Hydrogen energy is a crucial support for China’s low-carbon energy transition.With the large-scale integration of renewable energy,the combination of hydrogen and integrated energy systems has become one of the most ...Hydrogen energy is a crucial support for China’s low-carbon energy transition.With the large-scale integration of renewable energy,the combination of hydrogen and integrated energy systems has become one of the most promising directions of development.This paper proposes an optimized schedulingmodel for a hydrogen-coupled electro-heat-gas integrated energy system(HCEHG-IES)using generative adversarial imitation learning(GAIL).The model aims to enhance renewable-energy absorption,reduce carbon emissions,and improve grid-regulation flexibility.First,the optimal scheduling problem of HCEHG-IES under uncertainty is modeled as a Markov decision process(MDP).To overcome the limitations of conventional deep reinforcement learning algorithms—including long optimization time,slow convergence,and subjective reward design—this study augments the PPO algorithm by incorporating a discriminator network and expert data.The newly developed algorithm,termed GAIL,enables the agent to perform imitation learning from expert data.Based on this model,dynamic scheduling decisions are made in continuous state and action spaces,generating optimal energy-allocation and management schemes.Simulation results indicate that,compared with traditional reinforcement-learning algorithms,the proposed algorithmoffers better economic performance.Guided by expert data,the agent avoids blind optimization,shortens the offline training time,and improves convergence performance.In the online phase,the algorithm enables flexible energy utilization,thereby promoting renewable-energy absorption and reducing carbon emissions.展开更多
The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location re...The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.展开更多
This paper explores the impact of inward foreign direct investment(FDI)on entrepreneurial activity in host countries.It argues that inward FDI affects different types of entrepreneurship in distinct ways,with its impa...This paper explores the impact of inward foreign direct investment(FDI)on entrepreneurial activity in host countries.It argues that inward FDI affects different types of entrepreneurship in distinct ways,with its impact varying depending on the level of formal institutional development in the host country.On the one hand,inward FDI’s market spillover effects increase opportunities for imitative entrepreneurship and reduce entrepreneurial risk.On the other hand,inward FDI has a mixed blessing for innovative entrepreneurship:it fuels innovation through knowledge spillovers but simultaneously intensifies competition,creating uncertainty.Using 268 observations from 59 countries between 2010 and 2018,our empirical evidence reveals a striking dichotomy:inward FDI fuels imitative entrepreneurship where formal institutions are weak,yet only fosters innovative entrepreneurship where institutions are robust.Further analysis identifies key factors-such as host country R&D investment,intellectual property protection,financial development,and entrepreneurial support-that influence whether inward FDI can effectively foster innovative entrepreneurship.展开更多
The existing research on rescue robots has focused mainly on reconnaissance,detection,and firefighting,and a small number of robots that can achieve human rescue have problems such as poor safety and stability and ins...The existing research on rescue robots has focused mainly on reconnaissance,detection,and firefighting,and a small number of robots that can achieve human rescue have problems such as poor safety and stability and insufficient carrying capacity.This article addresses the above issues and cleverly combines the advantages of soft robotic arms,underactuated robotic arms,and suction cups based on the principles of bionics.A new design for a robotic arm was proposed,and its working principle was explained.Then,the human rescue process was divided into two stages,and the grasping force of the robotic arm in each stage was analyzed separately.Finally,a prototype of the principle was developed,and the feasibility of the design principle of the robotic arm was verified through grasping experiments on a cross-sectional contour model of the human chest.At the same time,grasping experiments were conducted on different objects to demonstrate the potential application of the robotic arm in grasping ground objects.This research proposes a stress envelope adsorption rescue robot arm inspired by the adhesion ability of the Drosera plant and the stress envelope effect,which can apply force to the entire surface of the human body,reduce local force on the human body,ensure load-bearing capacity and adaptability,and improve the safety and stability of rescue grasping.展开更多
