In recent years,breakthrough has been made in the field of artificial intelligence(AI),which has also revolutionized the industry of robotics.Soft robots featured with high-level safety,less weight,lower power consump...In recent years,breakthrough has been made in the field of artificial intelligence(AI),which has also revolutionized the industry of robotics.Soft robots featured with high-level safety,less weight,lower power consumption have always been one of the research hotspots.Recently,multifunctional sensors for perception of soft robotics have been rapidly developed,while more algorithms and models of machine learning with high accuracy have been optimized and proposed.Designs of soft robots with AI have also been advanced ranging from multimodal sensing,human-machine interaction to effective actuation in robotic systems.Nonethe-less,comprehensive reviews concerning the new developments and strategies for the ingenious design of the soft robotic systems equipped with AI are rare.Here,the new development is systematically reviewed in the field of soft robots with AI.First,background and mechanisms of soft robotic systems are briefed,after which development focused on how to endow the soft robots with AI,including the aspects of feeling,thought and reaction,is illustrated.Next,applications of soft robots with AI are systematically summarized and discussed together with advanced strategies proposed for performance enhancement.Design thoughts for future intelligent soft robotics are pointed out.Finally,some perspectives are put forward.展开更多
Research of autonomous manufacturing systems is motivated both by the new technical possibilities of cyber-physical systems and by the practical needs of the industry.Autonomous operation in semi-structured industrial...Research of autonomous manufacturing systems is motivated both by the new technical possibilities of cyber-physical systems and by the practical needs of the industry.Autonomous operation in semi-structured industrial environments can now be supported by advanced sensor technologies,digital twins,artificial intelligence and novel communication techniques.These enable real-time monitoring of production processes,situation recognition and prediction,automated and adaptive(re)planning,teamwork and performance improvement by learning.This paper summarizes the main requirements towards autonomous industrial robotics and suggests a generic workflow for realizing such systems.Application case studies will be presented from recent practice at HUN-REN SZTAKI in a broad range of domains such as assembly,welding,grinding,picking and placing,and machining.The various solutions have in common that they use a generic digital twin concept as their core.After making general recommendations for realizing autonomous robotic solutions in the industry,open issues for future research will be discussed.展开更多
In classical matter systems, typical phase-transition phenomena usually stem from changes in state variables, such as temperature and pressure, induced by external regulations such as heat transfer and volume adjustme...In classical matter systems, typical phase-transition phenomena usually stem from changes in state variables, such as temperature and pressure, induced by external regulations such as heat transfer and volume adjustment. However, in active matter systems, the self-propulsion nature of active particles endows the systems with the ability to induce unique collectivestate transitions by spontaneously regulating individual properties to alter the overall states. Based on an innovative robot-swarm experimental system, we demonstrate a field-driven active matter model capable of modulating individual motion behaviors through interaction with a recoverable environmental resource field by the resource perception and consumption.In the simulated model, by gradually reducing the individual resource-conversion coefficient over time, this robotic active matter can spontaneously decrease the overall level of motion, thereby actively achieving a regulation behavior like the cooling-down control. Through simulation calculations, we discover that the spatial structures of this robotic active matter convert from disorder to order during this process, with the resulting ordered structures exhibiting a high self-adaptability on the geometry of the environmental boundaries.展开更多
This study proposes a method for uniformly revolving swarm robots to entrap multiple targets,which is based on a gene regulatory network,an adaptive decision mechanism,and an improved Vicsek-model.Using the gene regul...This study proposes a method for uniformly revolving swarm robots to entrap multiple targets,which is based on a gene regulatory network,an adaptive decision mechanism,and an improved Vicsek-model.Using the gene regulatory network method,the robots can generate entrapping patterns according to the environmental input,including the positions of the targets and obstacles.Next,an adaptive decision mechanism is proposed,allowing each robot to choose the most well-adapted capture point on the pattern,based on its environment.The robots employ an improved Vicsek-model to maneuver to the planned capture point smoothly,without colliding with other robots or obstacles.The proposed decision mechanism,combined with the improved Vicsek-model,can form a uniform entrapment shape and create a revolving effect around targets while entrapping them.This study also enables swarm robots,with an adaptive pattern formation,to entrap multiple targets in complex environments.Swarm robots can be deployed in the military field of unmanned aerial vehicles’(UAVs)entrapping multiple targets.Simulation experiments demonstrate the feasibility and superiority of the proposed gene regulatory network method.展开更多
