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
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
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
Human object detection and recognition is essential for elderly monitoring and assisted living however,models relying solely on pose or scene context often struggle in cluttered or visually ambiguous settings.To addre...Human object detection and recognition is essential for elderly monitoring and assisted living however,models relying solely on pose or scene context often struggle in cluttered or visually ambiguous settings.To address this,we present SCENET-3D,a transformer-drivenmultimodal framework that unifies human-centric skeleton features with scene-object semantics for intelligent robotic vision through a three-stage pipeline.In the first stage,scene analysis,rich geometric and texture descriptors are extracted from RGB frames,including surface-normal histograms,angles between neighboring normals,Zernike moments,directional standard deviation,and Gabor-filter responses.In the second stage,scene-object analysis,non-human objects are segmented and represented using local feature descriptors and complementary surface-normal information.In the third stage,human-pose estimation,silhouettes are processed through an enhanced MoveNet to obtain 2D anatomical keypoints,which are fused with depth information and converted into RGB-based point clouds to construct pseudo-3D skeletons.Features from all three stages are fused and fed in a transformer encoder with multi-head attention to resolve visually similar activities.Experiments on UCLA(95.8%),ETRI-Activity3D(89.4%),andCAD-120(91.2%)demonstrate that combining pseudo-3D skeletonswith rich scene-object fusion significantly improves generalizable activity recognition,enabling safer elderly care,natural human–robot interaction,and robust context-aware robotic perception in real-world environments.展开更多
This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The partici...This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The participants were a 17-year-old young lady with ASD and intellectual deficit, and a control participant: a preadolescent with ASD but no intellectual deficit (Asperger syndrome). The game is comprised of four phases: greetings, pairing, imitation, and closing. Field educators were involved, playing specific roles: visual or physical inciter. The use of a robot allows for catching the participants’ attention, playing the imitation game for a longer period of time than with a human partner, and preventing the game partner’s negative facial expressions resulting from tiredness, impatience, or boredom. The participants’ behavior was observed in terms of initial approach towards the robot, positioning relative to the robot in terms of distance and orientation, reactions to the robot’s voice or moves, signs of happiness, and imitation attempts. Results suggest a more and more natural approach towards the robot during the sessions, as well as a higher level of social interaction, based on the variations of the parameters listed above. We use these preliminary results to draw the next steps of our research work as well as identify further perspectives, with this aim in mind: improving social interactions with adolescents with ASD and intellectual deficit, allowing for better integration of these people into our societies.展开更多
The 2025 World Robot Conference,held in Beijing from August 8 to 12,offered a vivid glimpse into the future of the global robotics industry,where breakthroughs in artificial intelligence(AI)are injecting new momentum ...The 2025 World Robot Conference,held in Beijing from August 8 to 12,offered a vivid glimpse into the future of the global robotics industry,where breakthroughs in artificial intelligence(AI)are injecting new momentum into growth.Drawing ove r 1.3 million attendees.展开更多
Since the idea of embodied artificial intelligence was born,the U.S.has been an international frontrunner in the research and development(R&D)and application of the technology,while China has been a capable chaser...Since the idea of embodied artificial intelligence was born,the U.S.has been an international frontrunner in the research and development(R&D)and application of the technology,while China has been a capable chaser in recent years,particularly in the area of humanoid robots.展开更多
Human-robot safety is an important topic in wearable robotics,especially in supernumerary robotic limbs(SRLs).The proposal of flexible joint improves human-robot safety strategy,which allows physical contact between h...Human-robot safety is an important topic in wearable robotics,especially in supernumerary robotic limbs(SRLs).The proposal of flexible joint improves human-robot safety strategy,which allows physical contact between human and robots,rather than strictly limiting the human-robot motion.However,most researchers focus on the variable stiffness features of flexible joints,but few evaluate the performance of the flexible joint in the human-robot collision.Therefore,the performance of two typical flexible joints,including the series elastic joint(SEJ)and the passive variable stiffness joint(PVSJ),are compared through dynamic collision experiments.The results demonstrate that the SEJ absorbs 40.7%-58.7%of the collision force and 34.2%-45.2%of the collision torque in the driven-torque below 4 N·m and driven-speed of 3-7(°)/s,which is more stable than PVSJ.In addition,the stiffness error of SEJ is measured at 5.1%,significantly lower than the 23.04%measured in the PVSJ.The huge stiffness error of PVSJ leads to its unreliability in buffering collision.Furthermore,we analyze results and confirm that SEJ has a more stable human-robot safety performance in buffering dynamic collision.Consequently,the SEJ is suitable in SRLs for human-robot safety in our scenario.展开更多
