This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external forces.The proposed control scheme is design...This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external forces.The proposed control scheme is designed based on the combination of a nonlinear proportional-derivative(NPD)controller and a genetic algorithm,in which the proportional-derivative(PD)parameters are updated online based on the tracking error and the preset error threshold.In addition,the genetic algorithm is employed to adaptively select initial controller parameters,contributing to system stability and improved control accuracy.The proposed controller is basic in design yet simple to implement.The ANPD controller has the advantage of being computationally lightweight and providing high robustness against external forces.The stability of the closed-loop system is rigorously analyzed and verified using Lyapunov theory,providing theoretical assurance of its robustness.Simulations and experimental results show that the TWSB robot with the proposed ANPD controller achieves quick balance and tracks target values with very small errors,demonstrating the effectiveness and performance of the proposed controller.The proposed ANPD controller demonstrates significant improvements in balancing and tracking performance for two-wheeled self-balancing robots,which has great applicability in the field of robot control systems.This represents a promising solution for applications requiring precise and stable motion control under varying external conditions.展开更多
Two types of coaxial self-balancing robots(CSBR)were proposed,one can be used as a mobile robot platform for parts transporting in unmanned factory or as an inspector in dangerous areas,and the other can be used as a ...Two types of coaxial self-balancing robots(CSBR)were proposed,one can be used as a mobile robot platform for parts transporting in unmanned factory or as an inspector in dangerous areas,and the other can be used as a personal transporter ridden in cities.Mechanical designing and control structures as well as control strategies were described and compared in order to get a general way to develop such robots.A state feedback controller and a fuzzy controller were designed for the robot using DC servo motors and the robot using torque motors,respectively.The experiments indicate that the robots can realize various desired operations smoothly and agilely at the velocity of 0.6 m/s with an operator of 65 kg.Furthermore,the robustness of the controllers is revealed since these controllers can stabilize the robot even with unknown external disturbances.展开更多
The paper presents the research on self-balancing two-wheels mobile robot control system analysis with experimental studies.The research problem in this work is to stabilize the mobile robot with self-control and to c...The paper presents the research on self-balancing two-wheels mobile robot control system analysis with experimental studies.The research problem in this work is to stabilize the mobile robot with self-control and to carry the sensitive things without failing in a long span period.The main objective of this study is to focus on the mathematical modelling of mobile robot from laboratory scale to real world applications.The numerical expression with mathematical modelling is very important to control the mobile robot system with linearization.The fundamental concepts of dynamic system stability were utilized for maintaining the stability of the constructed mobile robot system.The controller design is also important for checking the stability and the appropriate controller design is proportional,integral,and derivative-PID controller and Linear Quadratic Regulator(LQR).The steady state error could be reduced by using such kind of PID controller.The simulation of numerical expression on mathematical modeling was conducted in MATLAB environments.The confirmation results from the simulation techniques were applied to construct the hardware design of mobile robot system for practical study.The results from simulation approaches and experimental approaches are matched in various kinds of analyses.The constructed mobile robot system was designed and analyzed in the control system design laboratory of Yangon Technological University(YTU).展开更多
In this paper,a robust tracking control scheme based on nonlinear disturbance observer is developed for the self-balancing mobile robot with external unknown disturbances.A desired velocity control law is firstly desi...In this paper,a robust tracking control scheme based on nonlinear disturbance observer is developed for the self-balancing mobile robot with external unknown disturbances.A desired velocity control law is firstly designed using the Lyapunov analysis method and the arctan function.To improve the tracking control performance,a nonlinear disturbance observer is developed to estimate the unknown disturbance of the self-balancing mobile robot.Using the output of the designed disturbance observer,the robust tracking control scheme is presented employing the sliding mode method for the selfbalancing mobile robot.Numerical simulation results further demonstrate the effectiveness of the proposed robust tracking control scheme for the self-balancing mobile robot subject to external unknown disturbances.展开更多
