Based on reference[1], the Automatic Control System of the Excavating Process (ACSEP) is studied and aualyzed In this paper- At first, the general structure of the control system is discussed- And theo depeded on the ...Based on reference[1], the Automatic Control System of the Excavating Process (ACSEP) is studied and aualyzed In this paper- At first, the general structure of the control system is discussed- And theo depeded on the kinematical equations, the "Generator or Expected link variable (GE)" and "Generator of Actual bucket trajectory (CA)" are put forward. Finally, based on the current technology and existing techniques of WD-400 Mechanical Forward Excavator (MFE), the automatic system of excavating process composed of two relatively indepodent sub-systems is designed with simple but practical structure’ According to the computer simulation, this control system has high tracking precision to the desired trajectory and good adaptive capacity to the load disturbance.展开更多
From the view of robotics, kinematical and dynamical analyses of the WD400 Mechanical Forward Excavator are carried out in this paper. Transformation of the manipulator abstracted from the excavator is determined. For...From the view of robotics, kinematical and dynamical analyses of the WD400 Mechanical Forward Excavator are carried out in this paper. Transformation of the manipulator abstracted from the excavator is determined. Forward and Inverse kinematical analyses are given and the trajectories of bucket movement and their mathematic descriptions are derived. The kinematical and dynamical models as well as the excavating resistance along the trajectories are obtained. The computer simulations are included in this paper.展开更多
Banana de-handing is an important part of banana post-harvesting operation.The traditional artificial de-handing model has problems such as labor intensity,inaccurate cutting,uneven cutting surface,unstable catching,a...Banana de-handing is an important part of banana post-harvesting operation.The traditional artificial de-handing model has problems such as labor intensity,inaccurate cutting,uneven cutting surface,unstable catching,and damage of banana fruit,etc.The mapping relationship between the characteristic parameters of the movement posture of the cutter and the influencing factors of the contact stress of banana crown cutting in unstructured environments,and the changing rules of the bumping contact stress of complex multi-shaped banana fruit with the physical property parameters of the cushioning material are the theoretical and technical difficulties that urgently need to be solved in the realization of banana mechanical de-handing.The future research(research on the coupling mechanism of visual cognition-mechanism cutting and low-destructive catching method of full-field continuous de-handing of bananas under multi-constraint scenarios)should:(1)create a database of banana crown,obtain the optimal banana crown recognition model,develop a recognition and locating system of the cutting line of banana crown and obtain its spatial location information;(2)establish the discrete element mechanical model of banana crown and the interaction model between banana crown and the cutter,clarify the stress change and the force wave transmission characteristics of the cutting process,construct the multi-objective optimization equation of the cutting performance,obtain the best combination of cutting parameters,and ascertain the mechanisms of synergistic locating and continuous cutting of banana crown;(3)establish the contact mechanical model of banana fruit drop-bump,parse the bumping characteristics between banana fruit and cushioning material,construct mathematical equations to quantitatively assess damage results,and determine the detract catching method of banana fruit that matches the de-handing mode in multi-constraint scenarios.This study showed that the real-time identification and spatial positioning of fruit,the mechanical properties of crown and the optimization of cutting performance,the damage mechanism of fruit and its loss-reducing harvesting method are the three key breakthroughs in realizing the robotization of de-handing.The current bottleneck problems and future research directions of intelligent banana de-handing were pointed out in this paper,which can provide a theoretical basis for the optimal design of banana de-handing devices and provide technical support for promoting the practical application of intelligent de-handing equipment.展开更多
Magnetic soft robots are emerging as a promising technology in biomedical applications, offering precise, minimally invasive solutions for clinical procedures. Magnetic soft robots, often constructed by using magnetic...Magnetic soft robots are emerging as a promising technology in biomedical applications, offering precise, minimally invasive solutions for clinical procedures. Magnetic soft robots, often constructed by using magnetic particles embedded in flexible polymers, exhibit enhanced deformability and maneuverability, particularly at micro and nanoscale levels. This paper provides a comprehensive overview of the design, fabrication, and medical applications of these robots, focusing on the synthesis of magnetic materials, structural configurations, and actuation mechanisms. Structural designs are summarized, from simple one-dimensional forms to complex, multi-dimensional structures inspired by origami and kirigami principles. Additionally, magnetic actuation systems, including permanent magnets and electromagnetic coils, are examined for their respective roles in achieving the required precision or field strength for medical use. The potential applications in medicine are vast, ranging from targeted drug delivery and minimally invasive surgeries to disease diagnosis and treatment, with specific examples in tumor targeting, Alzheimer's therapy, and endodontics. The paper also addresses emerging applications in assisted reproduction and microbiota regulation. Despite challenges related to power supply, real-time tracking, and material safety, the review highlights the significant potential of magnetic soft robots to revolutionize healthcare practices.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
Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narr...Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narrow passages,slow convergence,and high computational costs.To address these challenges,this paper proposes a novel hybrid global path planning algorithm integrating Gaussian sampling and quadtree optimization(RRT^(*)-GSQ).This methodology aims to enhance path planning by synergistically combining a Gaussian mixture sampling strategy to improve node generation in critical regions,an adaptive step-size and direction optimization mechanism for enhanced obstacle avoidance,a Quadtree-AABB collision detection framework to lower computational complexity,and a dynamic iteration control strategy for more efficient convergence.In obstacle-free and obstructed scenarios,compared with the conventional RRT^(*),the proposed algorithm reduced the number of node evaluations by 67.57%and 62.72%,and decreased the search time by 79.72%and 78.52%,respectively.In path tracking tests,the proposed algorithm achieved substantial reductions in RMSE of the final path compared to the conventional RRT^(*).Specifically,the lateral RMSE was reduced by 41.5%in obstacle-free environments and 59.3%in obstructed environments,while the longitudinal RMSE was reduced by 57.2%and 58.5%,respectively.Furthermore,the maximum absolute errors in both lateral and longitudinal directions were constrained within 0.75 m.Field validation experiments in an operational orchard confirmed the algorithm's practical effectiveness,showing reductions in the mean tracking error of 47.6%(obstacle-free)and 58.3%(with obstructed),alongside a 5.1%and 7.2%shortening of the path length compared to the baseline method.The proposed algorithm effectively enhances path planning efficiency and navigation accuracy for robots,presenting a superior solution for high-precision autonomous navigation of agricultural robots in orchard environments and holding significant value for engineering applications.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
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
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
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
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
The intrinsic pressure framework,which treats self-propelling force as an external force,provides a convenient and consistent description of mechanical equilibrium in active matter.However,direct experimental evidence...The intrinsic pressure framework,which treats self-propelling force as an external force,provides a convenient and consistent description of mechanical equilibrium in active matter.However,direct experimental evidence is still lacking.To validate this framework,here we employ a programmable robotic platform,where a single light-controlled wheeled robot travels in an activity landscape.Our experiments quantitatively demonstrate that the intrinsic pressure difference across the activity interface is balanced by the emerged polarization force.This result unambiguously confirms the theoretical predictions,thus validating the intrinsic pressure framework and laying the experimental foundation for the intrinsic pressure-based mechanical description of dry active matter.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
Human life is invaluable,and timely efforts are crucial to rescue individuals trapped under debris following an earthquake.To identify opportunities for improving post-earthquake search and rescue(SAR)robotics,we get ...Human life is invaluable,and timely efforts are crucial to rescue individuals trapped under debris following an earthquake.To identify opportunities for improving post-earthquake search and rescue(SAR)robotics,we get insights through four different sources:(i)A literature review of disaster robotics and victim psychology,(ii)A public survey on earthquake awareness and their view of rescue robots,(iii)Semi-structured interviews with first responders,and(iv)Responses from GenAI chatbots which were prompted to assume the role of expert rescuers.The triangulated analysis show that there are challenges in mobility,autonomy,communication,situational awareness,and human-robot collaboration.The public respondents showed high acceptance of robot-assisted rescue and prioritised survivor detection,sensing,and communication as essential functionalities of robots.The experts expressed limitations in current equipment,the need for improved victim localisation,and interest in XR-based training and robot-assisted debris handling.The GenAI chatbots highlighted structural risk assessment,multi-sensor fusion,and supervised autonomy.Therefore,this study identifies critical robot features,outlines multi-modal interaction requirements,and highlights gaps in current SAR practice.These findings offer robot design directions for developing effective,trustworthy SAR robots,which can be integrated to future response disaster-workflows.展开更多
