Objective:To assess the safety and effectiveness of urological tumor surgeries using the hinotori^(TM)Surgical Robot System(hinotori)in a real-world clinical setting.Methods:All surgeries including robot-assisted radi...Objective:To assess the safety and effectiveness of urological tumor surgeries using the hinotori^(TM)Surgical Robot System(hinotori)in a real-world clinical setting.Methods:All surgeries including robot-assisted radical prostatectomy(RARP),robot-assisted partial nephrectomy(RAPN),robot-assisted radical nephrectomy(RARN),robot-assisted nephroureterectomy(RANU),robot-assisted adrenalectomy(RAA),and robot-assisted radical cystectomy with intracorporeal urinary diversion(RARC+ICUD)for urological tumors with the hinotori and da Vinci surgical system(da Vinci)from January 2022 to September 2023 were enrolled.We evaluated the safety and effectiveness of surgeries using the hinotori compared with those using the da Vinci.Results:Robotic surgeries using the hinotori were performed in a total of 91 cases,comprising 42 cases of RARP,18 cases of RAPN,six cases of RARN,10 cases of RANU,13 cases of RAA,and two cases of RARC+ICUD;no major intraoperative complications were observed in any of the cases using the hinotori;no major postoperative complications occurred in any of the cases;no case experienced an unrecoverable equipment error during surgery.Meanwhile,robotic surgeries using the da Vinci were performed in a total of 277 cases,comprising 126 cases of RARP,94 cases of RAPN,12 cases of RARN,10 cases of RANU,20 cases of RAA,and 15 cases of RARC+ICUD;major intraoperative complications occurred in two cases;major postoperative complications occurred in seven cases;seven cases required transfusion;one case underwent conversion to open surgery;during the study period,no case experienced an unrecoverable equipment error.Surgical outcomes for cases with the hinotori were comparable to those with the da Vinci.Conclusion:This study demonstrated that the hinotori is a safe and feasible tool for robotic surgeries in the field of urology.展开更多
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
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
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
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
Deep reinforcement learning(DRL)remains underexplored within architectural robotics,particularly in relation to self-learning of architectural design principles and designaware robotic fabrication.To address this gap,...Deep reinforcement learning(DRL)remains underexplored within architectural robotics,particularly in relation to self-learning of architectural design principles and designaware robotic fabrication.To address this gap,we applied established DRL methods to enable robot arms to autonomously learn design rules in a pilot block wall assembly-design scenario.Recognizing the complexity inherent in such learning tasks,the problem was strategically decomposed into two sub-tasks:(i)target reaching(T1),modeled within a continuous action space,and(ii)sequential planning(T2),formulated within a discrete action space.For T1,we evaluated major DRL algorithms―Proximal Policy Optimization(PPO),Advantage Actor-Critic(A2C),Deep Deterministic Policy Gradient,Twin Delayed Deep Deterministic Policy Gradient,and Soft Actor-Critic(SAC),and PPO,A2C,and Double Deep Q-Network(DDQN)were tested for T2.Performance was assessed based on training efficacy,reliability,and two novel metrics:degree index and variation index.Our results revealed that SAC was the best for T1,whereas DDQN excelled in T2.Notably,DDQN exhibited strong learning adaptability,yielding diverse final layouts in response to varying initial conditions.展开更多
In this study,we present a small,integrated jumping-crawling robot capable of intermittent jumping and self-resetting.Compared to robots with a single mode of locomotion,this multi-modal robot exhibits enhanced obstac...In this study,we present a small,integrated jumping-crawling robot capable of intermittent jumping and self-resetting.Compared to robots with a single mode of locomotion,this multi-modal robot exhibits enhanced obstacle-surmounting capabilities.To achieve this,the robot employs a novel combination of a jumping module and a crawling module.The jumping module features improved energy storage capacity and an active clutch.Within the constraints of structural robustness,the jumping module maximizes the explosive power of the linear spring by utilizing the mechanical advantage of a closed-loop mechanism and controls the energy flow of the jumping module through an active clutch mechanism.Furthermore,inspired by the limb movements of tortoises during crawling and self-righting,a single-degree-of-freedom spatial four-bar crawling mechanism was designed to enable crawling,steering,and resetting functions.To demonstrate its practicality,the integrated jumping-crawling robot was tested in a laboratory environment for functions such as jumping,crawling,self-resetting,and steering.Experimental results confirmed the feasibility of the proposed integrated jumping-crawling robot.展开更多