A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of agent. The motor learning method derives from the principle of CNS and operant learnin...A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of agent. The motor learning method derives from the principle of CNS and operant learning mechanism and it depends on the interactions between the basal ganglia and cerebellum. The whole learning system is composed of evaluation mechanism, action selection mechanism, tropism mechanism. The learning signals come from not only the Inferior Olive but also the Substantia Nigra in the beginning. The speed of learning is increased as well as the failure time is reduced with the cerebellum as a supervisor. Convergence can be guaranteed in the sense of entropy. With the proposed motor learning method, a motor learning system for the self-balancing two-wheeled robot has been built using the RBF neural networks as the actor and evaluation function approximator. The simulation experiments showed that the proposed motor learning system achieved a better learning effect, so the motor learning based on the coordination of cerebellum and basal ganglia is effective.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
Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2)...Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.展开更多
At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown ...At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments,this paper proposes an Attention-Enhanced Dueling Deep Q-Network(ADDueling DQN),which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework.A multi-objective reward function,centered on energy efficiency,is designed to comprehensively consider path length,terrain slope,motion smoothness,and obstacle avoidance,enabling optimal low-energy trajectory generation in 3D space from the source.The incorporation of a multihead attention mechanism allows the model to dynamically focus on energy-critical state features—such as slope gradients and obstacle density—thereby significantly improving its ability to recognize and avoid energy-intensive paths.Additionally,the prioritized experience replay mechanism accelerates learning from key decision-making experiences,suppressing inefficient exploration and guiding the policy toward low-energy solutions more rapidly.The effectiveness of the proposed path planning algorithm is validated through simulation experiments conducted in multiple off-road scenarios.Results demonstrate that AD-Dueling DQN consistently achieves the lowest average energy consumption across all tested environments.Moreover,the proposed method exhibits faster convergence and greater training stability compared to baseline algorithms,highlighting its global optimization capability under energy-aware objectives in complex terrains.This study offers an efficient and scalable intelligent control strategy for the development of energy-conscious autonomous navigation systems.展开更多
The purpose of this study is to develop a self-balancing controller (SBC) for one-wheeled vehicles (OWVs). The composition of the OWV system includes: a DSP motion card, a wheel motor, and its driver. In addition, a t...The purpose of this study is to develop a self-balancing controller (SBC) for one-wheeled vehicles (OWVs). The composition of the OWV system includes: a DSP motion card, a wheel motor, and its driver. In addition, a tilt and a gyro, for sensing the angle and angular velocity of the body slope, are used to realize self-balancing controls. OWV, a kind of unicycle robot, can be dealt with as a mobile-inverted-pendulum system for its instability. However, for its possible applications in mobile carriers or robots, it is worth being further developed. In this study, first, the OWV system model will be derived. Next, through the simulations based on the mathematical model, the analysis of system stability and controllability can be evaluated. Last, a concise and realizable method, through system pole-placement and linear quadratic regulator (LQR), will be proposed to design the SBC. The effectiveness, reliability, and feasibility of the proposal will be con- firmed through simulation studies and experimenting on a physical OWV.展开更多
This study mainly concerns a motion model and the main control algorithm of two-wheel self-balancing vehicle models.Details of the critical parameters fetching and output value of two-wheel self-balancing vehicle mode...This study mainly concerns a motion model and the main control algorithm of two-wheel self-balancing vehicle models.Details of the critical parameters fetching and output value of two-wheel self-balancing vehicle models are introduced,including those concerning balance control,speed control and direction control.An improved cascade coupling control scheme is proposed for two-wheel vehicles,based on a proportional-integral-derivative(PID)control algorithm.Moreover,a thorough comparison between a classic control system and the improved system is provided,and all aspects thereof are analyzed.It is determined that the control performance of the two-wheel self-balancing vehicle system based on the PID control algorithm is reliable,enabling the vehicle body to maintain balance while moving smoothly along a road at a fast average speed with better practical per-formance.展开更多
Wheeled mobile robot is one of the well-known nonholonomic systems. A two-wheeled sell-balance robot is taken as the research objective. This paper carried out a detailed force analysis of the robot and established a ...Wheeled mobile robot is one of the well-known nonholonomic systems. A two-wheeled sell-balance robot is taken as the research objective. This paper carried out a detailed force analysis of the robot and established a non-linear dynamics model. An adaptive tracking controller for the kinematic model of a nonhotonomic mobile robot with unknown parameters is also proposed. Using control Lyapunov function （CLF）, the controller＇s global asymptotic stability has been proven. The adaptive trajectory tracking controller decreases the disturbance in the course of tracking control and enhances the real-time control characteristics. The simulation result indicated that the wheeled mobile robot tracking can be effectively controlled.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
