A three-DOF (degree of freedom) planar robot completely restrained and positioned parallel pulled by four wires was studied. The wire driving properties were analyzed through experiments. The restrained three-DOF plan...A three-DOF (degree of freedom) planar robot completely restrained and positioned parallel pulled by four wires was studied. The wire driving properties were analyzed through experiments. The restrained three-DOF planar platform was established based on slippery course and bearing, and dSPACE real-time control system was used to perform the platform's motion control experiment on robot. Based on the kinematic equation and mechanical balance equation of moving platform, the stiffness of the robot system was analyzed and the calibration scheme of the system considering wire tension was put forward. Position servo control experiments were carried out, position servo tracking precision was analyzed, and real-time wire tension was detected. The results show that the moving error of the moving platform tracking is small (the maximum difference is about 3%), and the rotation error is large (the maximum difference is about 12%). The wire tension has wave properties (the wire tension fluctuation is about 10 N).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
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
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
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
The capability of whole-body proprioception,e.g.,pose estimation,is important for the control and interaction of continuum robots.However,existing pose estimation methods are often simplified through geometric assumpt...The capability of whole-body proprioception,e.g.,pose estimation,is important for the control and interaction of continuum robots.However,existing pose estimation methods are often simplified through geometric assumptions,primarily due to constraints such as computational and sensor deployment costs.We propose an explicit posture estimation method through a neural network,and implement it using an embedded camera for vision-based proprioception.We design a continuous location encoding neural network(LENN)by encoding continuous locational information.The LENN can capture deformation from changes in internal texture observed by an integrated camera,and output pose information—both position and orientation—for any point along the robot backbone,rather than only discrete points.Compared with interpolation-based estimation using a reduced model,our method reduces single-point estimation error by 33.6%.Furthermore,a systematic evaluation of hardware configurations demonstrates that our prototype achieves sub-millimetre accuracy in shape estimation(0.383 mm)while maintaining real-time inference speeds below 12 ms per frame.By combining a learning-based approach with a simple mechanical design,our method leverages internal visual information to estimate the whole-body pose,providing an effective solution for accurate shape estimation in continuum robots.展开更多
This paper presents an intelligent patrol and security robot integrating 2D LiDAR and RGB-D vision sensors to achieve semantic simultaneous localization and mapping(SLAM),real-time object recognition,and dynamic obsta...This paper presents an intelligent patrol and security robot integrating 2D LiDAR and RGB-D vision sensors to achieve semantic simultaneous localization and mapping(SLAM),real-time object recognition,and dynamic obstacle avoidance.The system employs the YOLOv7 deep-learning framework for semantic detection and SLAM for localization and mapping,fusing geometric and visual data to build a high-fidelity 2D semantic map.This map enables the robot to identify and project object information for improved situational awareness.Experimental results show that object recognition reached 95.4%mAP@0.5.Semantic completeness increased from 68.7%(single view)to 94.1%(multi-view)with an average position error of 3.1 cm.During navigation,the robot achieved 98.0%reliability,avoided moving obstacles in 90.0%of encounters,and replanned paths in 0.42 s on average.The integration of LiDAR-based SLAMwith deep-learning–driven semantic perception establishes a robust foundation for intelligent,adaptive,and safe robotic navigation in dynamic environments.展开更多
Protective hardware is essential for mitigating damage caused by unavoidable falls in humanoid robots.Despite notable progress in fall protection hardware,the theoretical foundation for modeling and the feasibility of...Protective hardware is essential for mitigating damage caused by unavoidable falls in humanoid robots.Despite notable progress in fall protection hardware,the theoretical foundation for modeling and the feasibility of conducting full-scale fall experiments on robots or their surrogates remain somewhat limited.This paper proposes a method for optimizing the thickness of Expandable Polyethylene(EPE),which is used as back protection for the Chubao humanoid robot,based on small-scale impact test data to predict full-scale behavior.The optimal thickness is defined as a balance between compact design and protective effectiveness.An equivalent impact model characterized by four parameters:contact area S,mass m,fall height h,and cushioning material thickness d is introduced to describe impact conditions.The relationship between the peak impact acceleration ap and material thickness d,which forms the core of the method and gives rise to the name AP-D,is analyzed through their plotted curves.After introducing three characteristic parameters and two correction fac-tors,the relationship among the aforementioned variables is derived.Subsequently,both the optimal thickness do and its corresponding peak impact acceleration aop are predicted via nonlinear and linear regression models.Finally,the accuracy and effectiveness of the theoretically derived optimal thickness are validated on both a dummy and the actual robot.With the cushioning material applied,the peak chest acceleration is reduced to 41.57g for the dummy and 32.08g for the robot.展开更多