Robots are increasingly expected to replace humans in many repetitive and high-precision tasks,of which surface scanning is a typical example.However,it is usually difficult for a robot to independently deal with a su...Robots are increasingly expected to replace humans in many repetitive and high-precision tasks,of which surface scanning is a typical example.However,it is usually difficult for a robot to independently deal with a surface scanning task with uncertainties in,for example the irregular surface shapes and surface properties.Moreover,it usually requires surface modelling with additional sensors,which might be time-consuming and costly.A human-robot collaboration-based approach that allows a human user and a robot to assist each other in scanning uncertain surfaces with uniform properties,such as scanning human skin in ultrasound examination is proposed.In this approach,teleoperation is used to obtain the operator's intent while allowing the operator to operate remotely.After external force perception and friction estimation,the orientation of the robot endeffector can be autonomously adjusted to keep as perpendicular to the surface as possible.Force control enables the robotic manipulator to maintain a constant contact force with the surface.And hybrid force/motion control ensures that force,position,and pose can be regulated without interfering with each other while reducing the operator's workload.The proposed method is validated using the Elite robot to perform a mock Bultrasound scanning experiment.展开更多
The textile industry,with its centuries-old heritage,is undergoing an unprecedented transformation-one where robots are stealing the spotlight.In factory floors that once hummed with the bustling activity of skilled w...The textile industry,with its centuries-old heritage,is undergoing an unprecedented transformation-one where robots are stealing the spotlight.In factory floors that once hummed with the bustling activity of skilled workers,automated systems are now the rising stars,quietly revolutionizing every aspect of production.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
Jumping robots are highly capable of overcoming obstacles.However,their explosive force,short duration,and variable trajectories pose significant challenges in achieving stable landings in complex environments.Traditi...Jumping robots are highly capable of overcoming obstacles.However,their explosive force,short duration,and variable trajectories pose significant challenges in achieving stable landings in complex environments.Traditional approaches rely heavily on sophisticated algorithms and electronic sensor feedback systems to ensure landing stability,which increases the implementation complexity.Inspired by the process by which humans complete jumps and achieve stable landings in complex environments,this study proposes a novel landing control method for jumping robots.By designing a mechanically coupled perception-control structure based on mechanical logic computing,the robot simulates the real-time transmission of neural signals triggered by the ground reaction force(GRF)in human reflex loops,thereby simplifying traditional control approaches.Through the collaboration of a flexible mechanical spine and a bistable foot module,the robot achieves an average height of 16.8 cm and a distance of 25.36 cm in consecutive stable jumps.It also demonstrates reliable landing performance on challenging terrain including slopes and cobblestone surfaces.This paper proposes a novel landing control method for jumping robots that simplifies traditional control approaches.The method enables stable landings on complex terrain through a mechanically coupled perception-control structure.This approach has potential applications in tasks requiring mobility over uneven terrain,such as search and rescue.展开更多
The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper pre...The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper presents an adaptive disturbance rejection balance controller based on a Variable-inertia Centroidal Model Predictive Control(ViC-MPC)approach,designed to address both minor disturbances that affect standing balance and major disturbances requiring stepping adjustments.The controller also facilitates reliable balance recovery after stepping adjustments.The humanoid robot is modeled as a spatial variable-inertia ellipsoid,representing the distribution of centroidal dynamics,with the contact wrenches optimized in real-time through a customized MPC formulation.Inspired by capturability-based constraints,we propose an adaptive dynamic stability transition strategy.This strategy is activated based on the Retrospective Horizon Average Centroidal Velocity(RHACV)and the Capture Point(CP),ensuring effective stepping adjustments and disturbance rejection.With the torque-controlled humanoid robot BHR8P,extensive simulation and experimental results demonstrate the effectiveness of the proposed method,highlighting its capability to adapt to and recover from various disturbances with improved stability.展开更多
