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
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
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
This paper presents an adaptive formation control method for a heterogeneous robot swarm,utilising a multilevel formation task tree to model various types of formation tasks and a single-state distributed k-winner-tak...This paper presents an adaptive formation control method for a heterogeneous robot swarm,utilising a multilevel formation task tree to model various types of formation tasks and a single-state distributed k-winner-take-all(S-DKWTA)algorithm to address the MRTA problem.In addition,we propose an enhanced load reassignment algorithm to resolve conflicts when using S-DKWTA.The S-DKWTA algorithm demonstrates the capability to manage multiple objectives and dynamically select leaders in real-time,thereby optimising formation efficiency and reducing energy consumption.The proposed approach integrates an enhanced artificial potential field(APF)to govern the motion of heterogeneous robot systems which encompasses both unmanned ground vehicles(UGVs)and unmanned aerial vehicles(UAVs),thereby achieving collision and obstacle avoidance.Simulations employing UGVs and UAVs swarm to achieve formation movement demonstrate the efficacy of this approach.The amalgamation of S-DKWTA and improved APF ensures stable and adaptable formation control,underscoring its potential for diverse multirobot applications.展开更多
In recent years,the rising incidence of gastrointestinal(GI)cancer has triggered an urgent need for effective early intervention strategies.Traditional endoscopic techniques often cause patient discomfort,and it is di...In recent years,the rising incidence of gastrointestinal(GI)cancer has triggered an urgent need for effective early intervention strategies.Traditional endoscopic techniques often cause patient discomfort,and it is difficult to navigate deep regions of complex organ structures.This work proposes a kind of bio-inspired magnetic soft robot(BMSR)to address these challenges.The design of the BMSRs is inspired by the rolling motion of the golden wheel spider.Two six-degree-of-freedom(6-DOF)robotic arms are used,where one arm is responsible for real-time manipulation of the BMSRs,and the other is dedicated to monitoring their status.Under the actuation of an external rotating magnetic field,the BMSRs can flexibly climb on inclined surfaces at any angle,involving the inverted surface.Through the powerful output force,the BMSRs can overcome the mobility barrier induced by different human organs,including mucus,folds,and height differences of up to 8 cm.Such an exceptional mobility enables the BMSRs to deliver drugs in the targeted complex GI environment.Moreover,in combination with an endoscope,it provides real-time visual feedback for precise navigation.In vitro animal experiments validate the feasibility of BMSRs,paving a way for their usage in minimally invasive GI treatment.This work advances the potential applications of magnetic soft robots in the biomedical field.展开更多
The Chinese SME’s vision shows the bright side of humanoid robots:rather than replacing human workers,they are handling everyday mechanical tasks,leaving human staff to focus on improving service and emotional experi...The Chinese SME’s vision shows the bright side of humanoid robots:rather than replacing human workers,they are handling everyday mechanical tasks,leaving human staff to focus on improving service and emotional experiences.IN the Jinqiao Economic and Technological Development Zone in Pudong New Area,Shanghai,KEENON Robotics,a national-level“Little Giant”(innovative SME),is leading the transformation of the service robots industry.Amid the wave of embodied intelligence development,the humanoid service robots created by this company have become a focal point of the industry and businesses alike.展开更多
Humans can learn complex and dexterous manipulation tasks by observing videos,imitating and exploring.Multiple endeffectors manipulation of free micron-sized deformable cells is one of the challenging tasks in robotic...Humans can learn complex and dexterous manipulation tasks by observing videos,imitating and exploring.Multiple endeffectors manipulation of free micron-sized deformable cells is one of the challenging tasks in robotic micromanipulation.We propose an imitation-enhanced reinforcement learning method inspired by the human learning process that enables robots to learn cell micromanipulation skills from videos.Firstly,for the microscopic robot micromanipulation videos,a multi-task observation(MTO)network is designed to identify the two end-effectors and the manipulated objects to obtain the spatiotemporal trajectories.The spatiotemporal constraints of the robot's actions are obtained by the task-parameterised hidden Markov model(THMM).To simultaneously address the safety and dexterity of robot micromanipulation,an imitation learning optimisation-based soft actor-critic(ILOSAC)algorithm is proposed in which the robot can perform skill learning by demonstration and exploration.The proposed method is capable of performing complex cell manipulation tasks in a realistic physical environment.Experiments indicated that compared with current methods and manual remote manipulation,the proposed framework achieved a shorter operation time and less deformation of cells,which is expected to facilitate the development of robot skill learning.展开更多