Industrial robot dynamics lay the foundation for high-precision and high-speed control, and accurate identification of dynamic parameters is essential for precise dynamic calculations. The choice of friction models is...Industrial robot dynamics lay the foundation for high-precision and high-speed control, and accurate identification of dynamic parameters is essential for precise dynamic calculations. The choice of friction models is a critical component in the identification of industrial robot dynamics. Traditional static friction models struggle to capture the hysteresis effects caused by robot joint elasticity and clearances, leading to large torque prediction errors when the joint velocity crosses zero. Due to the presence of hysteresis effects, the joint velocity crosses zero in the forward direction, and the reverse direction will have different friction patterns. Although the hysteresis effects can be modeled as an ordinary differential equation(ODE), it is difficult to determine the ODE structure that achieves both generalization and accuracy to describe the hysteresis effects of the friction model. To address this issue, we propose the neural hysteresis friction(NHF), which uses neural ODE to model the hysteresis effects in a data-driven manner, thereby mitigating the current inadequacies in the study of dynamic friction characteristics. The experiments on a real 6-axis industrial robot demonstrate that our proposed method can accurately model the friction dynamics during directional switching and outperform other modeling methods. Velocity tracking control experiments show that NHF can effectively reduce tracking errors when the velocity crosses zero.展开更多
Objective:Open retroperitoneal lymph node dissection(RPLND)is the gold-standard surgical approach for the management of metastatic testicular cancer,but robotic RPLND is becoming increasingly popular.There is limited ...Objective:Open retroperitoneal lymph node dissection(RPLND)is the gold-standard surgical approach for the management of metastatic testicular cancer,but robotic RPLND is becoming increasingly popular.There is limited research directly comparing open and robotic RPLND.The objective of this systematic review is to identify all the literature with direct comparisons between the open and robotic techniques for RPLND and to compare the two techniques.The primary outcome was peri-operative outcomes,and the secondary outcomes included oncological outcomes and patient demographics.Methods:This systematic review was prospectively registered and was conducted in accordance with the PRISMA statement.The PubMed,Embase and MEDLINE databases were searched for relevant publication from January 2006 to August 2024.Results:Eight studies,totaling 3995 patients,are included in this systematic review,with 3521 patients who underwent open RPLND and 474 who underwent robotic RPLND.For open RPLND,the mean operative duration,blood loss and length of stay were 267.8 min,475 mL and 7.3 d,respectively.For robotic RPLND,the mean operative duration,blood loss and length of stay were 334.5 min,94.6 mL and 3.7 d,respectively.Teratoma was the most common RPLND specimen pathology from both open and robotic surgeries.For open RPLND,the specimens have 13–23 nodes(26–32 mm),whereas the robotic RPLND specimens have 13–28 nodes(18–20 mm).Conclusion:This systematic review suggests that the benefitsof robotic RPLND may be associated with reduced blood loss,shorter hospitalisation and an overall lower risk of minor and major complications while maintaining oncological safety.展开更多
Deep learning has become integral to robotics,particularly in tasks such as robotic grasping,where objects often exhibit diverse shapes,textures,and physical properties.In robotic grasping tasks,due to the diverse cha...Deep learning has become integral to robotics,particularly in tasks such as robotic grasping,where objects often exhibit diverse shapes,textures,and physical properties.In robotic grasping tasks,due to the diverse characteristics of the targets,frequent adjustments to the network architecture and parameters are required to avoid a decrease in model accuracy,which presents a significant challenge for non-experts.Neural Architecture Search(NAS)provides a compelling method through the automated generation of network architectures,enabling the discovery of models that achieve high accuracy through efficient search algorithms.Compared to manually designed networks,NAS methods can significantly reduce design costs,time expenditure,and improve model performance.However,such methods often involve complex topological connections,and these redundant structures can severely reduce computational efficiency.To overcome this challenge,this work puts forward a robotic grasp detection framework founded on NAS.The method automatically designs a lightweight network with high accuracy and low topological complexity,effectively adapting to the target object to generate the optimal grasp pose,thereby significantly improving the success rate of robotic grasping.Additionally,we use Class Activation Mapping(CAM)as an interpretability tool,which captures sensitive information during the perception process through visualized results.The searched model achieved competitive,and in some cases superior,performance on the Cornell and Jacquard public datasets,achieving accuracies of 98.3%and 96.8%,respectively,while sustaining a detection speed of 89 frames per second with only 0.41 million parameters.To further validate its effectiveness beyond benchmark evaluations,we conducted real-world grasping experiments on a UR5 robotic arm,where the model demonstrated reliable performance across diverse objects and high grasp success rates,thereby confirming its practical applicability in robotic manipulation tasks.展开更多