Wireless millirobots engineered to infiltrate intricate vascular networks within living organisms,particularly within constricted and confined spaces,hold immense promise for the future of medical treatments.However,w...Wireless millirobots engineered to infiltrate intricate vascular networks within living organisms,particularly within constricted and confined spaces,hold immense promise for the future of medical treatments.However,with their multifaceted and intricate designs,some robots often grapple with motion and functionality issues when confronted with tight spaces characterized by small cross-sectional dimensions.In this study,drawing inspiration from the high aspect ratio and undulating swimming patterns of snakes,a millimeter-scale,snake-like robot was designed and fabricated via a combination of extrusion-based four-dimensional(4D)printing and magnetic-responsive intelligent functional inks.A sophisticated motion control strategy was also developed,which enables the robots to perform various dynamic movements,such as undulating swimming,precise turns,graceful circular motions,and coordinated cluster movements,under diverse magnetic field variations.As a potential application,the snake robot can navigate and release drugs in a model coronary intervention vessel with tortuous channels and fluid filling.The novel design and promising applications of this snake robot are invaluable tools in future medical surgeries and interventions.展开更多
OBJECTIVE:To propose an automatic acupuncture robot system for performing acupuncture operations.METHODS:The acupuncture robot system consists of three components:automatic acupoint localization,acupuncture manipulati...OBJECTIVE:To propose an automatic acupuncture robot system for performing acupuncture operations.METHODS:The acupuncture robot system consists of three components:automatic acupoint localization,acupuncture manipulations,and De Qi sensation detection.The OptiTrack motion capture system is used to locate acupoints,which are then translated into coordinates in the robot control system.A flexible collaborative robot with an intelligent gripper is then used to perform acupuncture manipulations with high precision.In addition,a De Qi sensation detection system is proposed to evaluate the effect of acupuncture.To verify the stability of the designed acupuncture robot,acupoints'coordinates localized by the acupuncture robot are compared with the Gold Standard labeled by a professional acupuncturist using significant level tests.RESULTS:Through repeated experiments for eight acupoints,the acupuncture robot achieved a positioning error within 3.3 mm,which is within the allowable range of needle extraction and acupoint insertion.During needle insertion,the robot arm followed the prescribed trajectory with a mean deviation distance of 0.02 mm and a deviation angle of less than 0.15°.The results of the lifting thrusting operation in the Xingzhen process show that the mean acupuncture depth error of the designed acupuncture robot is approximately 2 mm,which is within the recommended depth range for the Xingzhen operation.In addition,the average detection accuracy of the De Qi keywords is 94.52%,which meets the requirements of acupuncture effect testing for different dialects.CONCLUSION:The proposed acupuncture robot system streamlines the acupuncture process,increases efficiency,and reduces practitioner fatigue,while also allowing for the quantification of acupuncture manipulations and evaluation of therapeutic effects.The development of an acupuncture robot system has the potential to revolutionize low back pain treatment and improve patient outcomes.展开更多
文摘This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external forces.The proposed control scheme is designed based on the combination of a nonlinear proportional-derivative(NPD)controller and a genetic algorithm,in which the proportional-derivative(PD)parameters are updated online based on the tracking error and the preset error threshold.In addition,the genetic algorithm is employed to adaptively select initial controller parameters,contributing to system stability and improved control accuracy.The proposed controller is basic in design yet simple to implement.The ANPD controller has the advantage of being computationally lightweight and providing high robustness against external forces.The stability of the closed-loop system is rigorously analyzed and verified using Lyapunov theory,providing theoretical assurance of its robustness.Simulations and experimental results show that the TWSB robot with the proposed ANPD controller achieves quick balance and tracks target values with very small errors,demonstrating the effectiveness and performance of the proposed controller.The proposed ANPD controller demonstrates significant improvements in balancing and tracking performance for two-wheeled self-balancing robots,which has great applicability in the field of robot control systems.This represents a promising solution for applications requiring precise and stable motion control under varying external conditions.
