duration,motion ranges,speeds,and forces over time for achieving a quantitative assessment of the rehabilitation progress.Finally,the paper presents the BiCAR/BiEval capabilities by referring to a pilot Randomized Controlled Trial(RCT).The clinical trials have been used to validate the BiCAR/BiEval in terms of engineering feasibility and user acceptance to achieve an innovative cost-oriented integrated hardware/software device for the bimanual assistive rehabilitation of post-stroke patients.展开更多
Cable-driven parallel robots(CDPRs)have advantages of larger workspace and load capacity than conventional parallel robots while existing interference problems among cables,workpieces and the end-effector.In order to ...Cable-driven parallel robots(CDPRs)have advantages of larger workspace and load capacity than conventional parallel robots while existing interference problems among cables,workpieces and the end-effector.In order to avoid collision and improve the flexibility of the robots,this study proposes a reconfigurable cable-driven parallel robot(RCDPR)having characteristics of large load-to-weight ratio,easy modularity and variable stiffness.Adjustable brackets are connected to the moving platform to adjust the position of the pull-out point with the movement of the end-effector.In addition,a variable stiffness actuator(VSA)accompanied by finite element analysis is designed to optimize the cable tension to adapt different task requirements.Firstly,a new idea of reconfiguration is given,and an inverse kinematic model is established using the vector closure principle to derive its inverse kinematic expressions focusing on one of the configurations.Second,the VSA is attached to each cable to achieve stiffness adjustment,and the system stiffness is derived in detail.Finally,the rationality and accuracy of the robot are verified through numerical analysis,providing a reference for subsequent trajectory planning with implications.展开更多
Single-cell biomechanics and electrophysiology measuring tools have transformed biological research over the last few decades,which enabling a comprehensive and nuanced understanding of cellular behavior and function....Single-cell biomechanics and electrophysiology measuring tools have transformed biological research over the last few decades,which enabling a comprehensive and nuanced understanding of cellular behavior and function.Despite their high-quality information content,these single-cell measuring techniques suffer from laborious manual processing by highly skilled workers and extremely low throughput(tens of cells per day).Recently,numerous researchers have automated the measurement of cell mechanical and electrical signals through robotic localization and control processes.While these efforts have demonstrated promising progress,critical challenges persist,including human dependency,learning complexity,in-situ measurement,and multidimensional signal acquisition.To identify key limitations and highlight emerging opportunities for innovation,in this review,we comprehensively summarize the key steps of robotic technologies in single-cell biomechanics and electrophysiology.We also discussed the prospects and challenges of robotics and automation in biological research.By bridging gaps between engineering,biology,and data science,this work aims to stimulate interdisciplinary research and accelerate the translation of robotic single-cell technologies into practical applications in the life sciences and medical fields.展开更多
Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challeng...Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challenge due to factors such as light scattering,absorption,restricted visibility,and ambient noise.The advancement of deep learning has introduced powerful techniques for processing large amounts of unstructured and imperfect data collected from underwater environments.This study evaluated the efficacy of the You Only Look Once(YOLO)algorithm,a real-time object detection and localization model based on convolutional neural networks,in identifying and classifying various types of pipeline defects in underwater settings.YOLOv8,the latest evolution in the YOLO family,integrates advanced capabilities,such as anchor-free detection,a cross-stage partial network backbone for efficient feature extraction,and a feature pyramid network+path aggregation network neck for robust multi-scale object detection,which make it particularly well-suited for complex underwater environments.Due to the lack of suitable open-access datasets for underwater pipeline defects,a custom dataset was captured using a remotely operated vehicle in a controlled environment.This application has the following assets available for use.Extensive experimentation demonstrated that YOLOv8 X-Large consistently outperformed other models in terms of pipe defect detection and classification and achieved a strong balance between precision and recall in identifying pipeline cracks,rust,corners,defective welds,flanges,tapes,and holes.This research establishes the baseline performance of YOLOv8 for underwater defect detection and showcases its potential to enhance the reliability and efficiency of pipeline inspection tasks in challenging underwater environments.展开更多