The automatic and rapid generation of excavation trajectories is the foundation for achieving an intelligent excavator.To obtain high-performance trajectories that enhance operational capacity while avoiding the numer...The automatic and rapid generation of excavation trajectories is the foundation for achieving an intelligent excavator.To obtain high-performance trajectories that enhance operational capacity while avoiding the numerous issues present in existing methods for generating effective excavation paths,this paper proposes a trajectory generation method for excavators based on imitation learning,using the mole as a bionic prototype.Given the high excavation efficiency of moles,this paper first analyzes the structural characteristics of the mole’s forelimbs,its digging principles,morphology,and trajectory patterns.Subsequently,a higher-order polynomial is employed to fit and optimize the mole’s excavation trajectory.Next,imitation learning is conducted on sample trajectories based on Dynamic Movement Primitives,followed by the introduction of an obstacle avoidance algorithm.Simulation experiments and comparisons demonstrate that the mole-inspired trajectory method used in this paper performs well and possesses the ability to generate obstacle avoidance trajectories,as well as the convenience of transferring across different machine models.展开更多
IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional pro...IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional programming,BDIP leverages human's innate priors(e.g.,“A pack of tissues requires gentle grasps,cups demand firm contact”)by enabling real-time transfer of gesture and force policies during physical demon-stration.When a human demonstrator wears IntuiGrasp,driven rings provide real-time haptic feedback on contact stress and slip,while inte-grated tactile sensors translate these human policies into image data,offering valuable data for imitation learning.In this study,human teachers use IntuiGrasp to demonstrate how to grasp three types of objects:a cup,a crumpled tissue pack,and a thin playing card.IntuiGrasp translates the policies for grasping these objects into image information that describes tactile sensations in real time.展开更多
As a green sustainable alternative technology,synthesizing nitrate by electrocatalytic nitrogen oxidation reaction(NOR)can replace the traditional energyintensive Ostwald process.But low nitrogen fixation yields and p...As a green sustainable alternative technology,synthesizing nitrate by electrocatalytic nitrogen oxidation reaction(NOR)can replace the traditional energyintensive Ostwald process.But low nitrogen fixation yields and poor selectivity due to the high bond energy of the N≡N bond and competition from the oxygen evolution reaction in the electrolyte restrict its application.On the other hand,two-dimensional(2D)PdS_(2)as a member in the family of group-10 novel transition metal dichalcogenides(NTMDs)presents the interesting optical and electronic properties due to its novel folded pentagonal structure,but few researches involve to its fabrication and application.Herein,unique imitating growth feature for PdS_(2)on different 2D substrates has been firstly discovered for constructing 2D/2D heterostructures by interface engineering.Due to the different exposed chemical groups on the substrates,PdS_(2)grows as the imitation to the morphologies of the substrates and presents different thickness,size,shape and the degree of oxidation,resulting in the significant difference in the NOR activity and stability of the obtained composite catalysts.Especially,the thin and small PdS_(2)nanoplates with more defects can be obtained by decorating poly(1-vinyl-3-ethylimidazolium bromide)on the 2D substrate,easily oxidized during the preparation process,resulting in the in situ generation of SO_(4)^(2−),which plays a crucial role in reducing the activation energy of the NOR process,leading to improved efficiency for nitrate production,verified by theoretical calculation.This research provides valuable insights for the development of novel electrocatalysts based on NTMDs for NOR and highlights the importance of interface engineering in enhancing catalytic performance.展开更多