The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varyi...The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varying degrees of degradation and damage to the main cable,necessitating regular inspections to prevent catastrophic failures.Traditional manual inspection methods not only suffer from low efficiency but also pose significant safety risks to personnel.To address these challenges and ensure the safe and effective inspection of suspension bridge main cables,this study introduces a novel cooperative climbing robot,designated as Main Cable Robot Version II(CCRobot-M-II),inspired by the locomotion of the inchworm.The robot employs an alternating opening and closing mechanism of four gripper sets,mimicking the inchworm's movement to achieve efficient crawling along the suspension bridge handrails.This paper provides a comprehensive analysis of the structural design,key components,and motion mechanisms of CCRobot-M-II.A detailed force analysis of the robot's crawling process is also presented,followed by the design of the control system and the development of an efficient motion control algorithm.Laboratory experiments demonstrate that the robot achieves a positional error of 00.64%during crawling,with a maximum average crawling speed of 7.6 m/min.Furthermore,the biomimetic design enables the robot to overcome obstacles up to 30 mm in height and possess the capability to handle suspension bridge cables with spans ranging from 740 to 1100 mm.Finally,CCRobot-M-II successfully conducted an inspection of the main cable on a suspension bridge,marking the world's first successful deployment of a climbing robot for main cable inspection on a suspension bridge.展开更多
Robotic inguinal hernia repair remains in the early stages of implementation,and its potential advantages over the laparoscopic approach are still a matter of debate.This narrative review aims to summarize the finding...Robotic inguinal hernia repair remains in the early stages of implementation,and its potential advantages over the laparoscopic approach are still a matter of debate.This narrative review aims to summarize the findingsof major systematic reviews and randomized controlled trials and explore variables not adequately addressed in those studies.The literature review indicates that robotic inguinal hernia repair is associated with longer operative times but has improved ergonomics compared with laparoscopy.It is a safe procedure that results in a reduced inflammatory response,similar complication rates,and no significantdifference in acute postoperative pain.Although it involves higher direct costs,its cost-effectiveness remains unclear owing to a lack of analysis including indirect costs.Ongoing controversy continues regarding long-term benefits.The most recent systematic review pointed towards lower recurrence rates with robotic surgery,although randomized controlled trials have not validated this finding.Data on chronic pain are currently insufficientto draw firmconclusions.Further studies are needed to assess its use in complex cases and the role of novel techniques.展开更多
This study examines how foreign language education in the artificial intelligence(AI)era could assist the cultivation of national consciousness through a technology-enhanced pedagogy of film appreciation.Using The Wil...This study examines how foreign language education in the artificial intelligence(AI)era could assist the cultivation of national consciousness through a technology-enhanced pedagogy of film appreciation.Using The Wild Robot as a case study,we argue that cinematic narratives serve as cultural mirrors,offering immersive,reflective,and affective sites for intercultural learning.We propose a three-layered pedagogical framework-progressing from semiotic decoding,through narrative and value comparison,to creative identity construction-that integrates intelligent tools to develop both communicative competence and an agentive sense of belonging.The approach exemplifies a humanistic turn in language teaching,aiming to form“rooted global communicators”who can engage in cross-civilization dialogue with cultural confidence and critical awareness.展开更多