Multi-link cable-driven robots(MCDRs)have potential advantages in confined spaces exploration because of their redundancy and flexibility.Operational space wrench and acceleration capability analysis of MCDRs is impor...Multi-link cable-driven robots(MCDRs)have potential advantages in confined spaces exploration because of their redundancy and flexibility.Operational space wrench and acceleration capability analysis of MCDRs is important for their design,manipulability optimization,and motion planning.However,existing works mainly focus on capability analysis in the joint space.In this paper,we present a zonotope-based iterative method and a simplified capability zonotope to analyze the operational-space wrench and acceleration capability of MCDRs.In the iterative method,the capability generated by some cables can be iteratively added to the initial capability zonotope based on the Minkowski sum.In the simplified zonotope capability representation,a threshold is put forward to reduce redundant vertices and faces with little volume loss.Finally,simulations on a 24 DOFs MCDR are performed to verify the effectiveness of the developed method.The results demonstrate that our iterative algorithm can easily generate the capability zonotope with a few MB ROM,while traditional operational wrench capability evaluation without our iterative algorithm needs 18432 GB ROM.Furthermore,our simplified representation reduces the vertices and faces from 1260 and 2516 to 88 and 172,respectively,but with only 3.3%volume loss,which decreases the constraints of the robot and is conducive to manipulability optimization and motion planning.展开更多
Cable-driven parallel robots(CDPRs) are categorized as a type of parallel manipulators. In CDPRs, flexible cables are used to take the place of rigid links. The particular property of cables provides CDPRs several adv...Cable-driven parallel robots(CDPRs) are categorized as a type of parallel manipulators. In CDPRs, flexible cables are used to take the place of rigid links. The particular property of cables provides CDPRs several advantages, including larger workspaces, higher payload-to-weight ratio and lower manufacturing costs rather than rigid-link robots. In this paper, the history of the development of CDPRs is introduced and several successful latest application cases of CDPRs are presented. The theory development of CDPRs is introduced focusing on design, performance analysis and control theory. Research on CDPRs gains wide attention and is highly motivated by the modern engineering demand for large load capacity and workspace. A number of exciting advances in CDPRs are summarized in this paper since it is proposed in the 1980 s, which points to a fruitful future both in theory and application. In order to meet the increasing requirements of robot in different areas, future steps foresee more in-depth research and extension applications of CDPRs including intelligent control, composite materials, integrated and reconfigurable design.展开更多
This article introduces a cable-driven lower limb rehabilitation robot with movable distal anchor points(M-CDLR).The traditional cable-driven parallel robots(CDPRs)control the moving platform by changing the length of...This article introduces a cable-driven lower limb rehabilitation robot with movable distal anchor points(M-CDLR).The traditional cable-driven parallel robots(CDPRs)control the moving platform by changing the length of cables,M-CDLR can also adjust the position of the distal anchor point when the moving platform moves.The M-CDLR this article proposed has gait and single-leg training modes,which correspond to the plane and space motion of the moving platform,respectively.After introducing the system structure configuration,the generalized kinematics and dynamics of M-CDLR are established.The fully constrained CDPRs can provide more stable rehabilitation training than the under-constrained one but requires more cables.Therefore,a motion planning method for the movable distal anchor point of M-CDLR is proposed to realize the theoretically fully constrained with fewer cables.Then the expected trajectory of the moving platform is obtained from the motion capture experiment,and the motion planning of M-CDLR under two training modes is simulated.The simulation results verify the effectiveness of the proposed motion planning method.This study serves as a basic theoretical study of the structure optimization and control strategy of M-CDLR.展开更多
An assessment of the human motion repeatability for three selected Activities of Daily Living(ADL)is performed in this paper.These exercises were prescribed by an occupational therapist for the upper limb rehabilitati...An assessment of the human motion repeatability for three selected Activities of Daily Living(ADL)is performed in this paper.These exercises were prescribed by an occupational therapist for the upper limb rehabilitation.The movement patterns of five participants,recorded using a Qualisys motion capture system,are compared based on the Analysis of Variance(ANOVA)method.This survey is motivated by the need to find the appropriate task workspace of a 6-degrees of freedom cable-driven parallel robot for upper limb rehabilitation,which is able to reproduce the three selected exercises.This comparison is performed to justify,whether or not,there is enough similarity between the participants’gestures,and so a single reference trajectory can be adopted as the robot-prescribed workspace.Using the results of the comparative study,an optimization process of the sought robot design is carried out,where the structure size and the cable tensions simultaneously minimized.展开更多