Animals can adapt to their surroundings by modifying their trunk morphology,whereas legged robots currently utilize rigid trunks.This study introduces a single-degree-of-freedom(DoF),six-revolute(6R)morphing trunk mec...Animals can adapt to their surroundings by modifying their trunk morphology,whereas legged robots currently utilize rigid trunks.This study introduces a single-degree-of-freedom(DoF),six-revolute(6R)morphing trunk mechanism designed to equip legged robots with variable-width capabilities.Subsequently,a morphology-aware locomotion learning pipeline,based on reinforcement learning,is proposed for real-time trunk-width deformation and adaptive legged locomotion.The proposed variable-width trunk is integrated into a quadrupedal robot,and the learning pipeline is employed to train the adaptive locomotion controller of this robot.This study has three key contributions:(1)An overconstrained morphing mechanism is designed to achieve single-DoF trunk-width deformation,thereby minimizing power consumption and simplifying motion control.(2)A novel morphology-adaptive learning pipeline is introduced that utilizes adversarial joint-level motion imitation to ensure coordination consistency during morphological adaptation.This method addresses dynamic disturbances and interlimb coordination disruptions caused by width modifications.(3)A historical proprioception-based asymmetric neural network architecture is utilized to attain implicit terrain perception without visual input.Collectively,these developments enable the proposed variable-width legged robot to maintain consistent locomotion across complex terrains and facilitate rapid width deformation in response to environmental changes.Extensive simulation experiments validate the proposed design and control methodology.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
Salamander robots represent an innovative class of crawling robots that combine flexible limbs and spines to achieve exceptional motion stability and adaptability in unstructured environments.These biomimetic systems ...Salamander robots represent an innovative class of crawling robots that combine flexible limbs and spines to achieve exceptional motion stability and adaptability in unstructured environments.These biomimetic systems employ soft actuators that replicate the smooth,organic movements of living organisms,significantly enhancing fluid interaction efficiency and propulsion performance.This research specifically focuses on improving dielectric elastomer actuator(DEA)-based fish-like underwater robots by developing a novel drive mechanism inspired by the salamander musculature.While aquatic organisms such as fish possess complex muscle structures that challenge direct imitation,salamanders offer a more tractable model due to their simpler anatomical organization.Notably,the lateral inferior axonal muscles in salamanders exhibit a nearly flat configuration,with myomangial membranes arranged in a linear distribution from the lateral midline to the abdominal midline—a structural feature that is particularly amenable to DEA replication.Through systematic analysis of salamander morphology,this study develops a DEA driver model that investigates two critical performance parameters:(i)the impact of electrode geometry on the bending angle;and(ii)the relationship between driver quantity and angular displacement.The experimental results confirm that DEAs mimicking salamander muscle architecture can achieve substantially increased bending angles under optimized conditions,thereby demonstrating measurable improvements in robotic propulsion capabilities.展开更多
Robots are key to expanding the scope of space applications.The end-to-end training for robot vision-based detection and precision operations is challenging owing to constraints such as extreme environments and high c...Robots are key to expanding the scope of space applications.The end-to-end training for robot vision-based detection and precision operations is challenging owing to constraints such as extreme environments and high computational overhead.This study proposes a lightweight integrated framework for grasp detection and imitation learning,named GD-IL;it comprises a grasp detection algorithm based on manipulability and Gaussian mixture model(manipulability-GMM),and a grasp trajectory generation algorithm based on a two-stage robot imitation learning algorithm(TS-RIL).In the manipulability-GMM algorithm,we apply GMM clustering and ellipse regression to the object point cloud,propose two judgment criteria to generate multiple candidate grasp bounding boxes for the robot,and use manipulability as a metric for selecting the optimal grasp bounding box.The stages of the TS-RIL algorithm are grasp trajectory learning and robot pose optimization.In the first stage,the robot grasp trajectory is characterized using a second-order dynamic movement primitive model and Gaussian mixture regression(GMM).By adjusting the function form of the forcing term,the robot closely approximates the target-grasping trajectory.In the second stage,a robot pose optimization model is built based on the derived pose error formula and manipulability metric.This model allows the robot to adjust its configuration in real time while grasping,thereby effectively avoiding singularities.Finally,an algorithm verification platform is developed based on a Robot Operating System and a series of comparative experiments are conducted in real-world scenarios.The experimental results demonstrate that GD-IL significantly improves the effectiveness and robustness of grasp detection and trajectory imitation learning,outperforming existing state-of-the-art methods in execution efficiency,manipulability,and success rate.展开更多