BACKGROUND Median sternotomy has been considered the gold standard approach for anterior mediastinal tumor resection.However,recent advances in video-assisted thoracoscopic surgery and robotic-assisted thoracoscopic s...BACKGROUND Median sternotomy has been considered the gold standard approach for anterior mediastinal tumor resection.However,recent advances in video-assisted thoracoscopic surgery and robotic-assisted thoracoscopic surgery with carbon dioxide insufflation have allowed minimally invasive approaches even for large and locally invasive tumors of the upper-anterior mediastinum.The subxiphoid robotic optical approach is a recently developed technique for accessing the mediastinum.The trans-subxiphoid technique offers excellent exposure of the surgical field,reduces postoperative pain,facilitates specimen retrieval even for large tumors,and potentially improves early surgical outcomes.AIM To evaluate the safety,feasibility,and outcomes of a robotic subxiphoid approach for the resecting of large/invasive mediastinal tumors.METHODS Between July 2024 and September 2025,12 patients underwent subxiphoid robotic mediastinal resection.The diameter of the operated lesions ranged from 30 mm to 70 mm.A 3 cm subxiphoid incision was made at the subxiphoid level for GelPort placement,allowing for optical port access.Two operating ports were placed at the sixth intercostal space bilaterally.Carbon dioxide insufflations(8-10 mmHg)enlarged the surgical field,improving visualization of critical anatomical landmarks,such as the internal mammary arteries and phrenic nerves.This approach allowed complete resection of large or invasive tumors,preserving thoracic stability and reducing the risk of postoperative myasthenic crisis.RESULTS The mean operating time was 170.2 minutes,and the median hospital stay was 3.5 days.No major postoperative complications occurred.Two conversions were necessary:One with a lateral robotic approach due to previous abdominal surgery,and one with a sternotomy for tumor invasion of the aortic arch.Histopathological analysis identified nine thymomas and one solitary fibrous tumor.CONCLUSION Subxiphoid robotic approach is a safe,effective technique for extended thymectomy,fulfilling both oncological and myasthenia gravis surgical objectives.展开更多
In recent years,the rapid advancement of artificial intelligence(AI)has fostered deep integration between large AI models and robotic technology.Robots such as robotic dogs capable of carrying heavy loads on mountaino...In recent years,the rapid advancement of artificial intelligence(AI)has fostered deep integration between large AI models and robotic technology.Robots such as robotic dogs capable of carrying heavy loads on mountainous terrain or performing waste disposal tasks and humanoid robots that can execute high-precision component installations have gradually reached the public eye,raising expectations for embodied intelligent robots.展开更多
Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under dir...Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under directed graph to estimate the relative information between each follower robot and the leader robot.Then the formation control problem is transformed into the tracking problem and a finite-time tracking controller is proposed based on the robot model feature.展开更多
The rapid evolution of industrial robots from automation tools to intelligent systems marks a pivotal shift in manufacturing practices within the framework of Industry 4.0.Industrial robots,once limited to repetitive ...The rapid evolution of industrial robots from automation tools to intelligent systems marks a pivotal shift in manufacturing practices within the framework of Industry 4.0.Industrial robots,once limited to repetitive tasks on assembly lines,are now increasingly powered by advanced technologies such as Artificial Intelligence(AI),machine learning,and the Internet of Things(IoT),enabling them to perform complex,adaptive tasks in real-time.This paper explores the technological advancements that have transformed industrial robots,highlighting the integration of AI,smart sensors,and autonomous systems.Furthermore,it examines the implications of this paradigm shift for industries,human-robot collaboration,and the workforce.While intelligent robots promise greater efficiency,flexibility,and safety in manufacturing,challenges regarding implementation,economic impact,and ethical considerations remain significant.The paper concludes by looking at the future trends in robotics and their potential to reshape the global industrial landscape.展开更多