基金Project(61273344)supported by the National Natural Science Foundation of ChinaProject(SKLRS-2010-ZD-40)supported by the StateKey Laboratory of Robotics and Systems(HIT),China+1 种基金Project(2008AA04Z208)supported by the National Hi-tech Research and Development Program of ChinaProject(20121101110011)supported by PhD Program Foundation of Ministry of Education,China
文摘Two types of coaxial self-balancing robots(CSBR)were proposed,one can be used as a mobile robot platform for parts transporting in unmanned factory or as an inspector in dangerous areas,and the other can be used as a personal transporter ridden in cities.Mechanical designing and control structures as well as control strategies were described and compared in order to get a general way to develop such robots.A state feedback controller and a fuzzy controller were designed for the robot using DC servo motors and the robot using torque motors,respectively.The experiments indicate that the robots can realize various desired operations smoothly and agilely at the velocity of 0.6 m/s with an operator of 65 kg.Furthermore,the robustness of the controllers is revealed since these controllers can stabilize the robot even with unknown external disturbances.
基金fully supported by Government Research Funds for 2021-2022 Academic Year.
文摘The paper presents the research on self-balancing two-wheels mobile robot control system analysis with experimental studies.The research problem in this work is to stabilize the mobile robot with self-control and to carry the sensitive things without failing in a long span period.The main objective of this study is to focus on the mathematical modelling of mobile robot from laboratory scale to real world applications.The numerical expression with mathematical modelling is very important to control the mobile robot system with linearization.The fundamental concepts of dynamic system stability were utilized for maintaining the stability of the constructed mobile robot system.The controller design is also important for checking the stability and the appropriate controller design is proportional,integral,and derivative-PID controller and Linear Quadratic Regulator(LQR).The steady state error could be reduced by using such kind of PID controller.The simulation of numerical expression on mathematical modeling was conducted in MATLAB environments.The confirmation results from the simulation techniques were applied to construct the hardware design of mobile robot system for practical study.The results from simulation approaches and experimental approaches are matched in various kinds of analyses.The constructed mobile robot system was designed and analyzed in the control system design laboratory of Yangon Technological University(YTU).
基金supported by the National Natural Science Foundation of China(61573184)the Specialized Research Fund for the Doctoral Program of Higher Education(20133218110013)+1 种基金the Six Talents Peak Project of Jainism Province(2012-XRAY-010)the Fundamental Research Funds for theCentral Universities(NE2016101)
文摘In this paper,a robust tracking control scheme based on nonlinear disturbance observer is developed for the self-balancing mobile robot with external unknown disturbances.A desired velocity control law is firstly designed using the Lyapunov analysis method and the arctan function.To improve the tracking control performance,a nonlinear disturbance observer is developed to estimate the unknown disturbance of the self-balancing mobile robot.Using the output of the designed disturbance observer,the robust tracking control scheme is presented employing the sliding mode method for the selfbalancing mobile robot.Numerical simulation results further demonstrate the effectiveness of the proposed robust tracking control scheme for the self-balancing mobile robot subject to external unknown disturbances.
文摘A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of agent. The motor learning method derives from the principle of CNS and operant learning mechanism and it depends on the interactions between the basal ganglia and cerebellum. The whole learning system is composed of evaluation mechanism, action selection mechanism, tropism mechanism. The learning signals come from not only the Inferior Olive but also the Substantia Nigra in the beginning. The speed of learning is increased as well as the failure time is reduced with the cerebellum as a supervisor. Convergence can be guaranteed in the sense of entropy. With the proposed motor learning method, a motor learning system for the self-balancing two-wheeled robot has been built using the RBF neural networks as the actor and evaluation function approximator. The simulation experiments showed that the proposed motor learning system achieved a better learning effect, so the motor learning based on the coordination of cerebellum and basal ganglia is effective.