Existing control methods for humanoid robots,such as Model Predictive Control(MPC)and Reinforcement Learning(RL),generally lack the modeling and exploitation of rhythmic mechanisms.As a result,they struggle to balance...Existing control methods for humanoid robots,such as Model Predictive Control(MPC)and Reinforcement Learning(RL),generally lack the modeling and exploitation of rhythmic mechanisms.As a result,they struggle to balance stability,energy efficiency,and gait transition capability during typical rhythmic motions like walking and running.To address this limitation,we propose Walk2Run,a unified control framework inspired by biological rhythmicity.The method introduces control priors based on the frequency modulation observed in human walk-run transitions.Specifically,we extract rhythmic parameters from motion capture data to construct a Rhythm Generator grounded in Central Pattern Generator(CPG)principles,which guides the policy to produce speed-adaptive periodic motion.This rhythmic guidance is further integrated with a constrained reinforcement learning framework using barrier function optimization,enhancing training stability and output feasibility.Experimental results demonstrate that our method outperforms traditional approaches across multiple metrics,achieving more natural rhythmic motion with improved energy efficiency in medium-to high-speed scenarios,while also enhancing gait stability and adaptability to the robotic platform.展开更多
Humanoid robots exhibit structures and movements akin to those of humans,enabling them to assist or substitute for humans in various operations without necessitating alterations to their typical environment and tools....Humanoid robots exhibit structures and movements akin to those of humans,enabling them to assist or substitute for humans in various operations without necessitating alterations to their typical environment and tools.Sustaining bal-ance amidst disturbances constitutes a fundamental capability for humanoid robots.Consequently,adopting efficacious strategies to manage instability and mitigate injuries resulting from falls assumes paramount importance in advancing the widespread adoption of humanoid robotics.This paper presents a comprehensive overview of the ongoing development of strategies for coping with falls in humanoid robots.It systematically reviews and discusses three critical facets:fall state detection,preventive actions against falls,and post-fall protection measures.The paper undertakes a thorough classifica-tion of existing coping methodologies across different stages of falls,analyzes the merits and drawbacks of each approach,and outlines the evolving trajectory of solutions for addressing fall-related challenges across distinct stages.Finally,the paper provides a succinct summary and future prospects for the current fall coping strategies tailored for humanoid robots.展开更多
This paper proposes the Leg Dimensional Synergistic Optimization Strategy(LDSOS)for humanoid robotic legs based on mechanism decoupling and performance assignment.The proposed method addresses the interdependent effec...This paper proposes the Leg Dimensional Synergistic Optimization Strategy(LDSOS)for humanoid robotic legs based on mechanism decoupling and performance assignment.The proposed method addresses the interdependent effects of dimensional parameters on the local and whole mechanisms in the design of hybrid humanoid robotic legs.It sequentially optimizes the dimensional parameters of the local and whole mechanism,thereby balancing the motion performance requirements of both.Additionally,it considers the assignment of efficient performance resources between the Local Functional Workspace(LFW)and the Whole Available Workspace(WAW).To facilitate the modeling and optimization process,a local/whole Equivalent Configuration Framework(ECF)is introduced.By decoupling the hybrid mechanism into a whole mechanism and multiple local mechanisms,the ECF enhances the efficiency of design,modeling,and performance evaluation.Prototype experiments are conducted to validate the effectiveness of LDSOS.This research provides an effective configuration framework for humanoid robotic leg design,establishing a theoretical and practical foundation for future optimized designs of humanoid robotic legs and pioneering novel approaches to the design of complex hybrid humanoid robotic legs.展开更多
Activation of neutrophil membrane receptors initiates intracellular signal transduction cascades that orchestrate the cell's effector functions,including phagocytosis,production of reactive oxygen and halogen spec...Activation of neutrophil membrane receptors initiates intracellular signal transduction cascades that orchestrate the cell's effector functions,including phagocytosis,production of reactive oxygen and halogen species,degranulation,and NETosis(formation of neutrophil extracellular traps[NETs]).NETs,which contain antimicrobial compounds such as myeloperoxidase(MPO),represent a strategy to combat infection.However,excessive production of NETs promotes thrombosis,diabetes mellitus,and other diseases.Therefore,investigations into the mechanisms of NETosis and the identification of modulators of this process are critical for developing strategies to address NETosis-related disorders.Here,we identified a novel NETosis inducer,human serum albumin(HSA)modified by the MPO product hypochlorous acid(HSAHOCl),whose accumulation in vivo was correlated with inflammatory processes.Using human blood neutrophils,we investigated HSAHOCl-induced NETosis and detected NET formation by flow cytometry.The results showed that the mechanism of HSAHOClinduced NETosis involved MPO,NADPH oxidase,and phosphatidylinositol 3-kinases(PI3Ks),and that HSAHOCl activated a reactive oxygen species-dependent suicidal type of NETosis.Moreover,HSAHOCl-induced NETosis was inhibited by an anti-HSAHOCl monoclonal antibody.Thus,our findings may facilitate the development of strategies to modulate NETosis in inflammation associated with elevated MPO activity.展开更多