Carbon Fiber Reinforced Polymer(CFRP)and aluminum stacked are widely used in aircraft assemble thanks to the high strength-to-weight ratio.Riveting is an important joining technique of stacked structure and requires d...Carbon Fiber Reinforced Polymer(CFRP)and aluminum stacked are widely used in aircraft assemble thanks to the high strength-to-weight ratio.Riveting is an important joining technique of stacked structure and requires drilling and countersinking.Robotic machining systems are gradually used in the machining of holes due to their high flexibility.However,weakly rigid stacked structure and low-stiffness industrial robot system bring about complex and diverse countersinking depth errors,which significantly affects the fatigue life of components.In this paper,the influence mechanism of ultrasonic energy on the accuracy of robotic countersinking of stacked structure is investigated.Firstly,a workpiece deformation model is established with the thinwalled plate deformation theory,defined as static error.Then,the vibration of the industrial robot is calculated from the acceleration with the frequency domain integration,defined as dynamic error.The suppression of ultrasonic energy on the two kinds of errors were elucidated,respectively.Base on this,a depth compensation model of robotic ultrasonic countersinking is established.Finally,the feasibility of the accuracy compensation is experimentally verified,and the countersinking depth error can be controlled within±0.09 mm.展开更多
Since the first design of tactile sensors was proposed by Harmon in 1982,tactile sensors have evolved through four key phases:industrial applications(1980s,basic pressure detection),miniaturization via MEMS(1990s),fle...Since the first design of tactile sensors was proposed by Harmon in 1982,tactile sensors have evolved through four key phases:industrial applications(1980s,basic pressure detection),miniaturization via MEMS(1990s),flexible electronics(2010s,stretchable materials),and intelligent systems(2020s-present,AI-driven multimodal sensing).With the innovation of material,processing techniques,and multimodal fusion of stimuli,the application of tactile sensors has been continuously expanding to a diversity of areas,including but not limited to medical care,aerospace,sports and intelligent robots.Currently,researchers are dedicated to develop tactile sensors with emerging mechanisms and structures,pursuing high-sensitivity,high-resolution,and multimodal characteristics and further constructing tactile systems which imitate and approach the performance of human organs.However,challenges in the combination between the theoretical research and the practical applications are still significant.There is a lack of comprehensive understanding in the state of the art of such knowledge transferring from academic work to technical products.Scaled-up production of laboratory materials faces fatal challenges like high costs,small scale,and inconsistent quality.Ambient factors,such as temperature,humidity,and electromagnetic interference,also impair signal reliability.Moreover,tactile sensors must operate across a wide pressure range(0.1 k Pa to several or even dozens of MPa)to meet diverse application needs.Meanwhile,the existing algorithms,data models and sensing systems commonly reveal insufficient precision as well as undesired robustness in data processing,and there is a realistic gap between the designed and the demanded system response speed.In this review,oriented by the design requirements of intelligent tactile sensing systems,we summarize the common sensing mechanisms,inspired structures,key performance,and optimizing strategies,followed by a brief overview of the recent advances in the perspectives of system integration and algorithm implementation,and the possible roadmap of future development of tactile sensors,providing a forward-looking as well as critical discussions in the future industrial applications of flexible tactile sensors.展开更多
In this research,a comparative analysis was conducted on the performance and efficiency of the dual-anchor soft robot(DASR)and the extension-contraction soft robot(ECSR).These robots were constructed by imitating the ...In this research,a comparative analysis was conducted on the performance and efficiency of the dual-anchor soft robot(DASR)and the extension-contraction soft robot(ECSR).These robots were constructed by imitating the locomotion of razor clams.The penetration force for extension actuators and the anchorage force for expansion actuators in dry sand with distinct relative densities were tested by differentiating input air pressure and length-to-diameter ratios(λ).On the basis of the findings,a DASR and an ECSR were developed.DASR comprised two expansion actuators as the head and the tail segments at two ends,and one extension actuator as the middle segment.ECSR was composed of an extension actuator.A method based on the force equilibrium was introduced to ascertain and adjust the geometric parameters(length of each segment)of DASR.The burrowing-out performance and efficiency of DASR and ECSR in sands with distinct relative densities were explored.The results revealed that DASR exhibited high efficiency in dense sand in terms of lower time of burrowing-out,slip-to-advancement ratio,and cost of transport.ECSR might perform better in looser sand in terms of higher average burrowing-out velocity,higher advancement in each cycle,and lower energy consumption.However,it had larger slips than DASR.DASR could realize steady advancement and net displacement in each cycle and effectively decrease slips.These findings demonstrate the benefits and usability of the dual-anchor motion and offer new insights into the application of the dual-anchor mechanism in the burrowing of robots.展开更多
文摘Based on reference[1], the Automatic Control System of the Excavating Process (ACSEP) is studied and aualyzed In this paper- At first, the general structure of the control system is discussed- And theo depeded on the kinematical equations, the "Generator or Expected link variable (GE)" and "Generator of Actual bucket trajectory (CA)" are put forward. Finally, based on the current technology and existing techniques of WD-400 Mechanical Forward Excavator (MFE), the automatic system of excavating process composed of two relatively indepodent sub-systems is designed with simple but practical structure’ According to the computer simulation, this control system has high tracking precision to the desired trajectory and good adaptive capacity to the load disturbance.