The use of space robots(SRs)for on-orbit services(OOSs)has been a hot research topic in recent years.However,the space unstructured environment(i.e.:confined spaces,multiple obstacles,and strong radiation interference...The use of space robots(SRs)for on-orbit services(OOSs)has been a hot research topic in recent years.However,the space unstructured environment(i.e.:confined spaces,multiple obstacles,and strong radiation interference)has greatly restricted the application of SRs.The coupled active-passive multilink cable-driven space robot(CAP-MCDSR)has the characteristics of slim body,flexible movement,and electromechanical separation,which is very suitable for extreme space environments.However,the dynamic and stiffness modeling of CAP-MCDSRs is challenging,due to the complex coupling among the active cables,passive cables,joints,and the end-effector.To deal with these problems,this paper proposes a workspace,stiffness analysis and design optimization method for such type of MCDSRs.Firstly,the multi-coupling kinematics relationships among the joint,cables and the end-effector are established.Based on hybrid series-parallel characteristics,the improved coupled active–passive(CAP)dynamic equation is derived.Then,the maximum workspace,the maximum stiffness,and the minimum cable tension are resolved,among them,the overall stiffness is the superposition of the stiffness produced by the active and the passive cable.Furthermore,the workspace,the stiffness,and the cable tension are analyzed by using the nonlinear optimization method(NOPM).Finally,an 8-DOF CAP-MCDSR experiment system is built to verify the proposed modeling and trajectory tracking methods.The proposed modeling and analysis results are very useful for practical space applications,such as designing a new CAP-MCDSR,or utilizing an existing CAP-MCDSR system.展开更多
The number of people with abnormal gait in China has been increasing for years.Compared with traditional methods,lower limb rehabilitation robots which address problems such as longstanding human guidance may cause fa...The number of people with abnormal gait in China has been increasing for years.Compared with traditional methods,lower limb rehabilitation robots which address problems such as longstanding human guidance may cause fatigue,and the training is lacking scientific and intuitive monitoring data.However,typical rigid rehabilitation robots are always meeting drawbacks like the enormous weight,the limitation of joint movement,and low comfort.The purpose of this research is to design a cable-driven flexible exoskeleton robot to assist in rehabilitation training of patients who have abnormal gait due to low-level hemiplegia or senility.The system consists of a PC terminal,a Raspberry Pi,and the actuator structure.Monitoring and training are realized through remote operation and interactive interface simultaneously.We designed an integrated and miniaturized driving control box.Inside the box,two driving cables on customized pulley-blocks with different radii can retract/release by one motor after transmitting the target position to the Raspberry Pi from the PC.The force could be transferred to the flexible suit to aid hip flexion and ankle plantar flexion.Furthermore,the passive elastic structure was intended to assist ankle dorsiflexion.We also adopted the predictable admittance controller,which uses the Prophet algorithm to predict the changes in the next five gait cycles from the current ankle angular velocity and obtain the ideal force curve through a functional relationship.The admittance controller can realize the desired force following.Finally,we finished the performance test and the human-subject experiment.Experimental data indicate that the exoskeleton can meet the basic demand of multi-joint assistance and improve abnormal postures.Meanwhile,it can increase the range of joint rotation and eliminate asymmetrical during walking.展开更多
Robot-assisted laparoscopic radical prostatectomy(RARP)is widely used to treat prostate cancer.The rigid instruments primarily used in RARP cannot overcome the problem of blind areas in surgery and lead to more trauma...Robot-assisted laparoscopic radical prostatectomy(RARP)is widely used to treat prostate cancer.The rigid instruments primarily used in RARP cannot overcome the problem of blind areas in surgery and lead to more trauma such as more incision for the passage of the instrument and additional tissue damage caused by rigid instruments.Soft robots are relatively fexible and theoretically have infinite degrees of freedom which can overcome the problem of the rigid instrument.A soft robot system for single-port transvesical robot-assisted radical prostatectomy(STvRARP)is developed in this study.The soft manipulator with 10 mm in diameter and a maximum bending angle of 270°has good fexibility and dexterity.The design and mechanical structure of the soft robot are described.The kinematics of the soft manipulator is established and the inverse kinematics is compensated based on the characteristics of the designed soft manipulator.The master-slave control system of soft robot for surgery is built and the feasibility of the designed soft robot is verified.展开更多