Passive bionic feet,known for their human-like compliance,have garnered attention for their potential to achieve notable environmental adaptability.In this paper,a method was proposed to unifying passive bionic feet s...Passive bionic feet,known for their human-like compliance,have garnered attention for their potential to achieve notable environmental adaptability.In this paper,a method was proposed to unifying passive bionic feet static supporting stability and dynamic terrain adaptability through the utilization of the Rigid-Elastic Hybrid(REH)dynamics model.First,a bionic foot model,named the Hinge Tension Elastic Complex(HTEC)model,was developed by extracting key features from human feet.Furthermore,the kinematics and REH dynamics of the HTEC model were established.Based on the foot dynamics,a nonlinear optimization method for stiffness matching(NOSM)was designed.Finally,the HTEC-based foot was constructed and applied onto BHR-B2 humanoid robot.The foot static stability is achieved.The enhanced adaptability is observed as the robot traverses square steel,lawn,and cobblestone terrains.Through proposed design method and structure,the mobility of the humanoid robot is improved.展开更多
Food Science and Human Wellness (FSHW ISSN:2213-4530, CN 10-1750/TS) publishes original research papers demonstrating the latest advancement of multidisciplinary subjects related to food science and human health.Topic...Food Science and Human Wellness (FSHW ISSN:2213-4530, CN 10-1750/TS) publishes original research papers demonstrating the latest advancement of multidisciplinary subjects related to food science and human health.Topics may include but not limited to: nutriology, biochemistry, microbiology, immunology and toxicology.展开更多
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.
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funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Human object detection and recognition is essential for elderly monitoring and assisted living however,models relying solely on pose or scene context often struggle in cluttered or visually ambiguous settings.To address this,we present SCENET-3D,a transformer-drivenmultimodal framework that unifies human-centric skeleton features with scene-object semantics for intelligent robotic vision through a three-stage pipeline.In the first stage,scene analysis,rich geometric and texture descriptors are extracted from RGB frames,including surface-normal histograms,angles between neighboring normals,Zernike moments,directional standard deviation,and Gabor-filter responses.In the second stage,scene-object analysis,non-human objects are segmented and represented using local feature descriptors and complementary surface-normal information.In the third stage,human-pose estimation,silhouettes are processed through an enhanced MoveNet to obtain 2D anatomical keypoints,which are fused with depth information and converted into RGB-based point clouds to construct pseudo-3D skeletons.Features from all three stages are fused and fed in a transformer encoder with multi-head attention to resolve visually similar activities.Experiments on UCLA(95.8%),ETRI-Activity3D(89.4%),andCAD-120(91.2%)demonstrate that combining pseudo-3D skeletonswith rich scene-object fusion significantly improves generalizable activity recognition,enabling safer elderly care,natural human–robot interaction,and robust context-aware robotic perception in real-world environments.
文摘This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The participants were a 17-year-old young lady with ASD and intellectual deficit, and a control participant: a preadolescent with ASD but no intellectual deficit (Asperger syndrome). The game is comprised of four phases: greetings, pairing, imitation, and closing. Field educators were involved, playing specific roles: visual or physical inciter. The use of a robot allows for catching the participants’ attention, playing the imitation game for a longer period of time than with a human partner, and preventing the game partner’s negative facial expressions resulting from tiredness, impatience, or boredom. The participants’ behavior was observed in terms of initial approach towards the robot, positioning relative to the robot in terms of distance and orientation, reactions to the robot’s voice or moves, signs of happiness, and imitation attempts. Results suggest a more and more natural approach towards the robot during the sessions, as well as a higher level of social interaction, based on the variations of the parameters listed above. We use these preliminary results to draw the next steps of our research work as well as identify further perspectives, with this aim in mind: improving social interactions with adolescents with ASD and intellectual deficit, allowing for better integration of these people into our societies.
文摘The 2025 World Robot Conference,held in Beijing from August 8 to 12,offered a vivid glimpse into the future of the global robotics industry,where breakthroughs in artificial intelligence(AI)are injecting new momentum into growth.Drawing ove r 1.3 million attendees.