文摘From the view of robotics, kinematical and dynamical analyses of the WD400 Mechanical Forward Excavator are carried out in this paper. Transformation of the manipulator abstracted from the excavator is determined. Forward and Inverse kinematical analyses are given and the trajectories of bucket movement and their mathematic descriptions are derived. The kinematical and dynamical models as well as the excavating resistance along the trajectories are obtained. The computer simulations are included in this paper.
基金supported by the National Natural Science Foundation of China(32271996)Zhejiang Provincial Key R&D Program of China(2022C02013 and 2021C02023)+2 种基金Bingtuan Science and Technology Program(2021 DB001)Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(GZC20232310)the China Scholarship Council.
文摘Banana de-handing is an important part of banana post-harvesting operation.The traditional artificial de-handing model has problems such as labor intensity,inaccurate cutting,uneven cutting surface,unstable catching,and damage of banana fruit,etc.The mapping relationship between the characteristic parameters of the movement posture of the cutter and the influencing factors of the contact stress of banana crown cutting in unstructured environments,and the changing rules of the bumping contact stress of complex multi-shaped banana fruit with the physical property parameters of the cushioning material are the theoretical and technical difficulties that urgently need to be solved in the realization of banana mechanical de-handing.The future research(research on the coupling mechanism of visual cognition-mechanism cutting and low-destructive catching method of full-field continuous de-handing of bananas under multi-constraint scenarios)should:(1)create a database of banana crown,obtain the optimal banana crown recognition model,develop a recognition and locating system of the cutting line of banana crown and obtain its spatial location information;(2)establish the discrete element mechanical model of banana crown and the interaction model between banana crown and the cutter,clarify the stress change and the force wave transmission characteristics of the cutting process,construct the multi-objective optimization equation of the cutting performance,obtain the best combination of cutting parameters,and ascertain the mechanisms of synergistic locating and continuous cutting of banana crown;(3)establish the contact mechanical model of banana fruit drop-bump,parse the bumping characteristics between banana fruit and cushioning material,construct mathematical equations to quantitatively assess damage results,and determine the detract catching method of banana fruit that matches the de-handing mode in multi-constraint scenarios.This study showed that the real-time identification and spatial positioning of fruit,the mechanical properties of crown and the optimization of cutting performance,the damage mechanism of fruit and its loss-reducing harvesting method are the three key breakthroughs in realizing the robotization of de-handing.The current bottleneck problems and future research directions of intelligent banana de-handing were pointed out in this paper,which can provide a theoretical basis for the optimal design of banana de-handing devices and provide technical support for promoting the practical application of intelligent de-handing equipment.
基金support from Natural Science Foundation of China(No.52475030)supported by the National Key R&D Project of China(2023YFF0713700,YL)+1 种基金the Young Talent fund of University Association for Science and Technology in Shaanxi,China(No.20230302)Xi'an Science and Technology Plan Project(No.24YXYJ0161).
文摘Magnetic soft robots are emerging as a promising technology in biomedical applications, offering precise, minimally invasive solutions for clinical procedures. Magnetic soft robots, often constructed by using magnetic particles embedded in flexible polymers, exhibit enhanced deformability and maneuverability, particularly at micro and nanoscale levels. This paper provides a comprehensive overview of the design, fabrication, and medical applications of these robots, focusing on the synthesis of magnetic materials, structural configurations, and actuation mechanisms. Structural designs are summarized, from simple one-dimensional forms to complex, multi-dimensional structures inspired by origami and kirigami principles. Additionally, magnetic actuation systems, including permanent magnets and electromagnetic coils, are examined for their respective roles in achieving the required precision or field strength for medical use. The potential applications in medicine are vast, ranging from targeted drug delivery and minimally invasive surgeries to disease diagnosis and treatment, with specific examples in tumor targeting, Alzheimer's therapy, and endodontics. The paper also addresses emerging applications in assisted reproduction and microbiota regulation. Despite challenges related to power supply, real-time tracking, and material safety, the review highlights the significant potential of magnetic soft robots to revolutionize healthcare practices.