With the progress of Industry 4.0,collaborative robots(cobots) have become a key area of innovation.However,safety standards such as ISO/TS 15066 often lag behind rapid technological advances,failing to balance safety...With the progress of Industry 4.0,collaborative robots(cobots) have become a key area of innovation.However,safety standards such as ISO/TS 15066 often lag behind rapid technological advances,failing to balance safety and innovation.This paper analyzes the conflicts between standards and innovation of industrial cobots,including lag,rigidity,and safetyperformance trade-offs.It proposes flexible standards,regulatory sandboxes,and lifecycle safety approaches to align safety with technological progress.展开更多
Dear Editor,This letter presents a model predictive control(MPC)scheme for human-robot interaction(HRI)in a multi-joint exoskeleton robot(ER)driven by series elastic actuator(SEA).The proposed scheme in robot-in-charg...Dear Editor,This letter presents a model predictive control(MPC)scheme for human-robot interaction(HRI)in a multi-joint exoskeleton robot(ER)driven by series elastic actuator(SEA).The proposed scheme in robot-in-charge(RIC)mode facilitates the ER driven by SEA to provide the required assistance and support for the subject.展开更多
Mobile wheel-legged robots exhibiting mobility,stability and reliability have garnered heightened research attention in demanding real-world scenarios,especially in material transport,emergency response and space expl...Mobile wheel-legged robots exhibiting mobility,stability and reliability have garnered heightened research attention in demanding real-world scenarios,especially in material transport,emergency response and space exploration.The kinematics model merely delineates the geometric relationship of the controlled objective,disregarding force feedback.This study investigates model predictive trajectory tracking control utilising the robot dynamic model(DRMPC)in the context of unpredictable interactions.The predictive tracking controller for the wheel-legged robot is introduced in the context of position tracking.A dynamic approximator is employed to address the uncertain interactions in the tracking process.Ultimately,cosimulation and empirical tests are conducted to demonstrate the efficacy of the devised control methodology,which achieves high precision and dependable robustness.This work can elucidate the technical and practical oversight of autonomous movement in complicated environments and enhance the manoeuverability and flexibility.展开更多
Objective:Robotic colorectal surgery(RCS)provides a stable,magnifiedthree-dimensional visual field and enhanced ergonomics enabling precise dissection and tremor suppression.We postulate that this technique is associa...Objective:Robotic colorectal surgery(RCS)provides a stable,magnifiedthree-dimensional visual field and enhanced ergonomics enabling precise dissection and tremor suppression.We postulate that this technique is associated with less tissue trauma and improved postoperative outcomes than laparoscopic colorectal surgery(LCS).This study aimed to explore the inflammatoryresponse following RCS by measuring postoperative C-reactive protein(CRP)levels and compare them with LCS data reported in the literature.Methods:This single centre retrospective study included consecutive elective robotic colon and rectum resections via the da Vinci®Xi platform for benign and malignant colorectal tumours,performed by a single surgeon between January 2017 and December 2023 at the Sydney Adventist Hospital,Sydney.CRP values were measured on post-operative days(PODs)3 and 5.A narrative review of the literature was performed via EMBASE,MEDLINE via PubMed and Google Scholar from inception to December 2024 for comparative CRP values following LCS.Descriptive statistical comparisons were performed between the RCS and LCS.Results:One hundred ninety-three patients were identifiedin the RCS cohort.The median age was 73 y(range:62–83 y).Most colectomies were performed for adenocarcinoma(90.2%),with right hemicolectomy being the most common type of procedure(49.3%).The median CRP levels on PODs 3 and 5 were 83.10 mg/L(IQR:49.80–124.12 mg/L)and 26.20 mg/L(IQR:17.70–80.00 mg/L),respectively.The reported CRP after LCS was heterogeneous,with mean POD 3 values ranging from 69 mg/L to 99.5 mg/L,and mean POD 4–5 values ranging from 62.4 mg/L to 72.85 mg/L.Conclusions:There were similar,if not lower,POD 3 and 5 CRP values,suggesting that RCS was probably non-inferior to LCS regarding postoperative tissue trauma.In particular,there appeared to be a quicker recovery of the inflammatory response with RCS.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
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.
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.
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supported by the National Natural Science Foundation of China(624B2140).