Accurate mechanical modeling is essential for robotic belt grinding(RBG), a process characterized by compliant contact mechanisms that make force prediction particularly challenging. However, existing mechanical model...Accurate mechanical modeling is essential for robotic belt grinding(RBG), a process characterized by compliant contact mechanisms that make force prediction particularly challenging. However, existing mechanical models predominantly focus on macroscale compliance while neglecting grain-scale compliant motion. Moreover, abrasive grains are typically idealized as regular shapes, overlooking the inherent stochasticity of real grain geometries. This study proposes a shapeequivalence method for modeling stochastic abrasive grains and develops a multiscale compliant force model for RBG. Specifically, an individual grain is represented as a polygonal pyramid with stochastic edges that is mathematically equivalent to a cone;this method unifies the treatment of grain geometries and streamlines the modeling process. The mathematical equivalence relationship for random grain shapes is further derived based on a grain-compliant contact model. By integrating grain geometric characteristics and progressive grain wear, an analytical mechanical model that captures both the static contact force and dynamic grinding force is established, thereby describing the transition from grain-workpiece compliant interaction to belt-workpiece elastic contact. Grinding experiments were conducted using abrasive belts with different grain shape distributions to validate the model. The results demonstrated reliable predictions of the tangential grinding force and its component characteristics. Additional analyses were performed to reveal how the tangential grinding force varies with wear time and grinding parameters.展开更多
Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined ...Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined with a bio-inspired double wing clap-and-fling mechanism,affect thrust generation.This study focused on increasing vertical force and payload capacity.Through systematic experimentation with various vein configurations and structural designs,we developed innovative wings optimized for thrust production.Comprehensive tests were conducted to measure aerodynamic forces,power consumption,and wing kinematics across a range of flapping frequencies.Additionally,wings with different aspect ratios,a key factor in wing design,were fabricated and extensively evaluated.The study also examined the role of bio-inspired vein layouts on wing flexibility,a critical component in improving flight efficiency.Our findings demonstrate that the newly developed wing design led to a 20%increase in thrust,achieving up to 30 g-force(gf).This research sheds light on the clap-and-fling effect and establishes a promising framework for bio-inspired wing design,offering significant improvements in both performance and payload capacity for FW robots.展开更多
基金Project(20102304120007) supported by the Research Fund for the Doctoral Program of Higher Education of ChinaProject(QC2010009)supported by the Natural Science Foundation of Heilongjiang Province, China+1 种基金Projects(20110491030, LBH-Z10219) supported by China Postdoctoral Science FoundationProject(HEUCF120706) supported by the Fundamental Research Funds for the Central Universities of China
文摘A three-DOF (degree of freedom) planar robot completely restrained and positioned parallel pulled by four wires was studied. The wire driving properties were analyzed through experiments. The restrained three-DOF planar platform was established based on slippery course and bearing, and dSPACE real-time control system was used to perform the platform's motion control experiment on robot. Based on the kinematic equation and mechanical balance equation of moving platform, the stiffness of the robot system was analyzed and the calibration scheme of the system considering wire tension was put forward. Position servo control experiments were carried out, position servo tracking precision was analyzed, and real-time wire tension was detected. The results show that the moving error of the moving platform tracking is small (the maximum difference is about 3%), and the rotation error is large (the maximum difference is about 12%). The wire tension has wave properties (the wire tension fluctuation is about 10 N).
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.
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.
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.
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.
基金supported by the National Natural Science Foundation of China(Grant Nos.52188102,52505008)the National Key Research and Development Program of China(Grant No.2024YFB4707902)。
文摘The capability of whole-body proprioception,e.g.,pose estimation,is important for the control and interaction of continuum robots.However,existing pose estimation methods are often simplified through geometric assumptions,primarily due to constraints such as computational and sensor deployment costs.We propose an explicit posture estimation method through a neural network,and implement it using an embedded camera for vision-based proprioception.We design a continuous location encoding neural network(LENN)by encoding continuous locational information.The LENN can capture deformation from changes in internal texture observed by an integrated camera,and output pose information—both position and orientation—for any point along the robot backbone,rather than only discrete points.Compared with interpolation-based estimation using a reduced model,our method reduces single-point estimation error by 33.6%.Furthermore,a systematic evaluation of hardware configurations demonstrates that our prototype achieves sub-millimetre accuracy in shape estimation(0.383 mm)while maintaining real-time inference speeds below 12 ms per frame.By combining a learning-based approach with a simple mechanical design,our method leverages internal visual information to estimate the whole-body pose,providing an effective solution for accurate shape estimation in continuum robots.