Rollover accidents involving agricultural wheeled robots,accompanied by severe mechanical impacts,pose serious threats to operational safety and reduce functional efficiency.To address this issue,an active rollover pr...Rollover accidents involving agricultural wheeled robots,accompanied by severe mechanical impacts,pose serious threats to operational safety and reduce functional efficiency.To address this issue,an active rollover prevention strategy is proposed,utilizing a single‐gimbal control moment gyro(SGCMG),to stabilize typical agricultural robots and prevent potential rollovers.To match the free oscillation of the pivot front axle,a novel recovery torque model of the coupled robot‐SGCMG system is established,in which two patterns are introduced to refine the rollover process with uncertain parameters.Additionally,a lateral stability index is adopted and analyzed to assess the hazard level of potential rollovers.Aimed at handling uncertain parameters and hazard levels,an adaptive backstepping control strategy is developed for real‐time anti‐rollover implementation.Within this strategy,control gains are adaptively tuned based on theoretical derivations,thereby suppressing rollover tendency while minimizing tuning effort.For verification,a scaled experimental platform,designed according to similarity theory,is constructed to ensure safety of personnel and equipment.Experimental results show that the proposed method can precisely regulate the output torque of the gyro,rapidly and effectively mitigating the risk of imminent rollover.This method provides a promising solution for wheeled robot stability and a theoretical basis for advanced safety control in agricultural robotics.展开更多
Compared with conventional rigid-link robots,bionic continuum robots(CRs)show great potential in unstructured environments because of their adaptivity and continuous deformation ability.However,designing a CR to achie...Compared with conventional rigid-link robots,bionic continuum robots(CRs)show great potential in unstructured environments because of their adaptivity and continuous deformation ability.However,designing a CR to achieve miniaturization,variable length and compliant driving force remains a challenge.Here,inspired by the earthworm in nature,we report a length-variable bionic CR with millimeter-scale diameter and compliant driving force.The CR consists of two main components:the robot body and soft drives.The robot body is only 6 mm in diameter,and is composed of a backbone and transmission devices.The backbone is divided into three segments,and each segment is capable of adjusting its length and bending like the earthworm.The maximum length variation of the backbone can reach an astonishing 70 mm with a backbone’s initial length of 150 mm,and the maximum bending angle of each segment can reach 120 degrees.In addition,we develop soft drives using pneumatic soft actuators(PSAs)as a replacement for the rigid motors typically used in conventional CRs.These soft drives control the motions of the transmission devices,enabling length variation and bending of the backbone.By utilizing these soft drives,we ensure that the robot body has a compliant driving force,which addresses users’concerns about human safety during interactions.In practical applications,we prove that this CR can perform delicate manipulations by successfully completing writing tasks.Additionally,we show its application value for detections and medical treatments by entering the narrow tube and the oral.展开更多