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supported by the National Natural Science Foundation of China(22168008,22378085)the Guangxi Natural Science Foundation(2024GXNSFDA010053)+1 种基金the Technology Development Project of Guangxi Bossco Environmental Protection Technology Co.,Ltd(202100039)Innovation Project of Guangxi Graduate Education(YCBZ2024065).
文摘Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.
文摘At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments,this paper proposes an Attention-Enhanced Dueling Deep Q-Network(ADDueling DQN),which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework.A multi-objective reward function,centered on energy efficiency,is designed to comprehensively consider path length,terrain slope,motion smoothness,and obstacle avoidance,enabling optimal low-energy trajectory generation in 3D space from the source.The incorporation of a multihead attention mechanism allows the model to dynamically focus on energy-critical state features—such as slope gradients and obstacle density—thereby significantly improving its ability to recognize and avoid energy-intensive paths.Additionally,the prioritized experience replay mechanism accelerates learning from key decision-making experiences,suppressing inefficient exploration and guiding the policy toward low-energy solutions more rapidly.The effectiveness of the proposed path planning algorithm is validated through simulation experiments conducted in multiple off-road scenarios.Results demonstrate that AD-Dueling DQN consistently achieves the lowest average energy consumption across all tested environments.Moreover,the proposed method exhibits faster convergence and greater training stability compared to baseline algorithms,highlighting its global optimization capability under energy-aware objectives in complex terrains.This study offers an efficient and scalable intelligent control strategy for the development of energy-conscious autonomous navigation systems.
文摘The purpose of this study is to develop a self-balancing controller (SBC) for one-wheeled vehicles (OWVs). The composition of the OWV system includes: a DSP motion card, a wheel motor, and its driver. In addition, a tilt and a gyro, for sensing the angle and angular velocity of the body slope, are used to realize self-balancing controls. OWV, a kind of unicycle robot, can be dealt with as a mobile-inverted-pendulum system for its instability. However, for its possible applications in mobile carriers or robots, it is worth being further developed. In this study, first, the OWV system model will be derived. Next, through the simulations based on the mathematical model, the analysis of system stability and controllability can be evaluated. Last, a concise and realizable method, through system pole-placement and linear quadratic regulator (LQR), will be proposed to design the SBC. The effectiveness, reliability, and feasibility of the proposal will be con- firmed through simulation studies and experimenting on a physical OWV.
文摘This study mainly concerns a motion model and the main control algorithm of two-wheel self-balancing vehicle models.Details of the critical parameters fetching and output value of two-wheel self-balancing vehicle models are introduced,including those concerning balance control,speed control and direction control.An improved cascade coupling control scheme is proposed for two-wheel vehicles,based on a proportional-integral-derivative(PID)control algorithm.Moreover,a thorough comparison between a classic control system and the improved system is provided,and all aspects thereof are analyzed.It is determined that the control performance of the two-wheel self-balancing vehicle system based on the PID control algorithm is reliable,enabling the vehicle body to maintain balance while moving smoothly along a road at a fast average speed with better practical per-formance.
基金Supported by the National High Technology Research and Development Programme of China (No. 2006AA04Z245)the Program for Changjiang Scholars and Innovative Research Team in University ( No. IRT0423)the Fund for Foreign Scholars in University Research and Teaching Programs (No. B07018)
文摘Wheeled mobile robot is one of the well-known nonholonomic systems. A two-wheeled sell-balance robot is taken as the research objective. This paper carried out a detailed force analysis of the robot and established a non-linear dynamics model. An adaptive tracking controller for the kinematic model of a nonhotonomic mobile robot with unknown parameters is also proposed. Using control Lyapunov function （CLF）, the controller＇s global asymptotic stability has been proven. The adaptive trajectory tracking controller decreases the disturbance in the course of tracking control and enhances the real-time control characteristics. The simulation result indicated that the wheeled mobile robot tracking can be effectively controlled.