基金supported by the National Science and Technology Council of under Grant NSTC 114-2221-E-130-007.
文摘This paper presents an intelligent patrol and security robot integrating 2D LiDAR and RGB-D vision sensors to achieve semantic simultaneous localization and mapping(SLAM),real-time object recognition,and dynamic obstacle avoidance.The system employs the YOLOv7 deep-learning framework for semantic detection and SLAM for localization and mapping,fusing geometric and visual data to build a high-fidelity 2D semantic map.This map enables the robot to identify and project object information for improved situational awareness.Experimental results show that object recognition reached 95.4%mAP@0.5.Semantic completeness increased from 68.7%(single view)to 94.1%(multi-view)with an average position error of 3.1 cm.During navigation,the robot achieved 98.0%reliability,avoided moving obstacles in 90.0%of encounters,and replanned paths in 0.42 s on average.The integration of LiDAR-based SLAMwith deep-learning–driven semantic perception establishes a robust foundation for intelligent,adaptive,and safe robotic navigation in dynamic environments.
基金Natural Science Foundation of Beijing Municipality under Grant L243004the National Natural Science Foundation of China under Grant 62403060.
文摘Protective hardware is essential for mitigating damage caused by unavoidable falls in humanoid robots.Despite notable progress in fall protection hardware,the theoretical foundation for modeling and the feasibility of conducting full-scale fall experiments on robots or their surrogates remain somewhat limited.This paper proposes a method for optimizing the thickness of Expandable Polyethylene(EPE),which is used as back protection for the Chubao humanoid robot,based on small-scale impact test data to predict full-scale behavior.The optimal thickness is defined as a balance between compact design and protective effectiveness.An equivalent impact model characterized by four parameters:contact area S,mass m,fall height h,and cushioning material thickness d is introduced to describe impact conditions.The relationship between the peak impact acceleration ap and material thickness d,which forms the core of the method and gives rise to the name AP-D,is analyzed through their plotted curves.After introducing three characteristic parameters and two correction fac-tors,the relationship among the aforementioned variables is derived.Subsequently,both the optimal thickness do and its corresponding peak impact acceleration aop are predicted via nonlinear and linear regression models.Finally,the accuracy and effectiveness of the theoretically derived optimal thickness are validated on both a dummy and the actual robot.With the cushioning material applied,the peak chest acceleration is reduced to 41.57g for the dummy and 32.08g for the robot.
基金supported by the National Natural Science Foundation of China (Grant No.52188102)。
文摘Industrial robot dynamics lay the foundation for high-precision and high-speed control, and accurate identification of dynamic parameters is essential for precise dynamic calculations. The choice of friction models is a critical component in the identification of industrial robot dynamics. Traditional static friction models struggle to capture the hysteresis effects caused by robot joint elasticity and clearances, leading to large torque prediction errors when the joint velocity crosses zero. Due to the presence of hysteresis effects, the joint velocity crosses zero in the forward direction, and the reverse direction will have different friction patterns. Although the hysteresis effects can be modeled as an ordinary differential equation(ODE), it is difficult to determine the ODE structure that achieves both generalization and accuracy to describe the hysteresis effects of the friction model. To address this issue, we propose the neural hysteresis friction(NHF), which uses neural ODE to model the hysteresis effects in a data-driven manner, thereby mitigating the current inadequacies in the study of dynamic friction characteristics. The experiments on a real 6-axis industrial robot demonstrate that our proposed method can accurately model the friction dynamics during directional switching and outperform other modeling methods. Velocity tracking control experiments show that NHF can effectively reduce tracking errors when the velocity crosses zero.
