Humans can quickly perform adaptive grasping of soft objects by using visual perception and judgment of the grasping angle,which helps prevent the objects from sliding or deforming excessively.However,this easy task r...Humans can quickly perform adaptive grasping of soft objects by using visual perception and judgment of the grasping angle,which helps prevent the objects from sliding or deforming excessively.However,this easy task remains a challenge for robots.The grasping states of soft objects can be categorized into four types:sliding,appropriate,excessive and extreme.Effective recognition of different states is crucial for achieving adaptive grasping of soft objects.To address this problem,a novel visual-curvature fusion network based on YOLOv8(VCFN-YOLOv8)is proposed to evaluate the grasping state of various soft objects.In this framework,the robotic arm equipped with the wrist camera and the curvature sensor is established to perform generalization grasping and lifting experiments on 11 different objects.Meanwhile,the dataset is built for training and testing the proposed method.The results show a classification accuracy of 99.51% on four different grasping states.A series of grasping evaluation experiments is conducted based on the proposed framework,along with tests for the model's generality.The experiment results demonstrate that VCFN-YOLOv8 is accurate and efficient in evaluating the grasping state of soft objects and shows a certain degree of generalization for non-soft objects.It can be widely applied in fields such as automatic control,adaptive grasping and surgical robot.展开更多
Currently,numerous biomimetic robots inspired by natural biological systems have been developed.However,creating soft robots with versatile locomotion modes remains a significant challenge.Snakes,as invertebrate repti...Currently,numerous biomimetic robots inspired by natural biological systems have been developed.However,creating soft robots with versatile locomotion modes remains a significant challenge.Snakes,as invertebrate reptiles,exhibit diverse and powerful locomotion abilities,including prey constriction,sidewinding,accordion locomotion,and winding climbing,making them a focus of robotics research.In this study,we present a snake-inspired soft robot with an initial coiling structure,fabricated using MXene-cellulose nanofiber ink printed on pre-expanded polyethylene film through direct ink writing technology.The controllable fabrication of initial coiling structure soft robot(ICSBot)has been achieved through theoretical calculations and finite element analysis to predict and analyze the initial structure of ICSBot,and programmable ICSBot has been designed and fabricated.This robot functions as a coiling gripper capable of grasping objects with complex shapes under near infrared light stimulation.Additionally,it demonstrates multi-modal crawling locomotion in various environments,including confined spaces,unstructured terrains,and both inside and outside tubes.These results offer a novel strategy for designing and fabricating coiling-structured soft robots and highlight their potential applications in smart and multifunctional robotics.展开更多
The“visual perception+hand-eye transformation+motion planning”paradigm of robotic coordination grasping has demonstrated feasibility in unstructured scenes such as logistics.However,further developments in handling ...The“visual perception+hand-eye transformation+motion planning”paradigm of robotic coordination grasping has demonstrated feasibility in unstructured scenes such as logistics.However,further developments in handling complex and dynamic environments remain challenging.To address the issue of unknown targets requiring immediate deployment for grasping tasks,this paper proposes a novel hand-eye coordinated method for progressive grasping guided by the texture keypoints of the target.First,we develop an efficient system for acquiring texture-matching templates and an estimation algorithm for the feature region that filters the precisely registered texture feature points of the target.Then,we integrate optical flow estimation to update and track the robust texture region in real time,and design a feature-based servo grasping controller to map the optical flow points of the high-registration texture region to the robot joint velocities for precise tracking.Finally,we impose spatiotemporal constraints on the planned trajectory and decouple the target motion,to achieve progressive approach and rotationally invariant grasping for both dynamic and static targets.Comprehensive experiments demonstrate that this tracking grasping method exhibits a low latency,a high precision,and robustness in complex scenarios and dynamic disturbances,with an average position accuracy of approximately 5 mm,a rotation accuracy of approximately 0.02,and an overall grasping success rate of approximately 90%.展开更多
