Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.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
In the context of the rapid development of artificial intelligence and robotics,their application scenarios are continuously expanding to a variety of complex environments,with increasing attention being paid to the u...In the context of the rapid development of artificial intelligence and robotics,their application scenarios are continuously expanding to a variety of complex environments,with increasing attention being paid to the use of flexible sensors in lowtemperature environments.In this study,an ionic hydrogel was synthesized using acrylamide(AM),hydroxyethyl cellulose(HEC),and lithium chloride(LiCl)as composites.This hydrogel exhibits high adhesion,excellent sensitivity(gauge factor(GF)=2.84),rapid response time(100 ms),exceptional stretch ability(>1776%),high toughness(2.5 MJ/m^(3)),and the ability to maintain detectability at low temperatures(-60℃).HEC imparts reliable mechanical properties to the sensor through hydrogen bonding interactions of its hydroxyl groups.LiCl ensures that the sensor has outstanding antifreezing properties,maintains good conductivity and mechanical performance.Used for robotic attitude detection,the sensor demonstrated accurate recognition of various joint movements at both 20 and -20℃.This technology was extended to industrial operations and maintenance,where a mechanical claw was used to grasp parts at both room temperature and low temperature.A convolutional neural network deep learning algorithm was employed to identify and classify eight types of parts,achieving an impressive recognition accuracy of 98.8%.The polyacrylamide(PAM)/HEC/LiCl hydrogel sensor demonstrates the capability for wide-temperature range detection in flexible robotics,holding significant potential for future applications in human-machine interaction,tactile perception,and related fields.展开更多
Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined ...Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined with a bio-inspired double wing clap-and-fling mechanism,affect thrust generation.This study focused on increasing vertical force and payload capacity.Through systematic experimentation with various vein configurations and structural designs,we developed innovative wings optimized for thrust production.Comprehensive tests were conducted to measure aerodynamic forces,power consumption,and wing kinematics across a range of flapping frequencies.Additionally,wings with different aspect ratios,a key factor in wing design,were fabricated and extensively evaluated.The study also examined the role of bio-inspired vein layouts on wing flexibility,a critical component in improving flight efficiency.Our findings demonstrate that the newly developed wing design led to a 20%increase in thrust,achieving up to 30 g-force(gf).This research sheds light on the clap-and-fling effect and establishes a promising framework for bio-inspired wing design,offering significant improvements in both performance and payload capacity for FW robots.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
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
Objective:This study aimed to assess the feasibility and safety of the SHURUI single-port robotic surgical system for a range of major urological surgeries.Methods:In this prospective,multicenter clinical trial,we exa...Objective:This study aimed to assess the feasibility and safety of the SHURUI single-port robotic surgical system for a range of major urological surgeries.Methods:In this prospective,multicenter clinical trial,we examined the effectiveness of the SHURUI single-port robotic surgical system in urological interventions.The first 50 patients from four centers in China underwent single-port surgeries including partial nephrectomy,radical prostatectomy,partial adrenalectomy,and pyeloureteroplasty,exclusively by the SHURUI single-port robotic surgical system.The study's primary endpoints focused on the success of surgeries,defined as no deviations from planned procedures,no need for more than one port,and no re-operations within 24 h after surgery.Secondary endpoints encompassed a range of surgical metrics,functional outcomes,and patient demographic data.Clinical assessments were conducted before surgery,before discharge,and 1 month after discharge.Results:The surgical procedures were executed successfully without requiring intraoperative conversions or transfusions.Both estimated blood loss and operation durations were maintained within satisfactory limits.For each type of surgery,the mean console times and estimated blood loss were 179.8(standard deviation[SD]39.4)min and 125.6(SD 126.0)mL for radical prostatectomy,126.7(SD 47.8)min and 39.2(SD 54.4)mL for partial nephrectomy,112.6(SD 37.4)min and 20.0(SD 13.2)mL for partial adrenalectomy,and 148.0(SD 18.2)min and 18.0(SD 17.9)mL for pyeloureteroplasty,respectively.Across the cohort,17 patients experienced a total of 25 adverse events,while 10 postoperative complications,all rated as Clavien-Dindo grade I,were encountered by eight patients.All patients had shown recovery or improvement from these events before the end of this trial.Conclusion:The SHURUI single-port robotic surgical system demonstrated feasibility and safety in the performance of major urological surgeries.These initial findings highlight the system's potential,though further research and longer follow-up are required to assess long-term outcomes.展开更多