Insect-scale flapping wing aerial robots actuated by piezoelectric materials—known for their high power density and rapid frequency response—have recently garnered increasing attention.However,the limited output dis...Insect-scale flapping wing aerial robots actuated by piezoelectric materials—known for their high power density and rapid frequency response—have recently garnered increasing attention.However,the limited output displacement of piezoelectric actuators results in complex transmission methods that are challenging to assemble.Furthermore,high piezoelectric coefficient materials capable of large displacements for direct wing actuation are fragile,costly,and relatively bulky.This article presents a novel design for minimalist insect-scale aerial robots,where piezoelectric bimorph PZT actuators directly drive two pairs of wings,thus eliminating complex transmission mechanisms and reducing fabrication complexity.These robots demonstrate high liftoff speeds and favorable lift-to-weight ratios,and they can achieve vertical ascent under uncontrolled open-loop conditions.The piezoelectric direct-driven twowing insect-scale aerial robot,based on this approach,features an 8 cm wingspan and a prototype weight of 140 mg,successfully achieving takeoff under unconstrained conditions with an external power source.To further enhance insect-scale aerial robot performance,we optimized the wing-to-actuator ratio and wing arrangement.We propose a biaxial aerial robot with an X-shaped structure,a 2:1 wing-toactuator ratio,a 70 mm wingspan,and a total mass of 160 mg.This structure demonstrates a high lift-to-weight ratio of 2.8:1.During free flight,when powered externally,it attains a maximum takeoff speed exceeding 1 m/s and achieves a vertical takeoff height surpassing 80 cm under uncontrolled conditions.Consequently,it ranks among the fastest prototypes in the milligram-scale weight category.展开更多
Human-robot safety is an important topic in wearable robotics,especially in supernumerary robotic limbs(SRLs).The proposal of flexible joint improves human-robot safety strategy,which allows physical contact between h...Human-robot safety is an important topic in wearable robotics,especially in supernumerary robotic limbs(SRLs).The proposal of flexible joint improves human-robot safety strategy,which allows physical contact between human and robots,rather than strictly limiting the human-robot motion.However,most researchers focus on the variable stiffness features of flexible joints,but few evaluate the performance of the flexible joint in the human-robot collision.Therefore,the performance of two typical flexible joints,including the series elastic joint(SEJ)and the passive variable stiffness joint(PVSJ),are compared through dynamic collision experiments.The results demonstrate that the SEJ absorbs 40.7%-58.7%of the collision force and 34.2%-45.2%of the collision torque in the driven-torque below 4 N·m and driven-speed of 3-7(°)/s,which is more stable than PVSJ.In addition,the stiffness error of SEJ is measured at 5.1%,significantly lower than the 23.04%measured in the PVSJ.The huge stiffness error of PVSJ leads to its unreliability in buffering collision.Furthermore,we analyze results and confirm that SEJ has a more stable human-robot safety performance in buffering dynamic collision.Consequently,the SEJ is suitable in SRLs for human-robot safety in our scenario.展开更多
文摘Objective:To assess the safety and effectiveness of urological tumor surgeries using the hinotori^(TM)Surgical Robot System(hinotori)in a real-world clinical setting.Methods:All surgeries including robot-assisted radical prostatectomy(RARP),robot-assisted partial nephrectomy(RAPN),robot-assisted radical nephrectomy(RARN),robot-assisted nephroureterectomy(RANU),robot-assisted adrenalectomy(RAA),and robot-assisted radical cystectomy with intracorporeal urinary diversion(RARC+ICUD)for urological tumors with the hinotori and da Vinci surgical system(da Vinci)from January 2022 to September 2023 were enrolled.We evaluated the safety and effectiveness of surgeries using the hinotori compared with those using the da Vinci.Results:Robotic surgeries using the hinotori were performed in a total of 91 cases,comprising 42 cases of RARP,18 cases of RAPN,six cases of RARN,10 cases of RANU,13 cases of RAA,and two cases of RARC+ICUD;no major intraoperative complications were observed in any of the cases using the hinotori;no major postoperative complications occurred in any of the cases;no case experienced an unrecoverable equipment error during surgery.Meanwhile,robotic surgeries using the da Vinci were performed in a total of 277 cases,comprising 126 cases of RARP,94 cases of RAPN,12 cases of RARN,10 cases of RANU,20 cases of RAA,and 15 cases of RARC+ICUD;major intraoperative complications occurred in two cases;major postoperative complications occurred in seven cases;seven cases required transfusion;one case underwent conversion to open surgery;during the study period,no case experienced an unrecoverable equipment error.Surgical outcomes for cases with the hinotori were comparable to those with the da Vinci.Conclusion:This study demonstrated that the hinotori is a safe and feasible tool for robotic surgeries in the field of urology.