Robot grasp detection is a fundamental vision task for robots.Deep learning-based methods have shown excellent results in enhancing the grasp detection capabilities for model-free objects in unstructured scenes.Most p...Robot grasp detection is a fundamental vision task for robots.Deep learning-based methods have shown excellent results in enhancing the grasp detection capabilities for model-free objects in unstructured scenes.Most popular approaches explore deep network models and exploit RGB-D images combining colour and depth data to acquire enriched feature expressions.However,current work struggles to achieve a satisfactory balance between the accuracy and real-time performance;the variability of RGB and depth feature distributions receives inadequate attention.The treatment of predicted failure cases is also lacking.We propose an efficient fully convolutional network to predict the pixel-level antipodal grasp parameters in RGB-D images.A structure with hierarchical feature fusion is established using multiple lightweight feature extraction blocks.The feature fusion module with 3D global attention is used to select the complementary information in RGB and depth images suficiently.Additionally,a grasp configuration optimization method based on local grasp path is proposed to cope with the possible failures predicted by the model.Extensive experiments on two public grasping datasets,Cornell and Jacquard,demonstrate that the approach can improve the performance of grasping unknown objects.展开更多
Grasping is one of the most fundamental operations in modern robotics applications.While deep rein-forcement learning(DRL)has demonstrated strong potential in robotics,there is too much emphasis on maximizing the cumu...Grasping is one of the most fundamental operations in modern robotics applications.While deep rein-forcement learning(DRL)has demonstrated strong potential in robotics,there is too much emphasis on maximizing the cumulative reward in executing tasks,and the potential safety risks are often ignored.In this paper,an optimization method based on safe reinforcement learning(Safe RL)is proposed to address the robotic grasping problem under safety constraints.Specifically,considering the obstacle avoidance constraints of the system,the grasping problem of the manipulator is modeled as a Constrained Markov Decision Process(CMDP).The Lagrange multiplier and a dynamic weighted mechanism are introduced into the Proximal Policy Optimization(PPO)framework,leading to the development of the dynamic weighted Lagrange PPO(DWL-PPO)algorithm.The behavior of violating safety constraints is punished while the policy is optimized in this proposed method.In addition,the orientation control of the end-effector is included in the reward function,and a compound reward function adapted to changes in pose is designed.Ultimately,the efficacy and advantages of the suggested method are proved by extensive training and testing in the Pybullet simulator.The results of grasping experiments reveal that the recommended approach provides superior safety and efficiency compared with other advanced RL methods and achieves a good trade-off between model learning and risk aversion.展开更多
Research of capture mechanisms with strong capture adaptability and stable grasp is important to solve the problem of launch and recovery of torpedo-shaped autonomous underwater vehicles(AUVs).A multi-loop coupling ca...Research of capture mechanisms with strong capture adaptability and stable grasp is important to solve the problem of launch and recovery of torpedo-shaped autonomous underwater vehicles(AUVs).A multi-loop coupling capture mechanism with strong adaptability and high retraction rate has been proposed for the launch and recovery of torpedo-shaped AUVs with different morphological features.Firstly,the principle of capturing motion retraction is described based on the appearance characteristics of torpedo-shaped AUVs,and the configuration synthesis of the capture mechanism is carried out using the method of constrained chain synthesis.Secondly,the screw theory is employed to analyze the degree of freedom(DoF)of the capture mechanism.Then,the 3D model of the capture mechanism is established,and the kinematics and dynamics simulations are carried out.Combined with the capture orientation requirements of the capture mechanism,the statics and vibration characteristics analyses are carried out.Furthermore,considering the capture process and the underwater working environment,the motion characteristics and hydraulics characteristics of the capture mechanism are analyzed.Finally,a principle prototype is developed and the torpedo-shaped AUVs capture experiment is completed.The work provides technical reserves for the research and development of AUV capture special equipment.展开更多