The advent of parametric design has resulted in a marked increase in the complexity of building.Unfortunately,traditional construction methods make it difficult to meet the needs.Therefore,construction robots have bec...The advent of parametric design has resulted in a marked increase in the complexity of building.Unfortunately,traditional construction methods make it difficult to meet the needs.Therefore,construction robots have become a pivotal production tool in this context.Since the arm span of a single robot usually does not exceed 3 meters,it is not competent for producing large-scale building components.Accordingly,the extension of the robot,s working range is often achieved by external axes.Nevertheless,the coupling control of external axes and robots and their kinematic solution have become key challenges.The primary technical difficulties include customized construction robots,automatic solutions for external axes,fixed axis joints,and specific motion mode control.This paper proposes solutions to these difficulties,introduces the relevant basic concepts and algorithms in detail,and encapsulates these robotics principles and algorithm processes into the Grasshopper plug-in commonly used by architects to form the FURobot software platform.This platform effectively solves the above problems,lowers the threshold for architects,and improves production efficiency.The effectiveness of the algorithm and software in this paper is verified through simulation experiments.展开更多
This paper endeavours to bridge the existing gap in muscular actuator design for ligament-skeletal-inspired robots,thereby fostering the evolution of these robotic systems.We introduce two novel compliant actuators,na...This paper endeavours to bridge the existing gap in muscular actuator design for ligament-skeletal-inspired robots,thereby fostering the evolution of these robotic systems.We introduce two novel compliant actuators,namely the Internal Torsion Spring Compliant Actuator(ICA)and the External Spring Compliant Actuator(ECA),and present a comparative analysis against the previously conceived Magnet Integrated Soft Actuator(MISA)through computational and experimental results.These actuators,employing a motor-tendon system,emulate biological muscle-like forms,enhancing artificial muscle technology.Then,applications of the proposed actuators in a robotic arm inspired by the human musculoskeletal system are presented.Experiments demonstrate satisfactory power in tasks like lifting dumbbells(peak power:36 W),playing table tennis(end-effector speed:3.2 m/s),and door opening,without compromising biomimetic aesthetics.Compared to other linear stiffness serial elastic actuators(SEAs),ECA and ICA exhibit high power-to-volume(361×10^(3)W/m^(3))and power-to-mass(111.6 W/kg)ratios respectively,endorsing the biomimetic design’s promise in robotic development.展开更多
Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection metho...Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection methods,this paper proposes an enhanced fault detection method based on the unscented Kalman filter(UKF).A comprehensive mathematical model of the brushless DC motor drive system is developed to provide a theoretical foundation for the design of subsequent fault detection methods.The conventional UKF estimation process is detailed,and its limitations in balancing estimation accuracy and robustness are addressed by introducing a dynamic,time-varying boundary layer.To further enhance detection performance,the method incorporates residual analysis using improved z-score and signal-tonoise ratio(SNR)metrics.Numerical simulations under both fault-free and faulty conditions demonstrate that the proposed approach achieves lower root mean square error(RMSE)in fault-free scenarios and provides reliable fault detection.These results highlight the potential of the proposed method to enhance the reliability and robustness of fault detection in industrial robot drive systems.展开更多
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
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.
基金supported by the National Natural Science Foundation of China(No.52475580)the Special Foundation of the Taishan Scholar Project(No.tsqn202211077)+3 种基金the Shandong Provincial Natural Science Foundation(No.ZR2023ME118)the Open Project of State Key Laboratory of Chemical Safety(No.SKLCS-2024020)the Fundamental Research Funds for the Central Universities(No.24CX02014A)the Fund of State Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China).