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National Natural Science Foundation of China(32301712)Natural Science Foundation of Jiangsu Province(BK20230548,BK20250876)+2 种基金Project of Faculty of Agricultural Equipment of Jiangsu University(NGXB20240203)A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD-2023-87)Open Funding Project of the Key Laboratory of Modern Agricultural Equipment and Technology(Jiangsu University),Ministry of Education(MAET202101)。
文摘Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narrow passages,slow convergence,and high computational costs.To address these challenges,this paper proposes a novel hybrid global path planning algorithm integrating Gaussian sampling and quadtree optimization(RRT^(*)-GSQ).This methodology aims to enhance path planning by synergistically combining a Gaussian mixture sampling strategy to improve node generation in critical regions,an adaptive step-size and direction optimization mechanism for enhanced obstacle avoidance,a Quadtree-AABB collision detection framework to lower computational complexity,and a dynamic iteration control strategy for more efficient convergence.In obstacle-free and obstructed scenarios,compared with the conventional RRT^(*),the proposed algorithm reduced the number of node evaluations by 67.57%and 62.72%,and decreased the search time by 79.72%and 78.52%,respectively.In path tracking tests,the proposed algorithm achieved substantial reductions in RMSE of the final path compared to the conventional RRT^(*).Specifically,the lateral RMSE was reduced by 41.5%in obstacle-free environments and 59.3%in obstructed environments,while the longitudinal RMSE was reduced by 57.2%and 58.5%,respectively.Furthermore,the maximum absolute errors in both lateral and longitudinal directions were constrained within 0.75 m.Field validation experiments in an operational orchard confirmed the algorithm's practical effectiveness,showing reductions in the mean tracking error of 47.6%(obstacle-free)and 58.3%(with obstructed),alongside a 5.1%and 7.2%shortening of the path length compared to the baseline method.The proposed algorithm effectively enhances path planning efficiency and navigation accuracy for robots,presenting a superior solution for high-precision autonomous navigation of agricultural robots in orchard environments and holding significant value for engineering applications.
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.
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 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.
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 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 by the National Natural Science Foundation of China (Grant Nos.T2325027,12274448,T2350007,12404239,12174041,12325405,12090054,and T2221001)the National Key R&D Program of China (Grant No.2022YFF0503504)。
文摘The intrinsic pressure framework,which treats self-propelling force as an external force,provides a convenient and consistent description of mechanical equilibrium in active matter.However,direct experimental evidence is still lacking.To validate this framework,here we employ a programmable robotic platform,where a single light-controlled wheeled robot travels in an activity landscape.Our experiments quantitatively demonstrate that the intrinsic pressure difference across the activity interface is balanced by the emerged polarization force.This result unambiguously confirms the theoretical predictions,thus validating the intrinsic pressure framework and laying the experimental foundation for the intrinsic pressure-based mechanical description of dry active matter.
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Human life is invaluable,and timely efforts are crucial to rescue individuals trapped under debris following an earthquake.To identify opportunities for improving post-earthquake search and rescue(SAR)robotics,we get insights through four different sources:(i)A literature review of disaster robotics and victim psychology,(ii)A public survey on earthquake awareness and their view of rescue robots,(iii)Semi-structured interviews with first responders,and(iv)Responses from GenAI chatbots which were prompted to assume the role of expert rescuers.The triangulated analysis show that there are challenges in mobility,autonomy,communication,situational awareness,and human-robot collaboration.The public respondents showed high acceptance of robot-assisted rescue and prioritised survivor detection,sensing,and communication as essential functionalities of robots.The experts expressed limitations in current equipment,the need for improved victim localisation,and interest in XR-based training and robot-assisted debris handling.The GenAI chatbots highlighted structural risk assessment,multi-sensor fusion,and supervised autonomy.Therefore,this study identifies critical robot features,outlines multi-modal interaction requirements,and highlights gaps in current SAR practice.These findings offer robot design directions for developing effective,trustworthy SAR robots,which can be integrated to future response disaster-workflows.