Extensively studied since the early nineties,cable-driven robots have attracted the growing interest of the industrial and scientific community due to their desirable and peculiar attributes.In particular,underconstra...Extensively studied since the early nineties,cable-driven robots have attracted the growing interest of the industrial and scientific community due to their desirable and peculiar attributes.In particular,underconstrained and planar cable robots can find application in several fields,and specifically,in the packaging industry.The planning of dynamically feasible trajectories(i.e.,trajectories along which cable slackness and excessive tensions are avoided) is particularly challenging when dealing with such a topology of cable robots,which rely on gravity to maintain their cables in tension.This paper,after stressing the current relevance of cable robots,presents an extension and a generalization of a model-based method developed to translate typical cable tension bilateral bounds into intuitive limits on the velocity and acceleration of the robot end effector along a prescribed path.Such a new formulation of the method is based on a parametric expression of cable tensions.The computed kinematic limits can then be incorporated into any trajectory planning algorithm.The method is developed with reference to a hybrid multi-body cable robot topology which can be functionally advantageous but worsen the problem of keeping feasible tensions in the cables both in static and dynamic conditions.The definition of statically feasible workspace is also introduced to identify the positions where static equilibrium can be maintained with feasible tensions.Finally,some aspects related to the practical implementation of the method are discussed.展开更多
Cable-driven parallel robots(CDPRs)use cables instead of the rigid limbs of traditional parallel robots,thus processing a large potential workspace,easy to assemble and disassemble characteristics,and with application...Cable-driven parallel robots(CDPRs)use cables instead of the rigid limbs of traditional parallel robots,thus processing a large potential workspace,easy to assemble and disassemble characteristics,and with applications in numerous fields.However,owing to the influence of cable flexibility and nonlinear friction,model uncertainties are di cult to eliminate from the control design.Hence,in this study,the model uncertainties of CDPRs are first analyzed based on a brief introduction to related research.Control strategies for CDPRs with model uncertainties are then reviewed.The advantages and disadvantages of several control strategies for CDPRS are discussed through traditional control strategies with kinematic and dynamic uncertainties.Compared with these traditional control strategies,deep reinforcement learning and model predictive control have received widespread attention in recent years owing to their model independence and recursive feasibility with constraint limits.A comprehensive review and brief analysis of current advances in these two control strategies for CDPRs with model uncertainties are presented,concluding with discussions regarding development directions.展开更多
Cable-driven soft robots exhibit complex deformations,making state estimation challenging.Hence,this paper develops a multi-sensor fusion approach using a gradient descent strategy to estimate the weighting coefficien...Cable-driven soft robots exhibit complex deformations,making state estimation challenging.Hence,this paper develops a multi-sensor fusion approach using a gradient descent strategy to estimate the weighting coefficients.These coefficients combine measurements from proprioceptive sensors,such as resistive flex sensors,to determine the bending angle.Additionally,the fusion strategy adopted provides robust state estimates,overcoming mismatches between the flex sensors and soft robot dimensions.Furthermore,a nonlinear differentiator is introduced to filter the differentiated sensor signals to address noise and irrational values generated by the Analog-to-Digital Converter.A rational polynomial equation is also introduced to compensate for temperature drift exhibited by the resistive flex sensors,which affect the accuracy of state estimation and control.The processed multi-sensor data is then utilized in an improved PD controller for closed-loop control of the soft robot.The controller incorporates the nonlinear differentiator and drift compensation,enhancing tracking performance.Experimental results validate the effectiveness of the integrated approach,demonstrating improved tracking accuracy and robustness compared to traditional PD controllers.展开更多
Large language models(LLMs)have undergone significant expansion and have been increasingly integrated across various domains.Notably,in the realm of robot task planning,LLMs harness their advanced reasoning and langua...Large language models(LLMs)have undergone significant expansion and have been increasingly integrated across various domains.Notably,in the realm of robot task planning,LLMs harness their advanced reasoning and language comprehension capabilities to formulate precise and efficient action plans based on natural language instructions.However,for embodied tasks,where robots interact with complex environments,textonly LLMs often face challenges due to a lack of compatibility with robotic visual perception.This study provides a comprehensive overview of the emerging integration of LLMs and multimodal LLMs into various robotic tasks.Additionally,we propose a framework that utilizes multimodal GPT-4V to enhance embodied task planning through the combination of natural language instructions and robot visual perceptions.Our results,based on diverse datasets,indicate that GPT-4V effectively enhances robot performance in embodied tasks.This extensive survey and evaluation of LLMs and multimodal LLMs across a variety of robotic tasks enriches the understanding of LLM-centric embodied intelligence and provides forward-looking insights towards bridging the gap in Human-Robot-Environment interaction.展开更多
基金partially funded by UFU,FAPEMIG,CNPQ,and CAPES(Finance Code 001).