Soft grippers have great potential applications in daily life,since they can compliantly grasp soft and delicate objects.However,the highly elastic fingers of most soft grippers are prone to separate from each other w...Soft grippers have great potential applications in daily life,since they can compliantly grasp soft and delicate objects.However,the highly elastic fingers of most soft grippers are prone to separate from each other while grasping objects due to their low stiffness,thus reducing the grasping stability and load-bearing capacity.To tackle this problem,inspired from the venus flytrap plant,this work proposes a mutual-hook mechanism to restrain the separation and improve the grasping performance of soft fingers.The novel soft gripper design consists of three modules,a soft finger-cot,two Soft Hook Actuators(SHAs)and two sliding mechanisms.Here,the soft finger-cot covers on the soft finger,increasing the contact area with the target object,two SHAs are fixed to the left and right sides of the finger-cot,and the sliding mechanisms are designed to make SHAs stretch flexibly.Experiments demonstrate that the proposed design can restrain the separation of soft fingers substantially,and the soft fingers with the finger-cots can grasp objects three times heavier than the soft fingers without the proposed design.The proposed design can provide invaluable insights for soft fingers to restrain the separation while grasping,thus improving the grasping stability and the load-bearing capacity.展开更多
With the rapid development of robotics,grasp prediction has become fundamental to achieving intelligent physical interactions.To enhance grasp detection accuracy in unstructured environments,we propose a novel Cross-M...With the rapid development of robotics,grasp prediction has become fundamental to achieving intelligent physical interactions.To enhance grasp detection accuracy in unstructured environments,we propose a novel Cross-Multiscale Adaptive Collaborative and Fusion Grasp Detection Network(CMACF-Net).Addressing the limitations of conventional methods in capturing multi-scale spatial features,CMACF-Net introduces the Quantized Multi-scale Global Attention Module(QMGAM),which enables precise multi-scale spatial calibration and adaptive spatial-channel interaction,ultimately yielding a more robust and discriminative feature representation.To reduce the degradation of local features and the loss of high-frequency information,the Cross-scale Context Integration Module(CCI)is employed to facilitate the effective fusion and alignment of global context and local details.Furthermore,an Efficient Up-Convolution Block(EUCB)is integrated into a U-Net architecture to effectively restore spatial details lost during the downsampling process,while simultaneously preserving computational efficiency.Extensive evaluations demonstrate that CMACF-Net achieves state-of-the-art detection accuracies of 98.9% and 95.9% on the Cornell and Jacquard datasets,respectively.Additionally,real-time grasping experiments on the RM65-B robotic platform validate the framework’s robustness and generalization capability,underscoring its applicability to real-world robotic manipulation scenarios.展开更多
“Multidimensional international world”refers to understanding the world through multiple dimensions beyond traditional economic or political measures,fostering cross-cultural collaboration,and creating systems that ...“Multidimensional international world”refers to understanding the world through multiple dimensions beyond traditional economic or political measures,fostering cross-cultural collaboration,and creating systems that balance global integration with local needs.This also includes management of global business operations across diverse cultures in a multipolar international landscape.The paper briefs the developed and already tested in numerous applications high-level Spatial Grasp Model and Technology(SGT),which can help investigate and manage complex systems with a holistic spatial approach effectively covering various physical and virtual dimensions,their interrelations,and integration as a whole.Different areas will be investigated with examples of practical solutions in them and their combinations in a high-level Spatial Grasp Language(SGL),the key element of SGT.This allows for the creation and distributed management of very large spatial networks with different orientation which can be self-spreading,self-analyzing,self-modifying,and self-recovering in complex terrestrial and celestial environments,and also organize dynamic multi-networking solutions supporting global evolution and integrity.展开更多
The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level m...The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.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
When the space robot captures a floating target, contact impact occurs inevitably and frequently between the manipulator hand and the target, which seriously impacts the position and attitude of the robot and grasping...When the space robot captures a floating target, contact impact occurs inevitably and frequently between the manipulator hand and the target, which seriously impacts the position and attitude of the robot and grasping security. ＂Dynamic grasping area＂ is introduced to describe the collision process of manipulator grasping target, and grasping area control equation is established. By analyzing the impact of grasping control parameters, base and target mass on the grasping process and combining the life experience, it is found that if the product of speed control parameter and dB adjustment parameter is close to but smaller than the minimum grasping speed, collision impact in the grasping process could be reduced greatly, and then an ideal grasping strategy is proposed. Simulation results indicate that during the same period, the strategy grasping is superior to the accelerating grasping, in that the amplitude of impact force is reduced to 20%, and the attitude control torque is reduced to 15%, and the impact on the robot is eliminated significantly. The results would have important academic value and engineering significance.展开更多