基金co-supported by the National Key Research and Development Program of China(No.2024YFB4711201)National Natural Science Foundation of China(Nos.U22A20204,52305472)。
文摘Carbon Fiber Reinforced Polymer(CFRP)and aluminum stacked are widely used in aircraft assemble thanks to the high strength-to-weight ratio.Riveting is an important joining technique of stacked structure and requires drilling and countersinking.Robotic machining systems are gradually used in the machining of holes due to their high flexibility.However,weakly rigid stacked structure and low-stiffness industrial robot system bring about complex and diverse countersinking depth errors,which significantly affects the fatigue life of components.In this paper,the influence mechanism of ultrasonic energy on the accuracy of robotic countersinking of stacked structure is investigated.Firstly,a workpiece deformation model is established with the thinwalled plate deformation theory,defined as static error.Then,the vibration of the industrial robot is calculated from the acceleration with the frequency domain integration,defined as dynamic error.The suppression of ultrasonic energy on the two kinds of errors were elucidated,respectively.Base on this,a depth compensation model of robotic ultrasonic countersinking is established.Finally,the feasibility of the accuracy compensation is experimentally verified,and the countersinking depth error can be controlled within±0.09 mm.
基金the financial support of the National Natural Science Foundation of China(NO.52173028)。
文摘Since the first design of tactile sensors was proposed by Harmon in 1982,tactile sensors have evolved through four key phases:industrial applications(1980s,basic pressure detection),miniaturization via MEMS(1990s),flexible electronics(2010s,stretchable materials),and intelligent systems(2020s-present,AI-driven multimodal sensing).With the innovation of material,processing techniques,and multimodal fusion of stimuli,the application of tactile sensors has been continuously expanding to a diversity of areas,including but not limited to medical care,aerospace,sports and intelligent robots.Currently,researchers are dedicated to develop tactile sensors with emerging mechanisms and structures,pursuing high-sensitivity,high-resolution,and multimodal characteristics and further constructing tactile systems which imitate and approach the performance of human organs.However,challenges in the combination between the theoretical research and the practical applications are still significant.There is a lack of comprehensive understanding in the state of the art of such knowledge transferring from academic work to technical products.Scaled-up production of laboratory materials faces fatal challenges like high costs,small scale,and inconsistent quality.Ambient factors,such as temperature,humidity,and electromagnetic interference,also impair signal reliability.Moreover,tactile sensors must operate across a wide pressure range(0.1 k Pa to several or even dozens of MPa)to meet diverse application needs.Meanwhile,the existing algorithms,data models and sensing systems commonly reveal insufficient precision as well as undesired robustness in data processing,and there is a realistic gap between the designed and the demanded system response speed.In this review,oriented by the design requirements of intelligent tactile sensing systems,we summarize the common sensing mechanisms,inspired structures,key performance,and optimizing strategies,followed by a brief overview of the recent advances in the perspectives of system integration and algorithm implementation,and the possible roadmap of future development of tactile sensors,providing a forward-looking as well as critical discussions in the future industrial applications of flexible tactile sensors.
基金financially supported by the Natural Science Foundation of Jiangsu Province,China(No.BK 20221502)the National Natural Science Foundation of China(No.42477147)。
文摘In this research,a comparative analysis was conducted on the performance and efficiency of the dual-anchor soft robot(DASR)and the extension-contraction soft robot(ECSR).These robots were constructed by imitating the locomotion of razor clams.The penetration force for extension actuators and the anchorage force for expansion actuators in dry sand with distinct relative densities were tested by differentiating input air pressure and length-to-diameter ratios(λ).On the basis of the findings,a DASR and an ECSR were developed.DASR comprised two expansion actuators as the head and the tail segments at two ends,and one extension actuator as the middle segment.ECSR was composed of an extension actuator.A method based on the force equilibrium was introduced to ascertain and adjust the geometric parameters(length of each segment)of DASR.The burrowing-out performance and efficiency of DASR and ECSR in sands with distinct relative densities were explored.The results revealed that DASR exhibited high efficiency in dense sand in terms of lower time of burrowing-out,slip-to-advancement ratio,and cost of transport.ECSR might perform better in looser sand in terms of higher average burrowing-out velocity,higher advancement in each cycle,and lower energy consumption.However,it had larger slips than DASR.DASR could realize steady advancement and net displacement in each cycle and effectively decrease slips.These findings demonstrate the benefits and usability of the dual-anchor motion and offer new insights into the application of the dual-anchor mechanism in the burrowing of robots.
