The paper proposes a novel multi-legged robot with pitch adjustive units aiming at obstacle surmounting.With only 6 degrees of freedom,the robot with 16 mechanical legs walks steadily and surmounts the obstacles on th...The paper proposes a novel multi-legged robot with pitch adjustive units aiming at obstacle surmounting.With only 6 degrees of freedom,the robot with 16 mechanical legs walks steadily and surmounts the obstacles on the complex terrain.The leg unit with adjustive pitch provides a large workspace and empowers the legs to climb up obstacles in large sizes,which enhances the obstacle surmounting capability.The pitch adjustment in leg unit requires as few independent adjusting actuators as possible.Based on the kinematic analysis of the mechanical leg,the biped and quadruped leg units with adjustive pitch are analyzed and compared.The configuration of the robot is designed to obtain a compact structure and pragmatic performance.The uncertainty of the obstacle size and position in the surmounting process is taken into consideration and the parameters of the adjustments and the feasible strategies for obstacle surmounting are presented.Then the 3D virtual model and the robot prototype are built and the multi-body dynamic simulations and prototype experiments are carried out.The results from the simulations and the experiments show that the robot possesses good obstacle surmounting capabilities.展开更多
Real-time slip detection and state estimation are crucial for locomotion control,facilitating posture adjustment and stability recovery of multi-legged robots moving on slippery terrain.However,existing proprioceptive...Real-time slip detection and state estimation are crucial for locomotion control,facilitating posture adjustment and stability recovery of multi-legged robots moving on slippery terrain.However,existing proprioceptive methods rely on the fixed-contact assumption with fixed noise and suffer from low accuracy when multiple legs slip simultaneously.This paper proposes a novel proprioceptive approach for multi-legged robots moving in slippery scenarios to cope with slippage of multiple legs.In slip detection,the proprioceptive states of the robot are fed into a convolutional neural network to detect slip event(s)of the robot,enabling accurate identification of slipping legs even under simultaneous multi-leg slippage.For state estimation,an invariant extended Kalman filter is employed to fuse the motion information with the detected slip event(s)to obtain the robot state.By incorporating slip event(s)and foot velocity into the system motion equation of the filter,the proposed method better leverages leg odometry information and achieves more precise state estimation compared with existing methods.Simulations on a quadruped and a hexapod demonstrate the effectiveness and increased accuracy during multi-leg slippage.Experimental results for the quadruped robot show that the proposed approach achieves a 48% reduction in the root mean square error and a 47%reduction in the maximum error in velocity estimation under severe multi-leg slippage compared with the existing methods.展开更多
In order to achieve omnidirectional locomotion on rough terrain with multi-legged biomimetic robot,a free gait generation approach is proposed based on local rules.The phase coordinates of each operation leg was estab...In order to achieve omnidirectional locomotion on rough terrain with multi-legged biomimetic robot,a free gait generation approach is proposed based on local rules.The phase coordinates of each operation leg was established according to the motion task and a universal depiction of leg-end locomotion was implemented;the mathematical relation of gait pattern and walking velocity of multi-legged robot was put forward;combined polynomial curve was adopted to generate the leg-end trajectory,which was capable of accomplishing walking missions and accommodating to landform conditions;a distributed network of local rules for gait control was constructed based on a set of local rules operating between adjacent legs.In the simulation experiments,adaptive regulation of inter-leg phase sequence,omnidirectional locomotion and ground accommodation were realized.Moreover,statically stable free gait was obtained simultaneously,which provided multi-legged robot with the capability of walking on irregular terrain reliably and expeditiously.展开更多
In this paper,we propose a new gait planning method for a multi-legged robot which has only 1 degree-of-freedom in each leg and has a passive body joint between two body segments.We firstly introduce the Finite State ...In this paper,we propose a new gait planning method for a multi-legged robot which has only 1 degree-of-freedom in each leg and has a passive body joint between two body segments.We firstly introduce the Finite State Machine(FSM)to the undulatory gait planning method of the 2n-legged robot.Then,the undulatory gait sequence for straight line motion is achieved by undulations motion.The idea that legged locomotion is achievable by less actuation of 2n-legged robot as well as the gait planning methods are verified finally by simulations and experiments.展开更多
Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation...Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation is usually used for control compensation of manipulator arm,the error compensation of multi-legged robots has seldom been explored.In order to reduce the kinematic error of robots,a motion error compensation method based on the feedforward for multi-legged mobile robots is proposed to improve motion precision of a mobile robot.The locus error of a robot body is measured,when robot moves along a given track.Error of driven joint variables is obtained by error calculation model in terms of the locus error of robot body.Error value is used to compensate driven joint variables and modify control model of robot,which can drive the robots following control model modified.The model of the relation between robot＇s locus errors and kinematic variables errors is set up to achieve the kinematic error compensation.On the basis of the inverse kinematics of a multi-legged walking robot,the relation between error of the motion trajectory and driven joint variables of robots is discussed.Moreover,the equation set is obtained,which expresses relation among error of driven joint variables,structure parameters and error of robot＇s locus.Take MiniQuad as an example,when the robot MiniQuad moves following beeline tread,motion error compensation is studied.The actual locus errors of the robot body are measured before and after compensation in the test.According to the test,variations of the actual coordinate value of the robot centroid in x-direction and z-direction are reduced more than one time.The kinematic errors of robot body are reduced effectively by the use of the motion error compensation method based on the feedforward.展开更多
The semi-round rigid feet would cause position-posture deviation problem because the actual foothold position is hardly known due to the rolling effect of the semi-round rigid feet during the robot walking. The positi...The semi-round rigid feet would cause position-posture deviation problem because the actual foothold position is hardly known due to the rolling effect of the semi-round rigid feet during the robot walking. The position-posture deviation problem may harm to the stability and the harmony of the robot, or even makes the robot tip over and fail to walk forward. Focused on the position-posture deviation problem of multi-legged walking robots with semi-round rigid feet, a new method of position-posture closed-loop control is proposed to solve the position-posture deviation problem caused by semi-round rigid feet, based on the inverse velocity kinematics of the multi-legged walking robots. The position-posture closed-loop control is divided into two parts: the position closed-loop control and the posture closed-loop control. Thus, the position-posture control for the robot which is a tight coupling and nonlinear system is decoupled. Co-simulations of position-posture open-loop control and position-posture closed-loop control by MATLAB and ADAMS are implemented, respectively. The co-simulation results verify that the position-posture closed-loop control performs well in solving the position-posture deviation problem caused by semi-round rigid feet.展开更多
This paper presents a new kind of leg mechanism with which the wall climbing robot can easily perform the ground to wall transition by itself.To get its walking envelope and limit position,the forward/inverse kinem...This paper presents a new kind of leg mechanism with which the wall climbing robot can easily perform the ground to wall transition by itself.To get its walking envelope and limit position,the forward/inverse kinematics and the statics of the mechanism are solved.All of these lay the foundation for ground to wall transition gait programing,mechanism parameter selection and optimization.展开更多
Single-cell biomechanics and electrophysiology measuring tools have transformed biological research over the last few decades,which enabling a comprehensive and nuanced understanding of cellular behavior and function....Single-cell biomechanics and electrophysiology measuring tools have transformed biological research over the last few decades,which enabling a comprehensive and nuanced understanding of cellular behavior and function.Despite their high-quality information content,these single-cell measuring techniques suffer from laborious manual processing by highly skilled workers and extremely low throughput(tens of cells per day).Recently,numerous researchers have automated the measurement of cell mechanical and electrical signals through robotic localization and control processes.While these efforts have demonstrated promising progress,critical challenges persist,including human dependency,learning complexity,in-situ measurement,and multidimensional signal acquisition.To identify key limitations and highlight emerging opportunities for innovation,in this review,we comprehensively summarize the key steps of robotic technologies in single-cell biomechanics and electrophysiology.We also discussed the prospects and challenges of robotics and automation in biological research.By bridging gaps between engineering,biology,and data science,this work aims to stimulate interdisciplinary research and accelerate the translation of robotic single-cell technologies into practical applications in the life sciences and medical fields.展开更多
Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challeng...Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challenge due to factors such as light scattering,absorption,restricted visibility,and ambient noise.The advancement of deep learning has introduced powerful techniques for processing large amounts of unstructured and imperfect data collected from underwater environments.This study evaluated the efficacy of the You Only Look Once(YOLO)algorithm,a real-time object detection and localization model based on convolutional neural networks,in identifying and classifying various types of pipeline defects in underwater settings.YOLOv8,the latest evolution in the YOLO family,integrates advanced capabilities,such as anchor-free detection,a cross-stage partial network backbone for efficient feature extraction,and a feature pyramid network+path aggregation network neck for robust multi-scale object detection,which make it particularly well-suited for complex underwater environments.Due to the lack of suitable open-access datasets for underwater pipeline defects,a custom dataset was captured using a remotely operated vehicle in a controlled environment.This application has the following assets available for use.Extensive experimentation demonstrated that YOLOv8 X-Large consistently outperformed other models in terms of pipe defect detection and classification and achieved a strong balance between precision and recall in identifying pipeline cracks,rust,corners,defective welds,flanges,tapes,and holes.This research establishes the baseline performance of YOLOv8 for underwater defect detection and showcases its potential to enhance the reliability and efficiency of pipeline inspection tasks in challenging underwater environments.展开更多
Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2)...Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.展开更多
At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown ...At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments,this paper proposes an Attention-Enhanced Dueling Deep Q-Network(ADDueling DQN),which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework.A multi-objective reward function,centered on energy efficiency,is designed to comprehensively consider path length,terrain slope,motion smoothness,and obstacle avoidance,enabling optimal low-energy trajectory generation in 3D space from the source.The incorporation of a multihead attention mechanism allows the model to dynamically focus on energy-critical state features—such as slope gradients and obstacle density—thereby significantly improving its ability to recognize and avoid energy-intensive paths.Additionally,the prioritized experience replay mechanism accelerates learning from key decision-making experiences,suppressing inefficient exploration and guiding the policy toward low-energy solutions more rapidly.The effectiveness of the proposed path planning algorithm is validated through simulation experiments conducted in multiple off-road scenarios.Results demonstrate that AD-Dueling DQN consistently achieves the lowest average energy consumption across all tested environments.Moreover,the proposed method exhibits faster convergence and greater training stability compared to baseline algorithms,highlighting its global optimization capability under energy-aware objectives in complex terrains.This study offers an efficient and scalable intelligent control strategy for the development of energy-conscious autonomous navigation systems.展开更多
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
基金Supported by National Natural Science Foundation of China(Grant No.51735009).
文摘The paper proposes a novel multi-legged robot with pitch adjustive units aiming at obstacle surmounting.With only 6 degrees of freedom,the robot with 16 mechanical legs walks steadily and surmounts the obstacles on the complex terrain.The leg unit with adjustive pitch provides a large workspace and empowers the legs to climb up obstacles in large sizes,which enhances the obstacle surmounting capability.The pitch adjustment in leg unit requires as few independent adjusting actuators as possible.Based on the kinematic analysis of the mechanical leg,the biped and quadruped leg units with adjustive pitch are analyzed and compared.The configuration of the robot is designed to obtain a compact structure and pragmatic performance.The uncertainty of the obstacle size and position in the surmounting process is taken into consideration and the parameters of the adjustments and the feasible strategies for obstacle surmounting are presented.Then the 3D virtual model and the robot prototype are built and the multi-body dynamic simulations and prototype experiments are carried out.The results from the simulations and the experiments show that the robot possesses good obstacle surmounting capabilities.
基金supported by the National Natural Science Foundation of China(Grant No.52375014)Guangdong Innovative and Entrepreneurial Research Team Program,China(Grant No.2019ZT08Z780)Dongguan Introduction Program of Leading Innovative and Entrepreneurial Talents,China(Grant No.20181220).
文摘Real-time slip detection and state estimation are crucial for locomotion control,facilitating posture adjustment and stability recovery of multi-legged robots moving on slippery terrain.However,existing proprioceptive methods rely on the fixed-contact assumption with fixed noise and suffer from low accuracy when multiple legs slip simultaneously.This paper proposes a novel proprioceptive approach for multi-legged robots moving in slippery scenarios to cope with slippage of multiple legs.In slip detection,the proprioceptive states of the robot are fed into a convolutional neural network to detect slip event(s)of the robot,enabling accurate identification of slipping legs even under simultaneous multi-leg slippage.For state estimation,an invariant extended Kalman filter is employed to fuse the motion information with the detected slip event(s)to obtain the robot state.By incorporating slip event(s)and foot velocity into the system motion equation of the filter,the proposed method better leverages leg odometry information and achieves more precise state estimation compared with existing methods.Simulations on a quadruped and a hexapod demonstrate the effectiveness and increased accuracy during multi-leg slippage.Experimental results for the quadruped robot show that the proposed approach achieves a 48% reduction in the root mean square error and a 47%reduction in the maximum error in velocity estimation under severe multi-leg slippage compared with the existing methods.