文摘Rehabilitation is the most effective way to reduce motor impairments in post-stroke patients.This process demands several hours with a specialized therapist.Given resources and personnel shortages,the literature reports a high interest in robotic assisted rehabilitation solutions.Recently,cable-driven robotic architectures are attracting significant research interest for post-stroke rehabilitation.However,the existing cable-driven robots are mostly unilateral devices allowing the rehabilitation only of the most affected limb.This leaves unaddressed the rehabilitation of bimanual activities,which are predominant within the common Activities of Daily Living(ADL).Thus,this paper presents a specific novel design to achieve bimanual rehabilitation tasks that has been named as BiCAR robot.Specifically,this paper provides a full insight on the BiCAR system as well as on its dedicated developed software BiEval.In particular,BiEval software has been developed as based on a serious game strategy and a virtual reality environment to track the patient exercising duration,motion ranges,speeds,and forces over time for achieving a quantitative assessment of the rehabilitation progress.Finally,the paper presents the BiCAR/BiEval capabilities by referring to a pilot Randomized Controlled Trial(RCT).The clinical trials have been used to validate the BiCAR/BiEval in terms of engineering feasibility and user acceptance to achieve an innovative cost-oriented integrated hardware/software device for the bimanual assistive rehabilitation of post-stroke patients.
基金Supported by National Natural Science Foundation of China(Grant Nos.52335002,52205014,52275033)the Fundamental Research Funds for the Central Universities(Grant No.JZ2024HGTB0245).
文摘Cable-driven parallel robots(CDPRs)have advantages of larger workspace and load capacity than conventional parallel robots while existing interference problems among cables,workpieces and the end-effector.In order to avoid collision and improve the flexibility of the robots,this study proposes a reconfigurable cable-driven parallel robot(RCDPR)having characteristics of large load-to-weight ratio,easy modularity and variable stiffness.Adjustable brackets are connected to the moving platform to adjust the position of the pull-out point with the movement of the end-effector.In addition,a variable stiffness actuator(VSA)accompanied by finite element analysis is designed to optimize the cable tension to adapt different task requirements.Firstly,a new idea of reconfiguration is given,and an inverse kinematic model is established using the vector closure principle to derive its inverse kinematic expressions focusing on one of the configurations.Second,the VSA is attached to each cable to achieve stiffness adjustment,and the system stiffness is derived in detail.Finally,the rationality and accuracy of the robot are verified through numerical analysis,providing a reference for subsequent trajectory planning with implications.
基金the National Natural Science Foundation of China[62525301,62127811,62433019]the New Cornerstone Science Foundation through the XPLORER PRIZEthe financial support by the China Postdoctoral Science Foundation[GZB20240797].
文摘Single-cell biomechanics and electrophysiology measuring tools have transformed biological research over the last few decades,which enabling a comprehensive and nuanced understanding of cellular behavior and function.Despite their high-quality information content,these single-cell measuring techniques suffer from laborious manual processing by highly skilled workers and extremely low throughput(tens of cells per day).Recently,numerous researchers have automated the measurement of cell mechanical and electrical signals through robotic localization and control processes.While these efforts have demonstrated promising progress,critical challenges persist,including human dependency,learning complexity,in-situ measurement,and multidimensional signal acquisition.To identify key limitations and highlight emerging opportunities for innovation,in this review,we comprehensively summarize the key steps of robotic technologies in single-cell biomechanics and electrophysiology.We also discussed the prospects and challenges of robotics and automation in biological research.By bridging gaps between engineering,biology,and data science,this work aims to stimulate interdisciplinary research and accelerate the translation of robotic single-cell technologies into practical applications in the life sciences and medical fields.
文摘Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challenge due to factors such as light scattering,absorption,restricted visibility,and ambient noise.The advancement of deep learning has introduced powerful techniques for processing large amounts of unstructured and imperfect data collected from underwater environments.This study evaluated the efficacy of the You Only Look Once(YOLO)algorithm,a real-time object detection and localization model based on convolutional neural networks,in identifying and classifying various types of pipeline defects in underwater settings.YOLOv8,the latest evolution in the YOLO family,integrates advanced capabilities,such as anchor-free detection,a cross-stage partial network backbone for efficient feature extraction,and a feature pyramid network+path aggregation network neck for robust multi-scale object detection,which make it particularly well-suited for complex underwater environments.Due to the lack of suitable open-access datasets for underwater pipeline defects,a custom dataset was captured using a remotely operated vehicle in a controlled environment.This application has the following assets available for use.Extensive experimentation demonstrated that YOLOv8 X-Large consistently outperformed other models in terms of pipe defect detection and classification and achieved a strong balance between precision and recall in identifying pipeline cracks,rust,corners,defective welds,flanges,tapes,and holes.This research establishes the baseline performance of YOLOv8 for underwater defect detection and showcases its potential to enhance the reliability and efficiency of pipeline inspection tasks in challenging underwater environments.