文摘In the context of the rapid development of artificial intelligence and robotics,their application scenarios are continuously expanding to a variety of complex environments,with increasing attention being paid to the use of flexible sensors in lowtemperature environments.In this study,an ionic hydrogel was synthesized using acrylamide(AM),hydroxyethyl cellulose(HEC),and lithium chloride(LiCl)as composites.This hydrogel exhibits high adhesion,excellent sensitivity(gauge factor(GF)=2.84),rapid response time(100 ms),exceptional stretch ability(>1776%),high toughness(2.5 MJ/m^(3)),and the ability to maintain detectability at low temperatures(-60℃).HEC imparts reliable mechanical properties to the sensor through hydrogen bonding interactions of its hydroxyl groups.LiCl ensures that the sensor has outstanding antifreezing properties,maintains good conductivity and mechanical performance.Used for robotic attitude detection,the sensor demonstrated accurate recognition of various joint movements at both 20 and -20℃.This technology was extended to industrial operations and maintenance,where a mechanical claw was used to grasp parts at both room temperature and low temperature.A convolutional neural network deep learning algorithm was employed to identify and classify eight types of parts,achieving an impressive recognition accuracy of 98.8%.The polyacrylamide(PAM)/HEC/LiCl hydrogel sensor demonstrates the capability for wide-temperature range detection in flexible robotics,holding significant potential for future applications in human-machine interaction,tactile perception,and related fields.
基金Nguyen Tat Thanh University,Ho Chi Minh City,Vietnam for supporting this study。
文摘Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined with a bio-inspired double wing clap-and-fling mechanism,affect thrust generation.This study focused on increasing vertical force and payload capacity.Through systematic experimentation with various vein configurations and structural designs,we developed innovative wings optimized for thrust production.Comprehensive tests were conducted to measure aerodynamic forces,power consumption,and wing kinematics across a range of flapping frequencies.Additionally,wings with different aspect ratios,a key factor in wing design,were fabricated and extensively evaluated.The study also examined the role of bio-inspired vein layouts on wing flexibility,a critical component in improving flight efficiency.Our findings demonstrate that the newly developed wing design led to a 20%increase in thrust,achieving up to 30 g-force(gf).This research sheds light on the clap-and-fling effect and establishes a promising framework for bio-inspired wing design,offering significant improvements in both performance and payload capacity for FW robots.
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.
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.
基金funded by the National Key Research and Development Program of China(Grant No.2022YFB4700904 to Wang L)the Shanghai Shenkang Hospital Development Center's project for the Promotion of Clinical Skills and Clinical Innovation Three-Year Action Plan(Project No.SHDC2022CRT006 to Wang L and SHDC2022CRS010B to Tang S).
文摘Objective:This study aimed to assess the feasibility and safety of the SHURUI single-port robotic surgical system for a range of major urological surgeries.Methods:In this prospective,multicenter clinical trial,we examined the effectiveness of the SHURUI single-port robotic surgical system in urological interventions.The first 50 patients from four centers in China underwent single-port surgeries including partial nephrectomy,radical prostatectomy,partial adrenalectomy,and pyeloureteroplasty,exclusively by the SHURUI single-port robotic surgical system.The study's primary endpoints focused on the success of surgeries,defined as no deviations from planned procedures,no need for more than one port,and no re-operations within 24 h after surgery.Secondary endpoints encompassed a range of surgical metrics,functional outcomes,and patient demographic data.Clinical assessments were conducted before surgery,before discharge,and 1 month after discharge.Results:The surgical procedures were executed successfully without requiring intraoperative conversions or transfusions.Both estimated blood loss and operation durations were maintained within satisfactory limits.For each type of surgery,the mean console times and estimated blood loss were 179.8(standard deviation[SD]39.4)min and 125.6(SD 126.0)mL for radical prostatectomy,126.7(SD 47.8)min and 39.2(SD 54.4)mL for partial nephrectomy,112.6(SD 37.4)min and 20.0(SD 13.2)mL for partial adrenalectomy,and 148.0(SD 18.2)min and 18.0(SD 17.9)mL for pyeloureteroplasty,respectively.Across the cohort,17 patients experienced a total of 25 adverse events,while 10 postoperative complications,all rated as Clavien-Dindo grade I,were encountered by eight patients.All patients had shown recovery or improvement from these events before the end of this trial.Conclusion:The SHURUI single-port robotic surgical system demonstrated feasibility and safety in the performance of major urological surgeries.These initial findings highlight the system's potential,though further research and longer follow-up are required to assess long-term outcomes.