Pipeline isolation plugging robot (PIPR) is an important tool in pipeline maintenance operation. During the plugging process, the violent vibration will occur by the flow field, which can cause serious damage to the p...Pipeline isolation plugging robot (PIPR) is an important tool in pipeline maintenance operation. During the plugging process, the violent vibration will occur by the flow field, which can cause serious damage to the pipeline and PIPR. In this paper, we propose a dynamic regulating strategy to reduce the plugging-induced vibration by regulating the spoiler angle and plugging velocity. Firstly, the dynamic plugging simulation and experiment are performed to study the flow field changes during dynamic plugging. And the pressure difference is proposed to evaluate the degree of flow field vibration. Secondly, the mathematical models of pressure difference with plugging states and spoiler angles are established based on the extreme learning machine (ELM) optimized by improved sparrow search algorithm (ISSA). Finally, a modified Q-learning algorithm based on simulated annealing is applied to determine the optimal strategy for the spoiler angle and plugging velocity in real time. The results show that the proposed method can reduce the plugging-induced vibration by 19.9% and 32.7% on average, compared with single-regulating methods. This study can effectively ensure the stability of the plugging process.展开更多
A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip ...A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip position. The Lagrangian principle is utilized to model the dynamic function of the single-degree flexible manipulator incorporating the assumed modes method. Simulation results of the fuzzy adaptive control method in the location control and the trajectory tracking with different tip disturbances are presented and compared with the results of the classic PD control. It shows that the controller can obtain the stable and robust performance.展开更多
This paper proposes a continuous cognitive emotional regulation model for robot in the case of external emotional stimulus from interactive person's expressions. It integrates a guiding cognitive reappraisal strat...This paper proposes a continuous cognitive emotional regulation model for robot in the case of external emotional stimulus from interactive person's expressions. It integrates a guiding cognitive reappraisal strategy into the HMM(Hidden Markov Model) emotional interactive model for empathizing between robot and person. The emotion is considered as a source in the 3D space(Arousal, Valence, and Stance). State transition and emotion intensity can be quantitatively analyzed in the continuous space. This cognition-emotion interactive model have been verified by the expression and behavior robot. Empathizing is the main distinguishing feature of our work, and it is realized by the emotional regulation which operated in a continuous 3D emotional space enabling a wide range of intermediate emotions. The experiment results provide evidence with acceptability, accuracy, richness, fluency, interestingness, friendliness and exaggeration that the robot with cognition and emotional control ability could be better accepted in the human-robot interaction(HRI).展开更多
The existing kinematic parameter calibration method cannot further improve the absolute positioning accuracy of the robot due to the uncertainty of positioning error caused by robot joint backlash.In view of this prob...The existing kinematic parameter calibration method cannot further improve the absolute positioning accuracy of the robot due to the uncertainty of positioning error caused by robot joint backlash.In view of this problem,a closed‑loop feedback accuracy compensation method for robot joints was proposed.Firstly,a Chebyshev polynomial error estimation model was established which took geometric error and non‑geometric error into account.In addition,the absolute linear grating scale was installed at each joint of the robot and the positioning error of the robot end was mapped to the joint angle.And the joint angle corrected value was obtained.Furthermore,the closed‑loop feedback of robot joints was established to realize the online correction of the positioning error.Finally,an experiment on the KUKA KR210 industrial robot was conducted to demonstrate the effectiveness of the method.The result shows that the maximum absolute positioning error of the robot is reduced by 75%from 0.76 mm to 0.19 mm.This method can compensate the robot joint backlash effectively and further improve the absolute positioning accuracy of the robot.展开更多
This paper sets up a robotic manipulator model on slewing crane. The model can synthetically describe the dynamic behavior of the load of slewing crane in rotating, elevating and hoisting motions. The dynamic equation...This paper sets up a robotic manipulator model on slewing crane. The model can synthetically describe the dynamic behavior of the load of slewing crane in rotating, elevating and hoisting motions. The dynamic equations of the system are recursively derived by a Newton Euler method. The dynamic behavior of the load of slewing crane in rotating motion is simulated on a computer. The method of robotic dynamics to derive the dynamic equations of the swing of load is accurate and convenient and it has good regularity. The result of the study provides a base in theory on design of crane and an accurate mathematical model for controlling the swing of load.展开更多
基金supported by the Hong Kong Polytechnic University(Project No.1-WZ1Y).