Endoscopic submucosal dissection(ESD) has allowed the achievement of histologically curative en bloc resection of gastrointestinal neoplasms regardless of size,permitting the resection of previously non-resectable tum...Endoscopic submucosal dissection(ESD) has allowed the achievement of histologically curative en bloc resection of gastrointestinal neoplasms regardless of size,permitting the resection of previously non-resectable tumors.The ESD technique for treatment of early gastric cancer has spread rapidly in Japan and a few other Asian countries due to its excellent eradication rate compared to endoscopic mucosal resection.Although numerous electrosurgical knives have been developed for ESD,technical difficulties and high complication rates(bleeding and perforation) have limited their use worldwide.We developed the grasping type scissor forceps(GSF) to resolve such ESD-related problems.Our animal and preliminary clinical studies showed that ESD using GSF is a safe(no intraoperative complication) and technically efficient(curative en bloc resection rate 92%) method for dissection of early gastrointestinal tumors.The use of GSF is a promising option for performing ESD on early stage GI tract tumors both safely and effectively.展开更多
It is important for robotic hands to obtain optimal grasping performance inthe meanwhile balancing external forces and maintaining grasp stability. The problem of forceoptimization of grasping is solved in the space o...It is important for robotic hands to obtain optimal grasping performance inthe meanwhile balancing external forces and maintaining grasp stability. The problem of forceoptimization of grasping is solved in the space of joint torques. A measure of grasping performanceis presented to protect joint actuators from working in heavy payloads. The joint torques arecalculated for the optimal performance under the frictional constraints and the physical limits ofmotor outputs. By formulating the grasping forces into the explicit function of joint torques, thefrictional constraints imposed on the grasping forces are transformed into the constraints on jointtorques. Without further simplification, the nonlinear frictional constraints can be simply handledin the process of optimization. Two numerical examples demonstrate the simplicity and effectivenessof the approach.展开更多
Grasping is a significant yet challenging task for the robots. In this paper, the grasping problem for a class of dexterous robotic hands is investigated based on the novel concept of constrained region in environment...Grasping is a significant yet challenging task for the robots. In this paper, the grasping problem for a class of dexterous robotic hands is investigated based on the novel concept of constrained region in environment, which is inspired by the grasping operations of the human beings. More precisely, constrained region in environment is formed by the environment, which integrates a bio-inspired co-sensing framework. By utilizing the concept of constrained region in environment, the grasping by robots can be effectively accomplished with relatively low-precision sensors. For the grasping of dexterous robotic hands, the attractive region in environment is first established by model primitives in the configuration space to generate offline grasping planning. Then, online dynamic adjustment is implemented by integrating the visual sensory and force sensory information, such that the uncertainty can be further eliminated and certain compliance can be obtained. In the end, an experimental example of BarrettHand is provided to show the effectiveness of our proposed grasping strategy based on constrained region in environment.展开更多
The stable grasping gesture of a novel cable-driven robotic hand is analyzed. The robotic hand is underactuated, using tendon-pulley transmission and a parallel four-linkage mechanism to realize grasp. The structure d...The stable grasping gesture of a novel cable-driven robotic hand is analyzed. The robotic hand is underactuated, using tendon-pulley transmission and a parallel four-linkage mechanism to realize grasp. The structure design and a basic grasping strategy of one finger was introduced. According to the established round object enveloping grasp model, the relationship between the contacting and driving forces in a finger and stable grasping conditions were expounded. A method of interpolation and iteration was proposed to obtain the stable grasping gesture of the cable-driven hand grasping a round target. Quasi-statics analysis in ADAMS validated the variation of grasping forces, which illustrated the feasibility and validity of the proposed analytical method. Three basic types of grasping gestures of the underactuated hand were obtained on the basis of the relationship between the contact forces and position of a grasped object.展开更多
基金supported by the Fundamental Research Project of Shanxi Province(202403021211229).