文摘Since the idea of embodied artificial intelligence was born,the U.S.has been an international frontrunner in the research and development(R&D)and application of the technology,while China has been a capable chaser in recent years,particularly in the area of humanoid robots.
基金supported by the Na⁃tional Natural Science Foundation of China(No.U22A20204)the Innovation Foundation from National Clinical Research Center for Orthopedics,Sports Medicine&Rehabilitation Foundation(No.23-NCRC-CXJJ-ZD3-8)。
文摘Human-robot safety is an important topic in wearable robotics,especially in supernumerary robotic limbs(SRLs).The proposal of flexible joint improves human-robot safety strategy,which allows physical contact between human and robots,rather than strictly limiting the human-robot motion.However,most researchers focus on the variable stiffness features of flexible joints,but few evaluate the performance of the flexible joint in the human-robot collision.Therefore,the performance of two typical flexible joints,including the series elastic joint(SEJ)and the passive variable stiffness joint(PVSJ),are compared through dynamic collision experiments.The results demonstrate that the SEJ absorbs 40.7%-58.7%of the collision force and 34.2%-45.2%of the collision torque in the driven-torque below 4 N·m and driven-speed of 3-7(°)/s,which is more stable than PVSJ.In addition,the stiffness error of SEJ is measured at 5.1%,significantly lower than the 23.04%measured in the PVSJ.The huge stiffness error of PVSJ leads to its unreliability in buffering collision.Furthermore,we analyze results and confirm that SEJ has a more stable human-robot safety performance in buffering dynamic collision.Consequently,the SEJ is suitable in SRLs for human-robot safety in our scenario.
基金Engineering and Physical Sciences Research Council(EPSRC),Grant/Award Number:EP/S001913。
文摘Robots are increasingly expected to replace humans in many repetitive and high-precision tasks,of which surface scanning is a typical example.However,it is usually difficult for a robot to independently deal with a surface scanning task with uncertainties in,for example the irregular surface shapes and surface properties.Moreover,it usually requires surface modelling with additional sensors,which might be time-consuming and costly.A human-robot collaboration-based approach that allows a human user and a robot to assist each other in scanning uncertain surfaces with uniform properties,such as scanning human skin in ultrasound examination is proposed.In this approach,teleoperation is used to obtain the operator's intent while allowing the operator to operate remotely.After external force perception and friction estimation,the orientation of the robot endeffector can be autonomously adjusted to keep as perpendicular to the surface as possible.Force control enables the robotic manipulator to maintain a constant contact force with the surface.And hybrid force/motion control ensures that force,position,and pose can be regulated without interfering with each other while reducing the operator's workload.The proposed method is validated using the Elite robot to perform a mock Bultrasound scanning experiment.
文摘The textile industry,with its centuries-old heritage,is undergoing an unprecedented transformation-one where robots are stealing the spotlight.In factory floors that once hummed with the bustling activity of skilled workers,automated systems are now the rising stars,quietly revolutionizing every aspect of production.
文摘Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challenge due to factors such as light scattering,absorption,restricted visibility,and ambient noise.The advancement of deep learning has introduced powerful techniques for processing large amounts of unstructured and imperfect data collected from underwater environments.This study evaluated the efficacy of the You Only Look Once(YOLO)algorithm,a real-time object detection and localization model based on convolutional neural networks,in identifying and classifying various types of pipeline defects in underwater settings.YOLOv8,the latest evolution in the YOLO family,integrates advanced capabilities,such as anchor-free detection,a cross-stage partial network backbone for efficient feature extraction,and a feature pyramid network+path aggregation network neck for robust multi-scale object detection,which make it particularly well-suited for complex underwater environments.Due to the lack of suitable open-access datasets for underwater pipeline defects,a custom dataset was captured using a remotely operated vehicle in a controlled environment.This application has the following assets available for use.Extensive experimentation demonstrated that YOLOv8 X-Large consistently outperformed other models in terms of pipe defect detection and classification and achieved a strong balance between precision and recall in identifying pipeline cracks,rust,corners,defective welds,flanges,tapes,and holes.This research establishes the baseline performance of YOLOv8 for underwater defect detection and showcases its potential to enhance the reliability and efficiency of pipeline inspection tasks in challenging underwater environments.
基金Supported by New Chongqing Innovative Young Talent Project(Grant No.2024NSCQ-qncxX0468)Natural Science Foundation of Chongqing(Grant No.CSTB2022NSCQ-MSX1283)Dreams Foundation of Jianghuai Advanced Technology Center(Grant No.2023-ZM01Z007).