文摘In recent years,breakthrough has been made in the field of artificial intelligence(AI),which has also revolutionized the industry of robotics.Soft robots featured with high-level safety,less weight,lower power consumption have always been one of the research hotspots.Recently,multifunctional sensors for perception of soft robotics have been rapidly developed,while more algorithms and models of machine learning with high accuracy have been optimized and proposed.Designs of soft robots with AI have also been advanced ranging from multimodal sensing,human-machine interaction to effective actuation in robotic systems.Nonethe-less,comprehensive reviews concerning the new developments and strategies for the ingenious design of the soft robotic systems equipped with AI are rare.Here,the new development is systematically reviewed in the field of soft robots with AI.First,background and mechanisms of soft robotic systems are briefed,after which development focused on how to endow the soft robots with AI,including the aspects of feeling,thought and reaction,is illustrated.Next,applications of soft robots with AI are systematically summarized and discussed together with advanced strategies proposed for performance enhancement.Design thoughts for future intelligent soft robotics are pointed out.Finally,some perspectives are put forward.
基金supported by the European Union within the framework of the“National Laboratory for Autonomous Systems”(No.RRF-2.3.1-212022-00002)the Hungarian“Research on prime exploitation of the potential provided by the industrial digitalisation(No.ED-18-2-2018-0006)”the“Research on cooperative production and logistics systems to support a competitive and sustainable economy(No.TKP2021-NKTA-01)”。
文摘Research of autonomous manufacturing systems is motivated both by the new technical possibilities of cyber-physical systems and by the practical needs of the industry.Autonomous operation in semi-structured industrial environments can now be supported by advanced sensor technologies,digital twins,artificial intelligence and novel communication techniques.These enable real-time monitoring of production processes,situation recognition and prediction,automated and adaptive(re)planning,teamwork and performance improvement by learning.This paper summarizes the main requirements towards autonomous industrial robotics and suggests a generic workflow for realizing such systems.Application case studies will be presented from recent practice at HUN-REN SZTAKI in a broad range of domains such as assembly,welding,grinding,picking and placing,and machining.The various solutions have in common that they use a generic digital twin concept as their core.After making general recommendations for realizing autonomous robotic solutions in the industry,open issues for future research will be discussed.
基金Project supported by the National Natural Science Foundation of China(Grant No.12174041)China Postdoctoral Science Foundation(Grant No.2022M723118)the Seed Grants from the Wenzhou Institute,University of Chinese Academy of Sciences(Grant No.WIUCASQD2021002)。
文摘In classical matter systems, typical phase-transition phenomena usually stem from changes in state variables, such as temperature and pressure, induced by external regulations such as heat transfer and volume adjustment. However, in active matter systems, the self-propulsion nature of active particles endows the systems with the ability to induce unique collectivestate transitions by spontaneously regulating individual properties to alter the overall states. Based on an innovative robot-swarm experimental system, we demonstrate a field-driven active matter model capable of modulating individual motion behaviors through interaction with a recoverable environmental resource field by the resource perception and consumption.In the simulated model, by gradually reducing the individual resource-conversion coefficient over time, this robotic active matter can spontaneously decrease the overall level of motion, thereby actively achieving a regulation behavior like the cooling-down control. Through simulation calculations, we discover that the spatial structures of this robotic active matter convert from disorder to order during this process, with the resulting ordered structures exhibiting a high self-adaptability on the geometry of the environmental boundaries.
基金funded by the National Natural Science Foundation of China(62176147)the Science and Technology Planning Project of Guangdong Province of China,the State Key Lab of Digital Manufacturing Equipment and Technology(DMETKF2019020)the National Defense Technology Innovation Special Zone Project(193-A14-226-01-01)。
文摘This study proposes a method for uniformly revolving swarm robots to entrap multiple targets,which is based on a gene regulatory network,an adaptive decision mechanism,and an improved Vicsek-model.Using the gene regulatory network method,the robots can generate entrapping patterns according to the environmental input,including the positions of the targets and obstacles.Next,an adaptive decision mechanism is proposed,allowing each robot to choose the most well-adapted capture point on the pattern,based on its environment.The robots employ an improved Vicsek-model to maneuver to the planned capture point smoothly,without colliding with other robots or obstacles.The proposed decision mechanism,combined with the improved Vicsek-model,can form a uniform entrapment shape and create a revolving effect around targets while entrapping them.This study also enables swarm robots,with an adaptive pattern formation,to entrap multiple targets in complex environments.Swarm robots can be deployed in the military field of unmanned aerial vehicles’(UAVs)entrapping multiple targets.Simulation experiments demonstrate the feasibility and superiority of the proposed gene regulatory network method.