文摘This paper presents an adaptive formation control method for a heterogeneous robot swarm,utilising a multilevel formation task tree to model various types of formation tasks and a single-state distributed k-winner-take-all(S-DKWTA)algorithm to address the MRTA problem.In addition,we propose an enhanced load reassignment algorithm to resolve conflicts when using S-DKWTA.The S-DKWTA algorithm demonstrates the capability to manage multiple objectives and dynamically select leaders in real-time,thereby optimising formation efficiency and reducing energy consumption.The proposed approach integrates an enhanced artificial potential field(APF)to govern the motion of heterogeneous robot systems which encompasses both unmanned ground vehicles(UGVs)and unmanned aerial vehicles(UAVs),thereby achieving collision and obstacle avoidance.Simulations employing UGVs and UAVs swarm to achieve formation movement demonstrate the efficacy of this approach.The amalgamation of S-DKWTA and improved APF ensures stable and adaptable formation control,underscoring its potential for diverse multirobot applications.
基金supported in part by the National Natural Science Foundation of China under grant 52175556the Macao Science and Technology Development Fund under grant 0004/2022/AKP,0102/2022/A2,and 0078/2023/RIB3+1 种基金the Research Committee of the University of Macao under grants MYRG2022-00068-FST and MYRG-CRG202200004-FST-ICIthe Guangdong Basic and Applied Basic Research Foundation under grant 2023A1515011178。
文摘In recent years,the rising incidence of gastrointestinal(GI)cancer has triggered an urgent need for effective early intervention strategies.Traditional endoscopic techniques often cause patient discomfort,and it is difficult to navigate deep regions of complex organ structures.This work proposes a kind of bio-inspired magnetic soft robot(BMSR)to address these challenges.The design of the BMSRs is inspired by the rolling motion of the golden wheel spider.Two six-degree-of-freedom(6-DOF)robotic arms are used,where one arm is responsible for real-time manipulation of the BMSRs,and the other is dedicated to monitoring their status.Under the actuation of an external rotating magnetic field,the BMSRs can flexibly climb on inclined surfaces at any angle,involving the inverted surface.Through the powerful output force,the BMSRs can overcome the mobility barrier induced by different human organs,including mucus,folds,and height differences of up to 8 cm.Such an exceptional mobility enables the BMSRs to deliver drugs in the targeted complex GI environment.Moreover,in combination with an endoscope,it provides real-time visual feedback for precise navigation.In vitro animal experiments validate the feasibility of BMSRs,paving a way for their usage in minimally invasive GI treatment.This work advances the potential applications of magnetic soft robots in the biomedical field.
文摘The Chinese SME’s vision shows the bright side of humanoid robots:rather than replacing human workers,they are handling everyday mechanical tasks,leaving human staff to focus on improving service and emotional experiences.IN the Jinqiao Economic and Technological Development Zone in Pudong New Area,Shanghai,KEENON Robotics,a national-level“Little Giant”(innovative SME),is leading the transformation of the service robots industry.Amid the wave of embodied intelligence development,the humanoid service robots created by this company have become a focal point of the industry and businesses alike.
基金supported in part with the General Programme of the National Natural Science Foundation of China(Grant 62576312)the Key Research and Development Program of Zhejiang Province(Grant 2025C01132)the Shandong Province Key R&D Plan Project(Grant 2022LZGC020).
文摘Humans can learn complex and dexterous manipulation tasks by observing videos,imitating and exploring.Multiple endeffectors manipulation of free micron-sized deformable cells is one of the challenging tasks in robotic micromanipulation.We propose an imitation-enhanced reinforcement learning method inspired by the human learning process that enables robots to learn cell micromanipulation skills from videos.Firstly,for the microscopic robot micromanipulation videos,a multi-task observation(MTO)network is designed to identify the two end-effectors and the manipulated objects to obtain the spatiotemporal trajectories.The spatiotemporal constraints of the robot's actions are obtained by the task-parameterised hidden Markov model(THMM).To simultaneously address the safety and dexterity of robot micromanipulation,an imitation learning optimisation-based soft actor-critic(ILOSAC)algorithm is proposed in which the robot can perform skill learning by demonstration and exploration.The proposed method is capable of performing complex cell manipulation tasks in a realistic physical environment.Experiments indicated that compared with current methods and manual remote manipulation,the proposed framework achieved a shorter operation time and less deformation of cells,which is expected to facilitate the development of robot skill learning.