Group living animals form striking aggregation patterns and display synchronization,polarization,and collective intelligence.Though many col-lective behavioral studies have been conducted on small animals like insects...Group living animals form striking aggregation patterns and display synchronization,polarization,and collective intelligence.Though many col-lective behavioral studies have been conducted on small animals like insects and fish,research on large animals is still rare due to the limited availability of field collective data.We used drones to record videos and analyzed the decision-making and behavioral spatial patterns in orienta-tion of Kiang(Tibetan wild ass,Equus kiang).Leadership is unevenly distributed among Kiang,with the minority initiating majority behavior-shift decisions.Decisions of individual to join are driven by imitation between group members,and are largely dependent on the number of members who have already joined.Kiang respond to the behavior and position of neighbors through different strategies.They strongly polarize when moving,therefore adopting a linear alignment.When vigilant,orientation deviation increases as they form a tighter group.They remain scattered while feeding and,in that context,adopt a side-by-side alignment.This study reveals partially-shared decision-making among Kiang,whereby copying neighbors provides the wisdom to thrive in harsh conditions.This study also suggests that animals'spatial patterns in orientation depend largely ontheirbehavioral states inachieving synchronization.展开更多
The theory of“imitation”in painting occupies a leading position in western art,which originated from the theory of“imitation”in ancient Greece,and has become one of the art theories affecting the world through the...The theory of“imitation”in painting occupies a leading position in western art,which originated from the theory of“imitation”in ancient Greece,and has become one of the art theories affecting the world through the continuous development of later generations.Through the exploration of the source of“imitation”in China and the West,there are some comments on the meaning of“imitation”in Chinese classical painting theory,such as“transfer model writing”and“image form”,which is obvious differences from the west.Traditional Chinese painting is a combination of careful observation of natural things and subjective emotions to express their own aesthetic feelings,and ultimately form a vivid artistic conception.Modern imitation is borrowed from Western imitation.In fact,imitation in traditional painting has its own meaning,which contains Chinese aesthetic thought.“Imitation”aesthetics is unique in traditional Chinese painting and is the most important form of painting art.展开更多
Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well wi...Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex problems.Given the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.展开更多
Aim The particle texture from diesel engine was imitated by use of computer. Methods The theory of fractal geometry and the diffusion limited aggregation model were used to simulate the micron texture. Results The...Aim The particle texture from diesel engine was imitated by use of computer. Methods The theory of fractal geometry and the diffusion limited aggregation model were used to simulate the micron texture. Results The fractal dimensions of granule distribution and corpuscle superficial area are quite conformed with those of measurement. Conclusion The texture parameters of engine particle cluster can be obtained precisely by use of fractal theory.展开更多
UG and imitation are two parallel hypotheses trying to answer how childrens language acquisition is realized. Imitation fails to explain how children acquire language; however, it helps a lot in childrens language acq...UG and imitation are two parallel hypotheses trying to answer how childrens language acquisition is realized. Imitation fails to explain how children acquire language; however, it helps a lot in childrens language acquisition.展开更多
It is of vital importance for modern college English teaching to properly construct an interactive multimedia-internet-based teaching system, the structure of which is clearly elaborated in this paper. An IMITS usuall...It is of vital importance for modern college English teaching to properly construct an interactive multimedia-internet-based teaching system, the structure of which is clearly elaborated in this paper. An IMITS usually consists of hardware, software, teaching and management. At the end of this paper, a conclusion is made that only when all the four parts of IMITS are construct ed such as is demonstrated, can the IMITS exert its full effects in college English teaching.展开更多
基金supported by State Grid Corporation Technology Project(No.522437250003).