文摘Jumping robots are highly capable of overcoming obstacles.However,their explosive force,short duration,and variable trajectories pose significant challenges in achieving stable landings in complex environments.Traditional approaches rely heavily on sophisticated algorithms and electronic sensor feedback systems to ensure landing stability,which increases the implementation complexity.Inspired by the process by which humans complete jumps and achieve stable landings in complex environments,this study proposes a novel landing control method for jumping robots.By designing a mechanically coupled perception-control structure based on mechanical logic computing,the robot simulates the real-time transmission of neural signals triggered by the ground reaction force(GRF)in human reflex loops,thereby simplifying traditional control approaches.Through the collaboration of a flexible mechanical spine and a bistable foot module,the robot achieves an average height of 16.8 cm and a distance of 25.36 cm in consecutive stable jumps.It also demonstrates reliable landing performance on challenging terrain including slopes and cobblestone surfaces.This paper proposes a novel landing control method for jumping robots that simplifies traditional control approaches.The method enables stable landings on complex terrain through a mechanically coupled perception-control structure.This approach has potential applications in tasks requiring mobility over uneven terrain,such as search and rescue.
基金supported in part by the National Natural Science Foundation of China under Grant 52575004the Beijing Natural Science Foundation under Grant L243004the National Natural Science Foundation of China under Grant 62403060.
文摘The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper presents an adaptive disturbance rejection balance controller based on a Variable-inertia Centroidal Model Predictive Control(ViC-MPC)approach,designed to address both minor disturbances that affect standing balance and major disturbances requiring stepping adjustments.The controller also facilitates reliable balance recovery after stepping adjustments.The humanoid robot is modeled as a spatial variable-inertia ellipsoid,representing the distribution of centroidal dynamics,with the contact wrenches optimized in real-time through a customized MPC formulation.Inspired by capturability-based constraints,we propose an adaptive dynamic stability transition strategy.This strategy is activated based on the Retrospective Horizon Average Centroidal Velocity(RHACV)and the Capture Point(CP),ensuring effective stepping adjustments and disturbance rejection.With the torque-controlled humanoid robot BHR8P,extensive simulation and experimental results demonstrate the effectiveness of the proposed method,highlighting its capability to adapt to and recover from various disturbances with improved stability.
基金supported in part by the National Natural Science Foundation of China(Grant Numbers:U2013602)the National Key R&D Program of China(Grant Number:2022YFB4601802)+1 种基金the Self-Planned Task of the State Key Laboratory of Robotics and System(Grant Number:2023FRFK01001)the National Independent Project of China(Grant Number:SKLR202301A12).
文摘Existing control methods for humanoid robots,such as Model Predictive Control(MPC)and Reinforcement Learning(RL),generally lack the modeling and exploitation of rhythmic mechanisms.As a result,they struggle to balance stability,energy efficiency,and gait transition capability during typical rhythmic motions like walking and running.To address this limitation,we propose Walk2Run,a unified control framework inspired by biological rhythmicity.The method introduces control priors based on the frequency modulation observed in human walk-run transitions.Specifically,we extract rhythmic parameters from motion capture data to construct a Rhythm Generator grounded in Central Pattern Generator(CPG)principles,which guides the policy to produce speed-adaptive periodic motion.This rhythmic guidance is further integrated with a constrained reinforcement learning framework using barrier function optimization,enhancing training stability and output feasibility.Experimental results demonstrate that our method outperforms traditional approaches across multiple metrics,achieving more natural rhythmic motion with improved energy efficiency in medium-to high-speed scenarios,while also enhancing gait stability and adaptability to the robotic platform.
基金supported by the key research and development project of Science and Technology Department of Jilin Province(No.20230201102GX)the Natural Science Foundation of Chongqing(No.CSTB2022NSCQ-MSX0278)the 2023 college students innovation and entrepreneurship training plan(202310183105).