基金Sponsored by the National High Technology Research and Development Program of China(Grant No. 2006AA04Z245)the Program for Changjiang Scholars and Innovative Research Team in University(Grant No. IRT0423)
文摘In order to achieve omnidirectional locomotion on rough terrain with multi-legged biomimetic robot,a free gait generation approach is proposed based on local rules.The phase coordinates of each operation leg was established according to the motion task and a universal depiction of leg-end locomotion was implemented;the mathematical relation of gait pattern and walking velocity of multi-legged robot was put forward;combined polynomial curve was adopted to generate the leg-end trajectory,which was capable of accomplishing walking missions and accommodating to landform conditions;a distributed network of local rules for gait control was constructed based on a set of local rules operating between adjacent legs.In the simulation experiments,adaptive regulation of inter-leg phase sequence,omnidirectional locomotion and ground accommodation were realized.Moreover,statically stable free gait was obtained simultaneously,which provided multi-legged robot with the capability of walking on irregular terrain reliably and expeditiously.
文摘In this paper,we propose a new gait planning method for a multi-legged robot which has only 1 degree-of-freedom in each leg and has a passive body joint between two body segments.We firstly introduce the Finite State Machine(FSM)to the undulatory gait planning method of the 2n-legged robot.Then,the undulatory gait sequence for straight line motion is achieved by undulations motion.The idea that legged locomotion is achievable by less actuation of 2n-legged robot as well as the gait planning methods are verified finally by simulations and experiments.
基金supported by National Natural Science Foundation of China (Grant Nos. 50675079,50875246)Program for Innovative Research Team (in Science and Technology) in University of Henan Province,China
文摘Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation is usually used for control compensation of manipulator arm,the error compensation of multi-legged robots has seldom been explored.In order to reduce the kinematic error of robots,a motion error compensation method based on the feedforward for multi-legged mobile robots is proposed to improve motion precision of a mobile robot.The locus error of a robot body is measured,when robot moves along a given track.Error of driven joint variables is obtained by error calculation model in terms of the locus error of robot body.Error value is used to compensate driven joint variables and modify control model of robot,which can drive the robots following control model modified.The model of the relation between robot＇s locus errors and kinematic variables errors is set up to achieve the kinematic error compensation.On the basis of the inverse kinematics of a multi-legged walking robot,the relation between error of the motion trajectory and driven joint variables of robots is discussed.Moreover,the equation set is obtained,which expresses relation among error of driven joint variables,structure parameters and error of robot＇s locus.Take MiniQuad as an example,when the robot MiniQuad moves following beeline tread,motion error compensation is studied.The actual locus errors of the robot body are measured before and after compensation in the test.According to the test,variations of the actual coordinate value of the robot centroid in x-direction and z-direction are reduced more than one time.The kinematic errors of robot body are reduced effectively by the use of the motion error compensation method based on the feedforward.
基金Project(51221004)supported by the Science Fund for Creative Research Groups of National Natural Science Foundation of ChinaProject supported by the Program for Zhejiang Leading Team of S&T Innovation,China
文摘The semi-round rigid feet would cause position-posture deviation problem because the actual foothold position is hardly known due to the rolling effect of the semi-round rigid feet during the robot walking. The position-posture deviation problem may harm to the stability and the harmony of the robot, or even makes the robot tip over and fail to walk forward. Focused on the position-posture deviation problem of multi-legged walking robots with semi-round rigid feet, a new method of position-posture closed-loop control is proposed to solve the position-posture deviation problem caused by semi-round rigid feet, based on the inverse velocity kinematics of the multi-legged walking robots. The position-posture closed-loop control is divided into two parts: the position closed-loop control and the posture closed-loop control. Thus, the position-posture control for the robot which is a tight coupling and nonlinear system is decoupled. Co-simulations of position-posture open-loop control and position-posture closed-loop control by MATLAB and ADAMS are implemented, respectively. The co-simulation results verify that the position-posture closed-loop control performs well in solving the position-posture deviation problem caused by semi-round rigid feet.