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.
基金the National Natural Science Foundation of China(Nos.52105421 and 52373050)the Guangdong Provincial Natural Science Foundation,China(No.2022A1515011621)+1 种基金the Science and Technology Projects in Guangzhou,China(Nos.202102080330 and 2024A04J6446)the Fundamental Research Funds for the Central Universities,Sun Yat-sen University(No.22qntd0101).
文摘Wireless millirobots engineered to infiltrate intricate vascular networks within living organisms,particularly within constricted and confined spaces,hold immense promise for the future of medical treatments.However,with their multifaceted and intricate designs,some robots often grapple with motion and functionality issues when confronted with tight spaces characterized by small cross-sectional dimensions.In this study,drawing inspiration from the high aspect ratio and undulating swimming patterns of snakes,a millimeter-scale,snake-like robot was designed and fabricated via a combination of extrusion-based four-dimensional(4D)printing and magnetic-responsive intelligent functional inks.A sophisticated motion control strategy was also developed,which enables the robots to perform various dynamic movements,such as undulating swimming,precise turns,graceful circular motions,and coordinated cluster movements,under diverse magnetic field variations.As a potential application,the snake robot can navigate and release drugs in a model coronary intervention vessel with tortuous channels and fluid filling.The novel design and promising applications of this snake robot are invaluable tools in future medical surgeries and interventions.
基金Modernization of Traditional Chinese Medicine Project of National Key R&D Program of China:The construction of the theoretical system of Traditional Chinese Medicine nonpharmacological therapy based on body surface stimulation(2023YFC3502704)Sichuan Provincial Science and Technology Program Project:Research and Development of Chinese Medicine Intelligent Tongue Diagnosis Equipment for Digestive System Chinese Medicine Advantageous Diseases(2023YFS0327)+2 种基金Research and Development of Chinese Medicine Intelligent Detection System for Intestinal Functions(2024YFFK0044)Research and Application of Chinese Medicine Diagnosis and Treatment Program for Herpes Zoster Treated by Shu Pai Fire Acupuncture(2024YFFK0089)Major Research and Development Project of The China Academy of Chinese Medical Sciences Innovation:Construction and application of the theoretical research mode of Traditional Chinese Medicine diagnosis and treatment of modern diseases(CI2021A00104)。
文摘OBJECTIVE:To propose an automatic acupuncture robot system for performing acupuncture operations.METHODS:The acupuncture robot system consists of three components:automatic acupoint localization,acupuncture manipulations,and De Qi sensation detection.The OptiTrack motion capture system is used to locate acupoints,which are then translated into coordinates in the robot control system.A flexible collaborative robot with an intelligent gripper is then used to perform acupuncture manipulations with high precision.In addition,a De Qi sensation detection system is proposed to evaluate the effect of acupuncture.To verify the stability of the designed acupuncture robot,acupoints'coordinates localized by the acupuncture robot are compared with the Gold Standard labeled by a professional acupuncturist using significant level tests.RESULTS:Through repeated experiments for eight acupoints,the acupuncture robot achieved a positioning error within 3.3 mm,which is within the allowable range of needle extraction and acupoint insertion.During needle insertion,the robot arm followed the prescribed trajectory with a mean deviation distance of 0.02 mm and a deviation angle of less than 0.15°.The results of the lifting thrusting operation in the Xingzhen process show that the mean acupuncture depth error of the designed acupuncture robot is approximately 2 mm,which is within the recommended depth range for the Xingzhen operation.In addition,the average detection accuracy of the De Qi keywords is 94.52%,which meets the requirements of acupuncture effect testing for different dialects.CONCLUSION:The proposed acupuncture robot system streamlines the acupuncture process,increases efficiency,and reduces practitioner fatigue,while also allowing for the quantification of acupuncture manipulations and evaluation of therapeutic effects.The development of an acupuncture robot system has the potential to revolutionize low back pain treatment and improve patient outcomes.