文摘Hydrogen energy is a crucial support for China’s low-carbon energy transition.With the large-scale integration of renewable energy,the combination of hydrogen and integrated energy systems has become one of the most promising directions of development.This paper proposes an optimized schedulingmodel for a hydrogen-coupled electro-heat-gas integrated energy system(HCEHG-IES)using generative adversarial imitation learning(GAIL).The model aims to enhance renewable-energy absorption,reduce carbon emissions,and improve grid-regulation flexibility.First,the optimal scheduling problem of HCEHG-IES under uncertainty is modeled as a Markov decision process(MDP).To overcome the limitations of conventional deep reinforcement learning algorithms—including long optimization time,slow convergence,and subjective reward design—this study augments the PPO algorithm by incorporating a discriminator network and expert data.The newly developed algorithm,termed GAIL,enables the agent to perform imitation learning from expert data.Based on this model,dynamic scheduling decisions are made in continuous state and action spaces,generating optimal energy-allocation and management schemes.Simulation results indicate that,compared with traditional reinforcement-learning algorithms,the proposed algorithmoffers better economic performance.Guided by expert data,the agent avoids blind optimization,shortens the offline training time,and improves convergence performance.In the online phase,the algorithm enables flexible energy utilization,thereby promoting renewable-energy absorption and reducing carbon emissions.
基金supported by the Natural Science Foundation of Fujian Province of China(2025J01380)National Natural Science Foundation of China(No.62471139)+3 种基金the Major Health Research Project of Fujian Province(2021ZD01001)Fujian Provincial Units Special Funds for Education and Research(2022639)Fujian University of Technology Research Start-up Fund(GY-S24002)Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare(GY-H-24179).
文摘The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.
基金supported by the National Natural Science Foundation of China(NSFC)“Research on Entrepreneurial Activities in Dynamic and Complex Institutional Environments”(Grant No.71872193)the Guangdong Basic and Applied Basic Research Foundation“Research on the Multiple Institutional Effects of Innovative Entrepreneurship from the Perspective of Knowledge Utilization”(Grant No.2023A1515110323)the Guangdong Basic and Applied Basic Research Foundation“From Strategic to Substantive Transformation:The Dynamic Process of Multi-Factor Family Involvement and Enterprise Digital Transformation”(Grant No.2024A1515012619).
文摘This paper explores the impact of inward foreign direct investment(FDI)on entrepreneurial activity in host countries.It argues that inward FDI affects different types of entrepreneurship in distinct ways,with its impact varying depending on the level of formal institutional development in the host country.On the one hand,inward FDI’s market spillover effects increase opportunities for imitative entrepreneurship and reduce entrepreneurial risk.On the other hand,inward FDI has a mixed blessing for innovative entrepreneurship:it fuels innovation through knowledge spillovers but simultaneously intensifies competition,creating uncertainty.Using 268 observations from 59 countries between 2010 and 2018,our empirical evidence reveals a striking dichotomy:inward FDI fuels imitative entrepreneurship where formal institutions are weak,yet only fosters innovative entrepreneurship where institutions are robust.Further analysis identifies key factors-such as host country R&D investment,intellectual property protection,financial development,and entrepreneurial support-that influence whether inward FDI can effectively foster innovative entrepreneurship.
基金Supported by National Natural Science Foundation of China(Grant No.52475032)Central Government Guides Local Science and Technology Development Fund Projects(Grant No.246Z2001G)Hebei Provincial Natural Science Foundation Key Projects(Grant No.E2021203125).
文摘The existing research on rescue robots has focused mainly on reconnaissance,detection,and firefighting,and a small number of robots that can achieve human rescue have problems such as poor safety and stability and insufficient carrying capacity.This article addresses the above issues and cleverly combines the advantages of soft robotic arms,underactuated robotic arms,and suction cups based on the principles of bionics.A new design for a robotic arm was proposed,and its working principle was explained.Then,the human rescue process was divided into two stages,and the grasping force of the robotic arm in each stage was analyzed separately.Finally,a prototype of the principle was developed,and the feasibility of the design principle of the robotic arm was verified through grasping experiments on a cross-sectional contour model of the human chest.At the same time,grasping experiments were conducted on different objects to demonstrate the potential application of the robotic arm in grasping ground objects.This research proposes a stress envelope adsorption rescue robot arm inspired by the adhesion ability of the Drosera plant and the stress envelope effect,which can apply force to the entire surface of the human body,reduce local force on the human body,ensure load-bearing capacity and adaptability,and improve the safety and stability of rescue grasping.