基金the China National Key R&D Program(Grant No.2019YFB1311204)the Shanghai Jiao Tong University Scientific and Technological Innovation Funds。
文摘Multi-link cable-driven robots(MCDRs)have potential advantages in confined spaces exploration because of their redundancy and flexibility.Operational space wrench and acceleration capability analysis of MCDRs is important for their design,manipulability optimization,and motion planning.However,existing works mainly focus on capability analysis in the joint space.In this paper,we present a zonotope-based iterative method and a simplified capability zonotope to analyze the operational-space wrench and acceleration capability of MCDRs.In the iterative method,the capability generated by some cables can be iteratively added to the initial capability zonotope based on the Minkowski sum.In the simplified zonotope capability representation,a threshold is put forward to reduce redundant vertices and faces with little volume loss.Finally,simulations on a 24 DOFs MCDR are performed to verify the effectiveness of the developed method.The results demonstrate that our iterative algorithm can easily generate the capability zonotope with a few MB ROM,while traditional operational wrench capability evaluation without our iterative algorithm needs 18432 GB ROM.Furthermore,our simplified representation reduces the vertices and faces from 1260 and 2516 to 88 and 172,respectively,but with only 3.3%volume loss,which decreases the constraints of the robot and is conducive to manipulability optimization and motion planning.
基金Supported by National Natural Science Foundation of China(Grant Nos.51605126,51575150,91748109)
文摘Cable-driven parallel robots(CDPRs) are categorized as a type of parallel manipulators. In CDPRs, flexible cables are used to take the place of rigid links. The particular property of cables provides CDPRs several advantages, including larger workspaces, higher payload-to-weight ratio and lower manufacturing costs rather than rigid-link robots. In this paper, the history of the development of CDPRs is introduced and several successful latest application cases of CDPRs are presented. The theory development of CDPRs is introduced focusing on design, performance analysis and control theory. Research on CDPRs gains wide attention and is highly motivated by the modern engineering demand for large load capacity and workspace. A number of exciting advances in CDPRs are summarized in this paper since it is proposed in the 1980 s, which points to a fruitful future both in theory and application. In order to meet the increasing requirements of robot in different areas, future steps foresee more in-depth research and extension applications of CDPRs including intelligent control, composite materials, integrated and reconfigurable design.
基金funded by the National Natural Science Foundation of China,Grant Number:52175006.
文摘This article introduces a cable-driven lower limb rehabilitation robot with movable distal anchor points(M-CDLR).The traditional cable-driven parallel robots(CDPRs)control the moving platform by changing the length of cables,M-CDLR can also adjust the position of the distal anchor point when the moving platform moves.The M-CDLR this article proposed has gait and single-leg training modes,which correspond to the plane and space motion of the moving platform,respectively.After introducing the system structure configuration,the generalized kinematics and dynamics of M-CDLR are established.The fully constrained CDPRs can provide more stable rehabilitation training than the under-constrained one but requires more cables.Therefore,a motion planning method for the movable distal anchor point of M-CDLR is proposed to realize the theoretically fully constrained with fewer cables.Then the expected trajectory of the moving platform is obtained from the motion capture experiment,and the motion planning of M-CDLR under two training modes is simulated.The simulation results verify the effectiveness of the proposed motion planning method.This study serves as a basic theoretical study of the structure optimization and control strategy of M-CDLR.
基金supported by the"PHC Utiquc"program of the French Ministry of Foreign Affairs and Ministry of Higher Education,Research and Innovation and the Tunisian Ministry of Higher Education and Scientific Research.P.n°19G1121the support of the Erasmus+KA 107 program.
文摘An assessment of the human motion repeatability for three selected Activities of Daily Living(ADL)is performed in this paper.These exercises were prescribed by an occupational therapist for the upper limb rehabilitation.The movement patterns of five participants,recorded using a Qualisys motion capture system,are compared based on the Analysis of Variance(ANOVA)method.This survey is motivated by the need to find the appropriate task workspace of a 6-degrees of freedom cable-driven parallel robot for upper limb rehabilitation,which is able to reproduce the three selected exercises.This comparison is performed to justify,whether or not,there is enough similarity between the participants’gestures,and so a single reference trajectory can be adopted as the robot-prescribed workspace.Using the results of the comparative study,an optimization process of the sought robot design is carried out,where the structure size and the cable tensions simultaneously minimized.