基金National Key R&D Program of China(Nos.2023YFC3806900,2022YFE0141400)。
文摘The advent of parametric design has resulted in a marked increase in the complexity of building.Unfortunately,traditional construction methods make it difficult to meet the needs.Therefore,construction robots have become a pivotal production tool in this context.Since the arm span of a single robot usually does not exceed 3 meters,it is not competent for producing large-scale building components.Accordingly,the extension of the robot,s working range is often achieved by external axes.Nevertheless,the coupling control of external axes and robots and their kinematic solution have become key challenges.The primary technical difficulties include customized construction robots,automatic solutions for external axes,fixed axis joints,and specific motion mode control.This paper proposes solutions to these difficulties,introduces the relevant basic concepts and algorithms in detail,and encapsulates these robotics principles and algorithm processes into the Grasshopper plug-in commonly used by architects to form the FURobot software platform.This platform effectively solves the above problems,lowers the threshold for architects,and improves production efficiency.The effectiveness of the algorithm and software in this paper is verified through simulation experiments.
基金research project funded by the National Natural Science Foundation of China(NSFC)under Grant 91948302 and Grant 52021003Research England fund at NERIC.
文摘This paper endeavours to bridge the existing gap in muscular actuator design for ligament-skeletal-inspired robots,thereby fostering the evolution of these robotic systems.We introduce two novel compliant actuators,namely the Internal Torsion Spring Compliant Actuator(ICA)and the External Spring Compliant Actuator(ECA),and present a comparative analysis against the previously conceived Magnet Integrated Soft Actuator(MISA)through computational and experimental results.These actuators,employing a motor-tendon system,emulate biological muscle-like forms,enhancing artificial muscle technology.Then,applications of the proposed actuators in a robotic arm inspired by the human musculoskeletal system are presented.Experiments demonstrate satisfactory power in tasks like lifting dumbbells(peak power:36 W),playing table tennis(end-effector speed:3.2 m/s),and door opening,without compromising biomimetic aesthetics.Compared to other linear stiffness serial elastic actuators(SEAs),ECA and ICA exhibit high power-to-volume(361×10^(3)W/m^(3))and power-to-mass(111.6 W/kg)ratios respectively,endorsing the biomimetic design’s promise in robotic development.
基金Supported by the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(22KJB520012)the Research Project on Higher Education Reform in Jiangsu Province(2023JSJG781)the College Student Innovation and Entrepreneurship Training Program Project(202313571008Z)。
文摘Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection methods,this paper proposes an enhanced fault detection method based on the unscented Kalman filter(UKF).A comprehensive mathematical model of the brushless DC motor drive system is developed to provide a theoretical foundation for the design of subsequent fault detection methods.The conventional UKF estimation process is detailed,and its limitations in balancing estimation accuracy and robustness are addressed by introducing a dynamic,time-varying boundary layer.To further enhance detection performance,the method incorporates residual analysis using improved z-score and signal-tonoise ratio(SNR)metrics.Numerical simulations under both fault-free and faulty conditions demonstrate that the proposed approach achieves lower root mean square error(RMSE)in fault-free scenarios and provides reliable fault detection.These results highlight the potential of the proposed method to enhance the reliability and robustness of fault detection in industrial robot drive systems.