文摘Objective:Open retroperitoneal lymph node dissection(RPLND)is the gold-standard surgical approach for the management of metastatic testicular cancer,but robotic RPLND is becoming increasingly popular.There is limited research directly comparing open and robotic RPLND.The objective of this systematic review is to identify all the literature with direct comparisons between the open and robotic techniques for RPLND and to compare the two techniques.The primary outcome was peri-operative outcomes,and the secondary outcomes included oncological outcomes and patient demographics.Methods:This systematic review was prospectively registered and was conducted in accordance with the PRISMA statement.The PubMed,Embase and MEDLINE databases were searched for relevant publication from January 2006 to August 2024.Results:Eight studies,totaling 3995 patients,are included in this systematic review,with 3521 patients who underwent open RPLND and 474 who underwent robotic RPLND.For open RPLND,the mean operative duration,blood loss and length of stay were 267.8 min,475 mL and 7.3 d,respectively.For robotic RPLND,the mean operative duration,blood loss and length of stay were 334.5 min,94.6 mL and 3.7 d,respectively.Teratoma was the most common RPLND specimen pathology from both open and robotic surgeries.For open RPLND,the specimens have 13–23 nodes(26–32 mm),whereas the robotic RPLND specimens have 13–28 nodes(18–20 mm).Conclusion:This systematic review suggests that the benefitsof robotic RPLND may be associated with reduced blood loss,shorter hospitalisation and an overall lower risk of minor and major complications while maintaining oncological safety.
基金funded by Guangdong Basic and Applied Basic Research Foundation(2023B1515120064)National Natural Science Foundation of China(62273097).
文摘Deep learning has become integral to robotics,particularly in tasks such as robotic grasping,where objects often exhibit diverse shapes,textures,and physical properties.In robotic grasping tasks,due to the diverse characteristics of the targets,frequent adjustments to the network architecture and parameters are required to avoid a decrease in model accuracy,which presents a significant challenge for non-experts.Neural Architecture Search(NAS)provides a compelling method through the automated generation of network architectures,enabling the discovery of models that achieve high accuracy through efficient search algorithms.Compared to manually designed networks,NAS methods can significantly reduce design costs,time expenditure,and improve model performance.However,such methods often involve complex topological connections,and these redundant structures can severely reduce computational efficiency.To overcome this challenge,this work puts forward a robotic grasp detection framework founded on NAS.The method automatically designs a lightweight network with high accuracy and low topological complexity,effectively adapting to the target object to generate the optimal grasp pose,thereby significantly improving the success rate of robotic grasping.Additionally,we use Class Activation Mapping(CAM)as an interpretability tool,which captures sensitive information during the perception process through visualized results.The searched model achieved competitive,and in some cases superior,performance on the Cornell and Jacquard public datasets,achieving accuracies of 98.3%and 96.8%,respectively,while sustaining a detection speed of 89 frames per second with only 0.41 million parameters.To further validate its effectiveness beyond benchmark evaluations,we conducted real-world grasping experiments on a UR5 robotic arm,where the model demonstrated reliable performance across diverse objects and high grasp success rates,thereby confirming its practical applicability in robotic manipulation tasks.
基金Shenzhen Science and Technology Program(Grant No.20220817171811004)(Grant No.RCBS20231211090816033)+4 种基金the Major Key Project of PCL,China under Grant PCL2025A13Longgang District,Shenzhen's"Ten-Action Plan"for Supporting Innovation Projects(Grant No.LGKCSDPT2024002,LGKCSDPT2024003,LGKCSDPT2024004)the"Zhiguo"Action of Guangxi Science and Technology Program(Grant No.ZG2503980003)Guangdong S&T Program under(Grant No.2025B0909040003)Guangdong Provincial Leading Talent Program(Grant No.2024TX08Z319).
文摘The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varying degrees of degradation and damage to the main cable,necessitating regular inspections to prevent catastrophic failures.Traditional manual inspection methods not only suffer from low efficiency but also pose significant safety risks to personnel.To address these challenges and ensure the safe and effective inspection of suspension bridge main cables,this study introduces a novel cooperative climbing robot,designated as Main Cable Robot Version II(CCRobot-M-II),inspired by the locomotion of the inchworm.The robot employs an alternating opening and closing mechanism of four gripper sets,mimicking the inchworm's movement to achieve efficient crawling along the suspension bridge handrails.This paper provides a comprehensive analysis of the structural design,key components,and motion mechanisms of CCRobot-M-II.A detailed force analysis of the robot's crawling process is also presented,followed by the design of the control system and the development of an efficient motion control algorithm.Laboratory experiments demonstrate that the robot achieves a positional error of 00.64%during crawling,with a maximum average crawling speed of 7.6 m/min.Furthermore,the biomimetic design enables the robot to overcome obstacles up to 30 mm in height and possess the capability to handle suspension bridge cables with spans ranging from 740 to 1100 mm.Finally,CCRobot-M-II successfully conducted an inspection of the main cable on a suspension bridge,marking the world's first successful deployment of a climbing robot for main cable inspection on a suspension bridge.