基金supported by the National Natural Science Foundation of China(No.62103454)the Key-Area Research and Development Program of Guangdong Province(No.2020B1111010001)+3 种基金the Guangdong Basic and Applied Basic Research Foundation(No.2019A1515110680)the Shenzhen Municipal Basic Research Project for Natural Science Foundation(No.JCYJ20190806143408992)the Fundamental Research Funds for the Central Universities(No.2021qntd08)Sun Yat-sen University。
文摘The use of space robots(SRs)for on-orbit services(OOSs)has been a hot research topic in recent years.However,the space unstructured environment(i.e.:confined spaces,multiple obstacles,and strong radiation interference)has greatly restricted the application of SRs.The coupled active-passive multilink cable-driven space robot(CAP-MCDSR)has the characteristics of slim body,flexible movement,and electromechanical separation,which is very suitable for extreme space environments.However,the dynamic and stiffness modeling of CAP-MCDSRs is challenging,due to the complex coupling among the active cables,passive cables,joints,and the end-effector.To deal with these problems,this paper proposes a workspace,stiffness analysis and design optimization method for such type of MCDSRs.Firstly,the multi-coupling kinematics relationships among the joint,cables and the end-effector are established.Based on hybrid series-parallel characteristics,the improved coupled active–passive(CAP)dynamic equation is derived.Then,the maximum workspace,the maximum stiffness,and the minimum cable tension are resolved,among them,the overall stiffness is the superposition of the stiffness produced by the active and the passive cable.Furthermore,the workspace,the stiffness,and the cable tension are analyzed by using the nonlinear optimization method(NOPM).Finally,an 8-DOF CAP-MCDSR experiment system is built to verify the proposed modeling and trajectory tracking methods.The proposed modeling and analysis results are very useful for practical space applications,such as designing a new CAP-MCDSR,or utilizing an existing CAP-MCDSR system.
基金the National Natural Science Foundation of China(Nos.61973211,M-0221 and 51911540479)the Research Project of Institute of Medical Robotics of Shanghai Jiao Tong Universitythe Interdisciplinary Program of Shanghai Jiao Tong University(No.ZH2018QNB31)。
文摘The number of people with abnormal gait in China has been increasing for years.Compared with traditional methods,lower limb rehabilitation robots which address problems such as longstanding human guidance may cause fatigue,and the training is lacking scientific and intuitive monitoring data.However,typical rigid rehabilitation robots are always meeting drawbacks like the enormous weight,the limitation of joint movement,and low comfort.The purpose of this research is to design a cable-driven flexible exoskeleton robot to assist in rehabilitation training of patients who have abnormal gait due to low-level hemiplegia or senility.The system consists of a PC terminal,a Raspberry Pi,and the actuator structure.Monitoring and training are realized through remote operation and interactive interface simultaneously.We designed an integrated and miniaturized driving control box.Inside the box,two driving cables on customized pulley-blocks with different radii can retract/release by one motor after transmitting the target position to the Raspberry Pi from the PC.The force could be transferred to the flexible suit to aid hip flexion and ankle plantar flexion.Furthermore,the passive elastic structure was intended to assist ankle dorsiflexion.We also adopted the predictable admittance controller,which uses the Prophet algorithm to predict the changes in the next five gait cycles from the current ankle angular velocity and obtain the ideal force curve through a functional relationship.The admittance controller can realize the desired force following.Finally,we finished the performance test and the human-subject experiment.Experimental data indicate that the exoskeleton can meet the basic demand of multi-joint assistance and improve abnormal postures.Meanwhile,it can increase the range of joint rotation and eliminate asymmetrical during walking.
基金the National Natural Science Foundation of China(Nos.62133009,61973211,51911540479 and M-0221)the Project of the Science and Technology Commission of Shanghai Municipality(No.21550714200)+1 种基金the Research Project of Institute of Medical Robotics of Shanghai Jiao Tong University,the Foreign Cooperation Project of Fujian Science and Technology Plan(No.202210041)the Quanzhou High-Level Talent Innovation and Entrepreneurship Project(No.2021C003R)。
文摘Robot-assisted laparoscopic radical prostatectomy(RARP)is widely used to treat prostate cancer.The rigid instruments primarily used in RARP cannot overcome the problem of blind areas in surgery and lead to more trauma such as more incision for the passage of the instrument and additional tissue damage caused by rigid instruments.Soft robots are relatively fexible and theoretically have infinite degrees of freedom which can overcome the problem of the rigid instrument.A soft robot system for single-port transvesical robot-assisted radical prostatectomy(STvRARP)is developed in this study.The soft manipulator with 10 mm in diameter and a maximum bending angle of 270°has good fexibility and dexterity.The design and mechanical structure of the soft robot are described.The kinematics of the soft manipulator is established and the inverse kinematics is compensated based on the characteristics of the designed soft manipulator.The master-slave control system of soft robot for surgery is built and the feasibility of the designed soft robot is verified.