基金supported by the National Science Foundation of China(Grant No.52375246,No.52372428,No.52105100)Guangxi Science and Technology Program(Grant No.2023AB09014)Jilin Province Science and Technology Development Program,(Grant No.20230201094GX,No.20230201069GX).
文摘The automatic and rapid generation of excavation trajectories is the foundation for achieving an intelligent excavator.To obtain high-performance trajectories that enhance operational capacity while avoiding the numerous issues present in existing methods for generating effective excavation paths,this paper proposes a trajectory generation method for excavators based on imitation learning,using the mole as a bionic prototype.Given the high excavation efficiency of moles,this paper first analyzes the structural characteristics of the mole’s forelimbs,its digging principles,morphology,and trajectory patterns.Subsequently,a higher-order polynomial is employed to fit and optimize the mole’s excavation trajectory.Next,imitation learning is conducted on sample trajectories based on Dynamic Movement Primitives,followed by the introduction of an obstacle avoidance algorithm.Simulation experiments and comparisons demonstrate that the mole-inspired trajectory method used in this paper performs well and possesses the ability to generate obstacle avoidance trajectories,as well as the convenience of transferring across different machine models.
文摘IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional programming,BDIP leverages human's innate priors(e.g.,“A pack of tissues requires gentle grasps,cups demand firm contact”)by enabling real-time transfer of gesture and force policies during physical demon-stration.When a human demonstrator wears IntuiGrasp,driven rings provide real-time haptic feedback on contact stress and slip,while inte-grated tactile sensors translate these human policies into image data,offering valuable data for imitation learning.In this study,human teachers use IntuiGrasp to demonstrate how to grasp three types of objects:a cup,a crumpled tissue pack,and a thin playing card.IntuiGrasp translates the policies for grasping these objects into image information that describes tactile sensations in real time.
基金the Australian Research Council (ARC) through Future Fellowship (FT210100298)Discovery Project (DP220100603)+8 种基金Linkage Project (LP210200504,LP220100088, LP230200897)Industrial Transformation Research Hub (IH240100009) schemesthe Australian Government through the Cooperative Research Centres Projects (CRCPXIII000077)the Australian Renewable Energy Agency (ARENA) as part of ARENA’s Transformative Research Accelerating Commercialisation Program (TM021)European Commission’s Australia-Spain Network for Innovation and Research Excellence (Au Spire)the Foundation of Liaoning Province Education Administration (2020LQN03)the Foundation of Liaoning Province Education Administration in 2024 (Independent topic selection-Natural science category-Strategic industrialization project LJ212410163023)the Scientific Research Fund of Liaoning Provincial Education Department (JYTMS20230767)the Liaoning Revitalization Talents Program (XLYC2007132)
文摘As a green sustainable alternative technology,synthesizing nitrate by electrocatalytic nitrogen oxidation reaction(NOR)can replace the traditional energyintensive Ostwald process.But low nitrogen fixation yields and poor selectivity due to the high bond energy of the N≡N bond and competition from the oxygen evolution reaction in the electrolyte restrict its application.On the other hand,two-dimensional(2D)PdS_(2)as a member in the family of group-10 novel transition metal dichalcogenides(NTMDs)presents the interesting optical and electronic properties due to its novel folded pentagonal structure,but few researches involve to its fabrication and application.Herein,unique imitating growth feature for PdS_(2)on different 2D substrates has been firstly discovered for constructing 2D/2D heterostructures by interface engineering.Due to the different exposed chemical groups on the substrates,PdS_(2)grows as the imitation to the morphologies of the substrates and presents different thickness,size,shape and the degree of oxidation,resulting in the significant difference in the NOR activity and stability of the obtained composite catalysts.Especially,the thin and small PdS_(2)nanoplates with more defects can be obtained by decorating poly(1-vinyl-3-ethylimidazolium bromide)on the 2D substrate,easily oxidized during the preparation process,resulting in the in situ generation of SO_(4)^(2−),which plays a crucial role in reducing the activation energy of the NOR process,leading to improved efficiency for nitrate production,verified by theoretical calculation.This research provides valuable insights for the development of novel electrocatalysts based on NTMDs for NOR and highlights the importance of interface engineering in enhancing catalytic performance.