文摘This paper presents a new kind of leg mechanism with which the wall climbing robot can easily perform the ground to wall transition by itself.To get its walking envelope and limit position,the forward/inverse kinematics and the statics of the mechanism are solved.All of these lay the foundation for ground to wall transition gait programing,mechanism parameter selection and optimization.
基金the National Natural Science Foundation of China[62525301,62127811,62433019]the New Cornerstone Science Foundation through the XPLORER PRIZEthe financial support by the China Postdoctoral Science Foundation[GZB20240797].
文摘Single-cell biomechanics and electrophysiology measuring tools have transformed biological research over the last few decades,which enabling a comprehensive and nuanced understanding of cellular behavior and function.Despite their high-quality information content,these single-cell measuring techniques suffer from laborious manual processing by highly skilled workers and extremely low throughput(tens of cells per day).Recently,numerous researchers have automated the measurement of cell mechanical and electrical signals through robotic localization and control processes.While these efforts have demonstrated promising progress,critical challenges persist,including human dependency,learning complexity,in-situ measurement,and multidimensional signal acquisition.To identify key limitations and highlight emerging opportunities for innovation,in this review,we comprehensively summarize the key steps of robotic technologies in single-cell biomechanics and electrophysiology.We also discussed the prospects and challenges of robotics and automation in biological research.By bridging gaps between engineering,biology,and data science,this work aims to stimulate interdisciplinary research and accelerate the translation of robotic single-cell technologies into practical applications in the life sciences and medical fields.
文摘Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challenge due to factors such as light scattering,absorption,restricted visibility,and ambient noise.The advancement of deep learning has introduced powerful techniques for processing large amounts of unstructured and imperfect data collected from underwater environments.This study evaluated the efficacy of the You Only Look Once(YOLO)algorithm,a real-time object detection and localization model based on convolutional neural networks,in identifying and classifying various types of pipeline defects in underwater settings.YOLOv8,the latest evolution in the YOLO family,integrates advanced capabilities,such as anchor-free detection,a cross-stage partial network backbone for efficient feature extraction,and a feature pyramid network+path aggregation network neck for robust multi-scale object detection,which make it particularly well-suited for complex underwater environments.Due to the lack of suitable open-access datasets for underwater pipeline defects,a custom dataset was captured using a remotely operated vehicle in a controlled environment.This application has the following assets available for use.Extensive experimentation demonstrated that YOLOv8 X-Large consistently outperformed other models in terms of pipe defect detection and classification and achieved a strong balance between precision and recall in identifying pipeline cracks,rust,corners,defective welds,flanges,tapes,and holes.This research establishes the baseline performance of YOLOv8 for underwater defect detection and showcases its potential to enhance the reliability and efficiency of pipeline inspection tasks in challenging underwater environments.
基金supported by the National Natural Science Foundation of China(22168008,22378085)the Guangxi Natural Science Foundation(2024GXNSFDA010053)+1 种基金the Technology Development Project of Guangxi Bossco Environmental Protection Technology Co.,Ltd(202100039)Innovation Project of Guangxi Graduate Education(YCBZ2024065).
文摘Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.
文摘At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments,this paper proposes an Attention-Enhanced Dueling Deep Q-Network(ADDueling DQN),which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework.A multi-objective reward function,centered on energy efficiency,is designed to comprehensively consider path length,terrain slope,motion smoothness,and obstacle avoidance,enabling optimal low-energy trajectory generation in 3D space from the source.The incorporation of a multihead attention mechanism allows the model to dynamically focus on energy-critical state features—such as slope gradients and obstacle density—thereby significantly improving its ability to recognize and avoid energy-intensive paths.Additionally,the prioritized experience replay mechanism accelerates learning from key decision-making experiences,suppressing inefficient exploration and guiding the policy toward low-energy solutions more rapidly.The effectiveness of the proposed path planning algorithm is validated through simulation experiments conducted in multiple off-road scenarios.Results demonstrate that AD-Dueling DQN consistently achieves the lowest average energy consumption across all tested environments.Moreover,the proposed method exhibits faster convergence and greater training stability compared to baseline algorithms,highlighting its global optimization capability under energy-aware objectives in complex terrains.This study offers an efficient and scalable intelligent control strategy for the development of energy-conscious autonomous navigation systems.
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.