基金supported by the Universita degli Studi di Padova under Grant No.CPDA088355/08
文摘Extensively studied since the early nineties,cable-driven robots have attracted the growing interest of the industrial and scientific community due to their desirable and peculiar attributes.In particular,underconstrained and planar cable robots can find application in several fields,and specifically,in the packaging industry.The planning of dynamically feasible trajectories(i.e.,trajectories along which cable slackness and excessive tensions are avoided) is particularly challenging when dealing with such a topology of cable robots,which rely on gravity to maintain their cables in tension.This paper,after stressing the current relevance of cable robots,presents an extension and a generalization of a model-based method developed to translate typical cable tension bilateral bounds into intuitive limits on the velocity and acceleration of the robot end effector along a prescribed path.Such a new formulation of the method is based on a parametric expression of cable tensions.The computed kinematic limits can then be incorporated into any trajectory planning algorithm.The method is developed with reference to a hybrid multi-body cable robot topology which can be functionally advantageous but worsen the problem of keeping feasible tensions in the cables both in static and dynamic conditions.The definition of statically feasible workspace is also introduced to identify the positions where static equilibrium can be maintained with feasible tensions.Finally,some aspects related to the practical implementation of the method are discussed.
基金Supported by National Natural Science Foundation of China(Grant No.51525504)。
文摘Cable-driven parallel robots(CDPRs)use cables instead of the rigid limbs of traditional parallel robots,thus processing a large potential workspace,easy to assemble and disassemble characteristics,and with applications in numerous fields.However,owing to the influence of cable flexibility and nonlinear friction,model uncertainties are di cult to eliminate from the control design.Hence,in this study,the model uncertainties of CDPRs are first analyzed based on a brief introduction to related research.Control strategies for CDPRs with model uncertainties are then reviewed.The advantages and disadvantages of several control strategies for CDPRS are discussed through traditional control strategies with kinematic and dynamic uncertainties.Compared with these traditional control strategies,deep reinforcement learning and model predictive control have received widespread attention in recent years owing to their model independence and recursive feasibility with constraint limits.A comprehensive review and brief analysis of current advances in these two control strategies for CDPRs with model uncertainties are presented,concluding with discussions regarding development directions.
基金financial support from the National Natural Science Foundation of China(62103039,62073030)the Joint Fund of Ministry of Education for Equipment Pre-Research(8091B03032303).
文摘Cable-driven soft robots exhibit complex deformations,making state estimation challenging.Hence,this paper develops a multi-sensor fusion approach using a gradient descent strategy to estimate the weighting coefficients.These coefficients combine measurements from proprioceptive sensors,such as resistive flex sensors,to determine the bending angle.Additionally,the fusion strategy adopted provides robust state estimates,overcoming mismatches between the flex sensors and soft robot dimensions.Furthermore,a nonlinear differentiator is introduced to filter the differentiated sensor signals to address noise and irrational values generated by the Analog-to-Digital Converter.A rational polynomial equation is also introduced to compensate for temperature drift exhibited by the resistive flex sensors,which affect the accuracy of state estimation and control.The processed multi-sensor data is then utilized in an improved PD controller for closed-loop control of the soft robot.The controller incorporates the nonlinear differentiator and drift compensation,enhancing tracking performance.Experimental results validate the effectiveness of the integrated approach,demonstrating improved tracking accuracy and robustness compared to traditional PD controllers.
基金supported by National Natural Science Foundation of China(62376219 and 62006194)Foundational Research Project in Specialized Discipline(Grant No.G2024WD0146)Faculty Construction Project(Grant No.24GH0201148).
文摘Large language models(LLMs)have undergone significant expansion and have been increasingly integrated across various domains.Notably,in the realm of robot task planning,LLMs harness their advanced reasoning and language comprehension capabilities to formulate precise and efficient action plans based on natural language instructions.However,for embodied tasks,where robots interact with complex environments,textonly LLMs often face challenges due to a lack of compatibility with robotic visual perception.This study provides a comprehensive overview of the emerging integration of LLMs and multimodal LLMs into various robotic tasks.Additionally,we propose a framework that utilizes multimodal GPT-4V to enhance embodied task planning through the combination of natural language instructions and robot visual perceptions.Our results,based on diverse datasets,indicate that GPT-4V effectively enhances robot performance in embodied tasks.This extensive survey and evaluation of LLMs and multimodal LLMs across a variety of robotic tasks enriches the understanding of LLM-centric embodied intelligence and provides forward-looking insights towards bridging the gap in Human-Robot-Environment interaction.