基金Supported by State Key Lab of Mechanical System and Vibration Project of China(Grant No.MSVZD202008).
文摘Animals can adapt to their surroundings by modifying their trunk morphology,whereas legged robots currently utilize rigid trunks.This study introduces a single-degree-of-freedom(DoF),six-revolute(6R)morphing trunk mechanism designed to equip legged robots with variable-width capabilities.Subsequently,a morphology-aware locomotion learning pipeline,based on reinforcement learning,is proposed for real-time trunk-width deformation and adaptive legged locomotion.The proposed variable-width trunk is integrated into a quadrupedal robot,and the learning pipeline is employed to train the adaptive locomotion controller of this robot.This study has three key contributions:(1)An overconstrained morphing mechanism is designed to achieve single-DoF trunk-width deformation,thereby minimizing power consumption and simplifying motion control.(2)A novel morphology-adaptive learning pipeline is introduced that utilizes adversarial joint-level motion imitation to ensure coordination consistency during morphological adaptation.This method addresses dynamic disturbances and interlimb coordination disruptions caused by width modifications.(3)A historical proprioception-based asymmetric neural network architecture is utilized to attain implicit terrain perception without visual input.Collectively,these developments enable the proposed variable-width legged robot to maintain consistent locomotion across complex terrains and facilitate rapid width deformation in response to environmental changes.Extensive simulation experiments validate the proposed design and control methodology.
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.
基金supported by the Joint Open Fund of Guizhou Provincial Department of Education(Grant No.[2022]439)the Doctoral Research Foundation of Guiyang University,China(Grant No.GYUKY-2025)。
文摘Salamander robots represent an innovative class of crawling robots that combine flexible limbs and spines to achieve exceptional motion stability and adaptability in unstructured environments.These biomimetic systems employ soft actuators that replicate the smooth,organic movements of living organisms,significantly enhancing fluid interaction efficiency and propulsion performance.This research specifically focuses on improving dielectric elastomer actuator(DEA)-based fish-like underwater robots by developing a novel drive mechanism inspired by the salamander musculature.While aquatic organisms such as fish possess complex muscle structures that challenge direct imitation,salamanders offer a more tractable model due to their simpler anatomical organization.Notably,the lateral inferior axonal muscles in salamanders exhibit a nearly flat configuration,with myomangial membranes arranged in a linear distribution from the lateral midline to the abdominal midline—a structural feature that is particularly amenable to DEA replication.Through systematic analysis of salamander morphology,this study develops a DEA driver model that investigates two critical performance parameters:(i)the impact of electrode geometry on the bending angle;and(ii)the relationship between driver quantity and angular displacement.The experimental results confirm that DEAs mimicking salamander muscle architecture can achieve substantially increased bending angles under optimized conditions,thereby demonstrating measurable improvements in robotic propulsion capabilities.
基金Supported by National Natural Science Foundation of China(Grant No.52475280)Shaanxi Provincial Natural Science Basic Research Program(Grant No.2025SYSSYSZD-105).