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.
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.
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 the National Research Foundation of Korea(NRF)grants funded by the Korea government(MSIT)(RS-2024-00353461).
文摘Deep reinforcement learning(DRL)remains underexplored within architectural robotics,particularly in relation to self-learning of architectural design principles and designaware robotic fabrication.To address this gap,we applied established DRL methods to enable robot arms to autonomously learn design rules in a pilot block wall assembly-design scenario.Recognizing the complexity inherent in such learning tasks,the problem was strategically decomposed into two sub-tasks:(i)target reaching(T1),modeled within a continuous action space,and(ii)sequential planning(T2),formulated within a discrete action space.For T1,we evaluated major DRL algorithms―Proximal Policy Optimization(PPO),Advantage Actor-Critic(A2C),Deep Deterministic Policy Gradient,Twin Delayed Deep Deterministic Policy Gradient,and Soft Actor-Critic(SAC),and PPO,A2C,and Double Deep Q-Network(DDQN)were tested for T2.Performance was assessed based on training efficacy,reliability,and two novel metrics:degree index and variation index.Our results revealed that SAC was the best for T1,whereas DDQN excelled in T2.Notably,DDQN exhibited strong learning adaptability,yielding diverse final layouts in response to varying initial conditions.
基金supported by the National Natural Science Foundation of China(Nos.51375383).
文摘In this study,we present a small,integrated jumping-crawling robot capable of intermittent jumping and self-resetting.Compared to robots with a single mode of locomotion,this multi-modal robot exhibits enhanced obstacle-surmounting capabilities.To achieve this,the robot employs a novel combination of a jumping module and a crawling module.The jumping module features improved energy storage capacity and an active clutch.Within the constraints of structural robustness,the jumping module maximizes the explosive power of the linear spring by utilizing the mechanical advantage of a closed-loop mechanism and controls the energy flow of the jumping module through an active clutch mechanism.Furthermore,inspired by the limb movements of tortoises during crawling and self-righting,a single-degree-of-freedom spatial four-bar crawling mechanism was designed to enable crawling,steering,and resetting functions.To demonstrate its practicality,the integrated jumping-crawling robot was tested in a laboratory environment for functions such as jumping,crawling,self-resetting,and steering.Experimental results confirmed the feasibility of the proposed integrated jumping-crawling robot.
文摘BACKGROUND Median sternotomy has been considered the gold standard approach for anterior mediastinal tumor resection.However,recent advances in video-assisted thoracoscopic surgery and robotic-assisted thoracoscopic surgery with carbon dioxide insufflation have allowed minimally invasive approaches even for large and locally invasive tumors of the upper-anterior mediastinum.The subxiphoid robotic optical approach is a recently developed technique for accessing the mediastinum.The trans-subxiphoid technique offers excellent exposure of the surgical field,reduces postoperative pain,facilitates specimen retrieval even for large tumors,and potentially improves early surgical outcomes.AIM To evaluate the safety,feasibility,and outcomes of a robotic subxiphoid approach for the resecting of large/invasive mediastinal tumors.METHODS Between July 2024 and September 2025,12 patients underwent subxiphoid robotic mediastinal resection.The diameter of the operated lesions ranged from 30 mm to 70 mm.A 3 cm subxiphoid incision was made at the subxiphoid level for GelPort placement,allowing for optical port access.Two operating ports were placed at the sixth intercostal space bilaterally.Carbon dioxide insufflations(8-10 mmHg)enlarged the surgical field,improving visualization of critical anatomical landmarks,such as the internal mammary arteries and phrenic nerves.This approach allowed complete resection of large or invasive tumors,preserving thoracic stability and reducing the risk of postoperative myasthenic crisis.RESULTS The mean operating time was 170.2 minutes,and the median hospital stay was 3.5 days.No major postoperative complications occurred.Two conversions were necessary:One with a lateral robotic approach due to previous abdominal surgery,and one with a sternotomy for tumor invasion of the aortic arch.Histopathological analysis identified nine thymomas and one solitary fibrous tumor.CONCLUSION Subxiphoid robotic approach is a safe,effective technique for extended thymectomy,fulfilling both oncological and myasthenia gravis surgical objectives.