文摘Robotic inguinal hernia repair remains in the early stages of implementation,and its potential advantages over the laparoscopic approach are still a matter of debate.This narrative review aims to summarize the findingsof major systematic reviews and randomized controlled trials and explore variables not adequately addressed in those studies.The literature review indicates that robotic inguinal hernia repair is associated with longer operative times but has improved ergonomics compared with laparoscopy.It is a safe procedure that results in a reduced inflammatory response,similar complication rates,and no significantdifference in acute postoperative pain.Although it involves higher direct costs,its cost-effectiveness remains unclear owing to a lack of analysis including indirect costs.Ongoing controversy continues regarding long-term benefits.The most recent systematic review pointed towards lower recurrence rates with robotic surgery,although randomized controlled trials have not validated this finding.Data on chronic pain are currently insufficientto draw firmconclusions.Further studies are needed to assess its use in complex cases and the role of novel techniques.
基金supported by the project:Hunan Provincial Educational Science Research Project“Research on Cultivating National Consciousness in College Foreign Language Courses(XJT23CGD001)”.
文摘This study examines how foreign language education in the artificial intelligence(AI)era could assist the cultivation of national consciousness through a technology-enhanced pedagogy of film appreciation.Using The Wild Robot as a case study,we argue that cinematic narratives serve as cultural mirrors,offering immersive,reflective,and affective sites for intercultural learning.We propose a three-layered pedagogical framework-progressing from semiotic decoding,through narrative and value comparison,to creative identity construction-that integrates intelligent tools to develop both communicative competence and an agentive sense of belonging.The approach exemplifies a humanistic turn in language teaching,aiming to form“rooted global communicators”who can engage in cross-civilization dialogue with cultural confidence and critical awareness.
基金supported by the National Natural Science Foundation of China (Grant Nos.52505554,52575571)the Postdoctoral Fellowship Program of CPSF (Grant No.GZB20250348)。
文摘Accurate mechanical modeling is essential for robotic belt grinding(RBG), a process characterized by compliant contact mechanisms that make force prediction particularly challenging. However, existing mechanical models predominantly focus on macroscale compliance while neglecting grain-scale compliant motion. Moreover, abrasive grains are typically idealized as regular shapes, overlooking the inherent stochasticity of real grain geometries. This study proposes a shapeequivalence method for modeling stochastic abrasive grains and develops a multiscale compliant force model for RBG. Specifically, an individual grain is represented as a polygonal pyramid with stochastic edges that is mathematically equivalent to a cone;this method unifies the treatment of grain geometries and streamlines the modeling process. The mathematical equivalence relationship for random grain shapes is further derived based on a grain-compliant contact model. By integrating grain geometric characteristics and progressive grain wear, an analytical mechanical model that captures both the static contact force and dynamic grinding force is established, thereby describing the transition from grain-workpiece compliant interaction to belt-workpiece elastic contact. Grinding experiments were conducted using abrasive belts with different grain shape distributions to validate the model. The results demonstrated reliable predictions of the tangential grinding force and its component characteristics. Additional analyses were performed to reveal how the tangential grinding force varies with wear time and grinding parameters.
基金Nguyen Tat Thanh University,Ho Chi Minh City,Vietnam for supporting this study。
文摘Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined with a bio-inspired double wing clap-and-fling mechanism,affect thrust generation.This study focused on increasing vertical force and payload capacity.Through systematic experimentation with various vein configurations and structural designs,we developed innovative wings optimized for thrust production.Comprehensive tests were conducted to measure aerodynamic forces,power consumption,and wing kinematics across a range of flapping frequencies.Additionally,wings with different aspect ratios,a key factor in wing design,were fabricated and extensively evaluated.The study also examined the role of bio-inspired vein layouts on wing flexibility,a critical component in improving flight efficiency.Our findings demonstrate that the newly developed wing design led to a 20%increase in thrust,achieving up to 30 g-force(gf).This research sheds light on the clap-and-fling effect and establishes a promising framework for bio-inspired wing design,offering significant improvements in both performance and payload capacity for FW robots.