文摘Humanoid robots exhibit structures and movements akin to those of humans,enabling them to assist or substitute for humans in various operations without necessitating alterations to their typical environment and tools.Sustaining bal-ance amidst disturbances constitutes a fundamental capability for humanoid robots.Consequently,adopting efficacious strategies to manage instability and mitigate injuries resulting from falls assumes paramount importance in advancing the widespread adoption of humanoid robotics.This paper presents a comprehensive overview of the ongoing development of strategies for coping with falls in humanoid robots.It systematically reviews and discusses three critical facets:fall state detection,preventive actions against falls,and post-fall protection measures.The paper undertakes a thorough classifica-tion of existing coping methodologies across different stages of falls,analyzes the merits and drawbacks of each approach,and outlines the evolving trajectory of solutions for addressing fall-related challenges across distinct stages.Finally,the paper provides a succinct summary and future prospects for the current fall coping strategies tailored for humanoid robots.
文摘This paper proposes the Leg Dimensional Synergistic Optimization Strategy(LDSOS)for humanoid robotic legs based on mechanism decoupling and performance assignment.The proposed method addresses the interdependent effects of dimensional parameters on the local and whole mechanisms in the design of hybrid humanoid robotic legs.It sequentially optimizes the dimensional parameters of the local and whole mechanism,thereby balancing the motion performance requirements of both.Additionally,it considers the assignment of efficient performance resources between the Local Functional Workspace(LFW)and the Whole Available Workspace(WAW).To facilitate the modeling and optimization process,a local/whole Equivalent Configuration Framework(ECF)is introduced.By decoupling the hybrid mechanism into a whole mechanism and multiple local mechanisms,the ECF enhances the efficiency of design,modeling,and performance evaluation.Prototype experiments are conducted to validate the effectiveness of LDSOS.This research provides an effective configuration framework for humanoid robotic leg design,establishing a theoretical and practical foundation for future optimized designs of humanoid robotic legs and pioneering novel approaches to the design of complex hybrid humanoid robotic legs.
文摘Activation of neutrophil membrane receptors initiates intracellular signal transduction cascades that orchestrate the cell's effector functions,including phagocytosis,production of reactive oxygen and halogen species,degranulation,and NETosis(formation of neutrophil extracellular traps[NETs]).NETs,which contain antimicrobial compounds such as myeloperoxidase(MPO),represent a strategy to combat infection.However,excessive production of NETs promotes thrombosis,diabetes mellitus,and other diseases.Therefore,investigations into the mechanisms of NETosis and the identification of modulators of this process are critical for developing strategies to address NETosis-related disorders.Here,we identified a novel NETosis inducer,human serum albumin(HSA)modified by the MPO product hypochlorous acid(HSAHOCl),whose accumulation in vivo was correlated with inflammatory processes.Using human blood neutrophils,we investigated HSAHOCl-induced NETosis and detected NET formation by flow cytometry.The results showed that the mechanism of HSAHOClinduced NETosis involved MPO,NADPH oxidase,and phosphatidylinositol 3-kinases(PI3Ks),and that HSAHOCl activated a reactive oxygen species-dependent suicidal type of NETosis.Moreover,HSAHOCl-induced NETosis was inhibited by an anti-HSAHOCl monoclonal antibody.Thus,our findings may facilitate the development of strategies to modulate NETosis in inflammation associated with elevated MPO activity.
基金supported by the National Natural Science Foundation of China(Grant No.62073041)the Open Fund of Laboratory of Aerospace Servo Actuation and Transmission(Grant No.LASAT-2023A04)the Fundamental Research Funds for the Central Universities(Grant Nos.2024CX06011,2024CX06079)。
文摘Passive bionic feet,known for their human-like compliance,have garnered attention for their potential to achieve notable environmental adaptability.In this paper,a method was proposed to unifying passive bionic feet static supporting stability and dynamic terrain adaptability through the utilization of the Rigid-Elastic Hybrid(REH)dynamics model.First,a bionic foot model,named the Hinge Tension Elastic Complex(HTEC)model,was developed by extracting key features from human feet.Furthermore,the kinematics and REH dynamics of the HTEC model were established.Based on the foot dynamics,a nonlinear optimization method for stiffness matching(NOSM)was designed.Finally,the HTEC-based foot was constructed and applied onto BHR-B2 humanoid robot.The foot static stability is achieved.The enhanced adaptability is observed as the robot traverses square steel,lawn,and cobblestone terrains.Through proposed design method and structure,the mobility of the humanoid robot is improved.
文摘Food Science and Human Wellness (FSHW ISSN:2213-4530, CN 10-1750/TS) publishes original research papers demonstrating the latest advancement of multidisciplinary subjects related to food science and human health.Topics may include but not limited to: nutriology, biochemistry, microbiology, immunology and toxicology.