文摘In recent years,the rapid advancement of artificial intelligence(AI)has fostered deep integration between large AI models and robotic technology.Robots such as robotic dogs capable of carrying heavy loads on mountainous terrain or performing waste disposal tasks and humanoid robots that can execute high-precision component installations have gradually reached the public eye,raising expectations for embodied intelligent robots.
基金supported by the National Natural Science Foundation of China(62073113,62003122,62303148)the Fundamental Research Funds for the Central Universities(MCCSE2023A01,JZ2023HGTA0201,JZ2023HGQA0109)the Anhui Provincial Natural Science Foundation(2308085QF204)
文摘Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under directed graph to estimate the relative information between each follower robot and the leader robot.Then the formation control problem is transformed into the tracking problem and a finite-time tracking controller is proposed based on the robot model feature.
文摘The rapid evolution of industrial robots from automation tools to intelligent systems marks a pivotal shift in manufacturing practices within the framework of Industry 4.0.Industrial robots,once limited to repetitive tasks on assembly lines,are now increasingly powered by advanced technologies such as Artificial Intelligence(AI),machine learning,and the Internet of Things(IoT),enabling them to perform complex,adaptive tasks in real-time.This paper explores the technological advancements that have transformed industrial robots,highlighting the integration of AI,smart sensors,and autonomous systems.Furthermore,it examines the implications of this paradigm shift for industries,human-robot collaboration,and the workforce.While intelligent robots promise greater efficiency,flexibility,and safety in manufacturing,challenges regarding implementation,economic impact,and ethical considerations remain significant.The paper concludes by looking at the future trends in robotics and their potential to reshape the global industrial landscape.
基金supported by the National Natural Science Foundation of China(No.52175259)the 2115 Talent Development Program of China Agricultural University.
文摘Rollover accidents involving agricultural wheeled robots,accompanied by severe mechanical impacts,pose serious threats to operational safety and reduce functional efficiency.To address this issue,an active rollover prevention strategy is proposed,utilizing a single‐gimbal control moment gyro(SGCMG),to stabilize typical agricultural robots and prevent potential rollovers.To match the free oscillation of the pivot front axle,a novel recovery torque model of the coupled robot‐SGCMG system is established,in which two patterns are introduced to refine the rollover process with uncertain parameters.Additionally,a lateral stability index is adopted and analyzed to assess the hazard level of potential rollovers.Aimed at handling uncertain parameters and hazard levels,an adaptive backstepping control strategy is developed for real‐time anti‐rollover implementation.Within this strategy,control gains are adaptively tuned based on theoretical derivations,thereby suppressing rollover tendency while minimizing tuning effort.For verification,a scaled experimental platform,designed according to similarity theory,is constructed to ensure safety of personnel and equipment.Experimental results show that the proposed method can precisely regulate the output torque of the gyro,rapidly and effectively mitigating the risk of imminent rollover.This method provides a promising solution for wheeled robot stability and a theoretical basis for advanced safety control in agricultural robotics.