基金This work was financially supported by the National Natural Science Foundation of China(Grant No.51575528)the Science Foundation of China University of Petroleum,Beijing(No.2462022QEDX011).
文摘Pipeline isolation plugging robot (PIPR) is an important tool in pipeline maintenance operation. During the plugging process, the violent vibration will occur by the flow field, which can cause serious damage to the pipeline and PIPR. In this paper, we propose a dynamic regulating strategy to reduce the plugging-induced vibration by regulating the spoiler angle and plugging velocity. Firstly, the dynamic plugging simulation and experiment are performed to study the flow field changes during dynamic plugging. And the pressure difference is proposed to evaluate the degree of flow field vibration. Secondly, the mathematical models of pressure difference with plugging states and spoiler angles are established based on the extreme learning machine (ELM) optimized by improved sparrow search algorithm (ISSA). Finally, a modified Q-learning algorithm based on simulated annealing is applied to determine the optimal strategy for the spoiler angle and plugging velocity in real time. The results show that the proposed method can reduce the plugging-induced vibration by 19.9% and 32.7% on average, compared with single-regulating methods. This study can effectively ensure the stability of the plugging process.
文摘A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip position. The Lagrangian principle is utilized to model the dynamic function of the single-degree flexible manipulator incorporating the assumed modes method. Simulation results of the fuzzy adaptive control method in the location control and the trajectory tracking with different tip disturbances are presented and compared with the results of the classic PD control. It shows that the controller can obtain the stable and robust performance.
基金supported by Beijing Natural Science Foundation (No.4164091)China Postdoctoral Science Foundation (No.2015M580048)+2 种基金Fundamental Research Funds for the Central Universities (No.FRF-TP-15034A1)National Natural Science Foundation of China (No.61672093,61432004)National Key Research and Development Plan(2016YFB1001404)
文摘This paper proposes a continuous cognitive emotional regulation model for robot in the case of external emotional stimulus from interactive person's expressions. It integrates a guiding cognitive reappraisal strategy into the HMM(Hidden Markov Model) emotional interactive model for empathizing between robot and person. The emotion is considered as a source in the 3D space(Arousal, Valence, and Stance). State transition and emotion intensity can be quantitatively analyzed in the continuous space. This cognition-emotion interactive model have been verified by the expression and behavior robot. Empathizing is the main distinguishing feature of our work, and it is realized by the emotional regulation which operated in a continuous 3D emotional space enabling a wide range of intermediate emotions. The experiment results provide evidence with acceptability, accuracy, richness, fluency, interestingness, friendliness and exaggeration that the robot with cognition and emotional control ability could be better accepted in the human-robot interaction(HRI).
基金supported by the National Natural Science Foundation of China(Nos.51875287, 52075250)the Special Fund for Transformation of Scientific,and Technological Achievements of Jiangsu Province(No.BA2018053)
文摘The existing kinematic parameter calibration method cannot further improve the absolute positioning accuracy of the robot due to the uncertainty of positioning error caused by robot joint backlash.In view of this problem,a closed‑loop feedback accuracy compensation method for robot joints was proposed.Firstly,a Chebyshev polynomial error estimation model was established which took geometric error and non‑geometric error into account.In addition,the absolute linear grating scale was installed at each joint of the robot and the positioning error of the robot end was mapped to the joint angle.And the joint angle corrected value was obtained.Furthermore,the closed‑loop feedback of robot joints was established to realize the online correction of the positioning error.Finally,an experiment on the KUKA KR210 industrial robot was conducted to demonstrate the effectiveness of the method.The result shows that the maximum absolute positioning error of the robot is reduced by 75%from 0.76 mm to 0.19 mm.This method can compensate the robot joint backlash effectively and further improve the absolute positioning accuracy of the robot.
文摘This paper sets up a robotic manipulator model on slewing crane. The model can synthetically describe the dynamic behavior of the load of slewing crane in rotating, elevating and hoisting motions. The dynamic equations of the system are recursively derived by a Newton Euler method. The dynamic behavior of the load of slewing crane in rotating motion is simulated on a computer. The method of robotic dynamics to derive the dynamic equations of the swing of load is accurate and convenient and it has good regularity. The result of the study provides a base in theory on design of crane and an accurate mathematical model for controlling the swing of load.