文摘With the progress of Industry 4.0,collaborative robots(cobots) have become a key area of innovation.However,safety standards such as ISO/TS 15066 often lag behind rapid technological advances,failing to balance safety and innovation.This paper analyzes the conflicts between standards and innovation of industrial cobots,including lag,rigidity,and safetyperformance trade-offs.It proposes flexible standards,regulatory sandboxes,and lifecycle safety approaches to align safety with technological progress.
基金supported in part by the National Natural Science Foundation of China(62173048,62373065,61873304,62106023)the Key Science and Technology Projects of Jilin Province,China(20230204081YY)the Research and Innovation Team of Anhui Province(2024AH010023)。
文摘Dear Editor,This letter presents a model predictive control(MPC)scheme for human-robot interaction(HRI)in a multi-joint exoskeleton robot(ER)driven by series elastic actuator(SEA).The proposed scheme in robot-in-charge(RIC)mode facilitates the ER driven by SEA to provide the required assistance and support for the subject.
基金supported by the National Natural Science Foundation of China(62203176,62173038)Guangzhou Key Research and Development Program(2025B03J0072)+5 种基金Guangdong High-Level Talents Special Support Programme(2024TQ08Z107)Anhui Province Natural Science Funds for Distinguished Young Scholar(2308085J02)State Key Laboratory of Intelligent Vehicle Safety Technology(IVSTSKL-202402,IVSTSKL-202430,IVSTSKL-202508,IVSTSKL-202520)State Key Laboratory of Intelligent Green Vehicle and Mobility(KFY2417)State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body(32215010),Wuhu Major Scientific and Technological Achievements Engineering Project(2021zc04).
文摘Mobile wheel-legged robots exhibiting mobility,stability and reliability have garnered heightened research attention in demanding real-world scenarios,especially in material transport,emergency response and space exploration.The kinematics model merely delineates the geometric relationship of the controlled objective,disregarding force feedback.This study investigates model predictive trajectory tracking control utilising the robot dynamic model(DRMPC)in the context of unpredictable interactions.The predictive tracking controller for the wheel-legged robot is introduced in the context of position tracking.A dynamic approximator is employed to address the uncertain interactions in the tracking process.Ultimately,cosimulation and empirical tests are conducted to demonstrate the efficacy of the devised control methodology,which achieves high precision and dependable robustness.This work can elucidate the technical and practical oversight of autonomous movement in complicated environments and enhance the manoeuverability and flexibility.
文摘Objective:Robotic colorectal surgery(RCS)provides a stable,magnifiedthree-dimensional visual field and enhanced ergonomics enabling precise dissection and tremor suppression.We postulate that this technique is associated with less tissue trauma and improved postoperative outcomes than laparoscopic colorectal surgery(LCS).This study aimed to explore the inflammatoryresponse following RCS by measuring postoperative C-reactive protein(CRP)levels and compare them with LCS data reported in the literature.Methods:This single centre retrospective study included consecutive elective robotic colon and rectum resections via the da Vinci®Xi platform for benign and malignant colorectal tumours,performed by a single surgeon between January 2017 and December 2023 at the Sydney Adventist Hospital,Sydney.CRP values were measured on post-operative days(PODs)3 and 5.A narrative review of the literature was performed via EMBASE,MEDLINE via PubMed and Google Scholar from inception to December 2024 for comparative CRP values following LCS.Descriptive statistical comparisons were performed between the RCS and LCS.Results:One hundred ninety-three patients were identifiedin the RCS cohort.The median age was 73 y(range:62–83 y).Most colectomies were performed for adenocarcinoma(90.2%),with right hemicolectomy being the most common type of procedure(49.3%).The median CRP levels on PODs 3 and 5 were 83.10 mg/L(IQR:49.80–124.12 mg/L)and 26.20 mg/L(IQR:17.70–80.00 mg/L),respectively.The reported CRP after LCS was heterogeneous,with mean POD 3 values ranging from 69 mg/L to 99.5 mg/L,and mean POD 4–5 values ranging from 62.4 mg/L to 72.85 mg/L.Conclusions:There were similar,if not lower,POD 3 and 5 CRP values,suggesting that RCS was probably non-inferior to LCS regarding postoperative tissue trauma.In particular,there appeared to be a quicker recovery of the inflammatory response with RCS.
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.