基金supported by the Young Scientists Fund of National Natural Science Foundation of China(62203408)the China Postdoctoral Science Foundation(2023M733307),the Hubei Provincial Natural Science Foundation of China(2015CFA010)+1 种基金the 111 Project(B17040)the“CUG Scholar”Scientific Research Funds at China University of Geosciences(Wuhan)(2022088)。
文摘Compared with conventional rigid-link robots,bionic continuum robots(CRs)show great potential in unstructured environments because of their adaptivity and continuous deformation ability.However,designing a CR to achieve miniaturization,variable length and compliant driving force remains a challenge.Here,inspired by the earthworm in nature,we report a length-variable bionic CR with millimeter-scale diameter and compliant driving force.The CR consists of two main components:the robot body and soft drives.The robot body is only 6 mm in diameter,and is composed of a backbone and transmission devices.The backbone is divided into three segments,and each segment is capable of adjusting its length and bending like the earthworm.The maximum length variation of the backbone can reach an astonishing 70 mm with a backbone’s initial length of 150 mm,and the maximum bending angle of each segment can reach 120 degrees.In addition,we develop soft drives using pneumatic soft actuators(PSAs)as a replacement for the rigid motors typically used in conventional CRs.These soft drives control the motions of the transmission devices,enabling length variation and bending of the backbone.By utilizing these soft drives,we ensure that the robot body has a compliant driving force,which addresses users’concerns about human safety during interactions.In practical applications,we prove that this CR can perform delicate manipulations by successfully completing writing tasks.Additionally,we show its application value for detections and medical treatments by entering the narrow tube and the oral.
基金supported by the National Natural Science Foundation of China(No.52475039)。
文摘Insect-scale flapping wing aerial robots actuated by piezoelectric materials—known for their high power density and rapid frequency response—have recently garnered increasing attention.However,the limited output displacement of piezoelectric actuators results in complex transmission methods that are challenging to assemble.Furthermore,high piezoelectric coefficient materials capable of large displacements for direct wing actuation are fragile,costly,and relatively bulky.This article presents a novel design for minimalist insect-scale aerial robots,where piezoelectric bimorph PZT actuators directly drive two pairs of wings,thus eliminating complex transmission mechanisms and reducing fabrication complexity.These robots demonstrate high liftoff speeds and favorable lift-to-weight ratios,and they can achieve vertical ascent under uncontrolled open-loop conditions.The piezoelectric direct-driven twowing insect-scale aerial robot,based on this approach,features an 8 cm wingspan and a prototype weight of 140 mg,successfully achieving takeoff under unconstrained conditions with an external power source.To further enhance insect-scale aerial robot performance,we optimized the wing-to-actuator ratio and wing arrangement.We propose a biaxial aerial robot with an X-shaped structure,a 2:1 wing-toactuator ratio,a 70 mm wingspan,and a total mass of 160 mg.This structure demonstrates a high lift-to-weight ratio of 2.8:1.During free flight,when powered externally,it attains a maximum takeoff speed exceeding 1 m/s and achieves a vertical takeoff height surpassing 80 cm under uncontrolled conditions.Consequently,it ranks among the fastest prototypes in the milligram-scale weight category.
基金supported by the Na⁃tional Natural Science Foundation of China(No.U22A20204)the Innovation Foundation from National Clinical Research Center for Orthopedics,Sports Medicine&Rehabilitation Foundation(No.23-NCRC-CXJJ-ZD3-8)。
文摘Human-robot safety is an important topic in wearable robotics,especially in supernumerary robotic limbs(SRLs).The proposal of flexible joint improves human-robot safety strategy,which allows physical contact between human and robots,rather than strictly limiting the human-robot motion.However,most researchers focus on the variable stiffness features of flexible joints,but few evaluate the performance of the flexible joint in the human-robot collision.Therefore,the performance of two typical flexible joints,including the series elastic joint(SEJ)and the passive variable stiffness joint(PVSJ),are compared through dynamic collision experiments.The results demonstrate that the SEJ absorbs 40.7%-58.7%of the collision force and 34.2%-45.2%of the collision torque in the driven-torque below 4 N·m and driven-speed of 3-7(°)/s,which is more stable than PVSJ.In addition,the stiffness error of SEJ is measured at 5.1%,significantly lower than the 23.04%measured in the PVSJ.The huge stiffness error of PVSJ leads to its unreliability in buffering collision.Furthermore,we analyze results and confirm that SEJ has a more stable human-robot safety performance in buffering dynamic collision.Consequently,the SEJ is suitable in SRLs for human-robot safety in our scenario.