文摘Robots are key to expanding the scope of space applications.The end-to-end training for robot vision-based detection and precision operations is challenging owing to constraints such as extreme environments and high computational overhead.This study proposes a lightweight integrated framework for grasp detection and imitation learning,named GD-IL;it comprises a grasp detection algorithm based on manipulability and Gaussian mixture model(manipulability-GMM),and a grasp trajectory generation algorithm based on a two-stage robot imitation learning algorithm(TS-RIL).In the manipulability-GMM algorithm,we apply GMM clustering and ellipse regression to the object point cloud,propose two judgment criteria to generate multiple candidate grasp bounding boxes for the robot,and use manipulability as a metric for selecting the optimal grasp bounding box.The stages of the TS-RIL algorithm are grasp trajectory learning and robot pose optimization.In the first stage,the robot grasp trajectory is characterized using a second-order dynamic movement primitive model and Gaussian mixture regression(GMM).By adjusting the function form of the forcing term,the robot closely approximates the target-grasping trajectory.In the second stage,a robot pose optimization model is built based on the derived pose error formula and manipulability metric.This model allows the robot to adjust its configuration in real time while grasping,thereby effectively avoiding singularities.Finally,an algorithm verification platform is developed based on a Robot Operating System and a series of comparative experiments are conducted in real-world scenarios.The experimental results demonstrate that GD-IL significantly improves the effectiveness and robustness of grasp detection and trajectory imitation learning,outperforming existing state-of-the-art methods in execution efficiency,manipulability,and success rate.
基金supported by Tibet Major Science and Technology Project(XZ201901-GA-06)National Natural Science Foundation of China(32101237&41871294)National key research and development program(2022YFC3202104).
文摘Group living animals form striking aggregation patterns and display synchronization,polarization,and collective intelligence.Though many col-lective behavioral studies have been conducted on small animals like insects and fish,research on large animals is still rare due to the limited availability of field collective data.We used drones to record videos and analyzed the decision-making and behavioral spatial patterns in orienta-tion of Kiang(Tibetan wild ass,Equus kiang).Leadership is unevenly distributed among Kiang,with the minority initiating majority behavior-shift decisions.Decisions of individual to join are driven by imitation between group members,and are largely dependent on the number of members who have already joined.Kiang respond to the behavior and position of neighbors through different strategies.They strongly polarize when moving,therefore adopting a linear alignment.When vigilant,orientation deviation increases as they form a tighter group.They remain scattered while feeding and,in that context,adopt a side-by-side alignment.This study reveals partially-shared decision-making among Kiang,whereby copying neighbors provides the wisdom to thrive in harsh conditions.This study also suggests that animals'spatial patterns in orientation depend largely ontheirbehavioral states inachieving synchronization.
文摘The theory of“imitation”in painting occupies a leading position in western art,which originated from the theory of“imitation”in ancient Greece,and has become one of the art theories affecting the world through the continuous development of later generations.Through the exploration of the source of“imitation”in China and the West,there are some comments on the meaning of“imitation”in Chinese classical painting theory,such as“transfer model writing”and“image form”,which is obvious differences from the west.Traditional Chinese painting is a combination of careful observation of natural things and subjective emotions to express their own aesthetic feelings,and ultimately form a vivid artistic conception.Modern imitation is borrowed from Western imitation.In fact,imitation in traditional painting has its own meaning,which contains Chinese aesthetic thought.“Imitation”aesthetics is unique in traditional Chinese painting and is the most important form of painting art.
基金supported by the Open Project of Xiangjiang Laboratory (22XJ02003)Scientific Project of the National University of Defense Technology (NUDT)(ZK21-07, 23-ZZCX-JDZ-28)+1 种基金the National Science Fund for Outstanding Young Scholars (62122093)the National Natural Science Foundation of China (72071205)。
文摘Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex problems.Given the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.
文摘Aim The particle texture from diesel engine was imitated by use of computer. Methods The theory of fractal geometry and the diffusion limited aggregation model were used to simulate the micron texture. Results The fractal dimensions of granule distribution and corpuscle superficial area are quite conformed with those of measurement. Conclusion The texture parameters of engine particle cluster can be obtained precisely by use of fractal theory.
文摘UG and imitation are two parallel hypotheses trying to answer how childrens language acquisition is realized. Imitation fails to explain how children acquire language; however, it helps a lot in childrens language acquisition.
文摘It is of vital importance for modern college English teaching to properly construct an interactive multimedia-internet-based teaching system, the structure of which is clearly elaborated in this paper. An IMITS usually consists of hardware, software, teaching and management. At the end of this paper, a conclusion is made that only when all the four parts of IMITS are construct ed such as is demonstrated, can the IMITS exert its full effects in college English teaching.