文摘Humans can quickly perform adaptive grasping of soft objects by using visual perception and judgment of the grasping angle,which helps prevent the objects from sliding or deforming excessively.However,this easy task remains a challenge for robots.The grasping states of soft objects can be categorized into four types:sliding,appropriate,excessive and extreme.Effective recognition of different states is crucial for achieving adaptive grasping of soft objects.To address this problem,a novel visual-curvature fusion network based on YOLOv8(VCFN-YOLOv8)is proposed to evaluate the grasping state of various soft objects.In this framework,the robotic arm equipped with the wrist camera and the curvature sensor is established to perform generalization grasping and lifting experiments on 11 different objects.Meanwhile,the dataset is built for training and testing the proposed method.The results show a classification accuracy of 99.51% on four different grasping states.A series of grasping evaluation experiments is conducted based on the proposed framework,along with tests for the model's generality.The experiment results demonstrate that VCFN-YOLOv8 is accurate and efficient in evaluating the grasping state of soft objects and shows a certain degree of generalization for non-soft objects.It can be widely applied in fields such as automatic control,adaptive grasping and surgical robot.
基金supported by the National Key R&D Program of China(NO.2024YFB3409900)the China Postdoctoral Science Foundation(NO.2023M730845)the Heilongjiang Postdoctoral Fund(NO.LBH-Z23182)。
文摘Currently,numerous biomimetic robots inspired by natural biological systems have been developed.However,creating soft robots with versatile locomotion modes remains a significant challenge.Snakes,as invertebrate reptiles,exhibit diverse and powerful locomotion abilities,including prey constriction,sidewinding,accordion locomotion,and winding climbing,making them a focus of robotics research.In this study,we present a snake-inspired soft robot with an initial coiling structure,fabricated using MXene-cellulose nanofiber ink printed on pre-expanded polyethylene film through direct ink writing technology.The controllable fabrication of initial coiling structure soft robot(ICSBot)has been achieved through theoretical calculations and finite element analysis to predict and analyze the initial structure of ICSBot,and programmable ICSBot has been designed and fabricated.This robot functions as a coiling gripper capable of grasping objects with complex shapes under near infrared light stimulation.Additionally,it demonstrates multi-modal crawling locomotion in various environments,including confined spaces,unstructured terrains,and both inside and outside tubes.These results offer a novel strategy for designing and fabricating coiling-structured soft robots and highlight their potential applications in smart and multifunctional robotics.
基金Supported by National Key R&D Program of China(Grant No.2024YFB4709800)Fundamental Research Funds for the Central Universities。
文摘The“visual perception+hand-eye transformation+motion planning”paradigm of robotic coordination grasping has demonstrated feasibility in unstructured scenes such as logistics.However,further developments in handling complex and dynamic environments remain challenging.To address the issue of unknown targets requiring immediate deployment for grasping tasks,this paper proposes a novel hand-eye coordinated method for progressive grasping guided by the texture keypoints of the target.First,we develop an efficient system for acquiring texture-matching templates and an estimation algorithm for the feature region that filters the precisely registered texture feature points of the target.Then,we integrate optical flow estimation to update and track the robust texture region in real time,and design a feature-based servo grasping controller to map the optical flow points of the high-registration texture region to the robot joint velocities for precise tracking.Finally,we impose spatiotemporal constraints on the planned trajectory and decouple the target motion,to achieve progressive approach and rotationally invariant grasping for both dynamic and static targets.Comprehensive experiments demonstrate that this tracking grasping method exhibits a low latency,a high precision,and robustness in complex scenarios and dynamic disturbances,with an average position accuracy of approximately 5 mm,a rotation accuracy of approximately 0.02,and an overall grasping success rate of approximately 90%.
基金the National Natural Science Foundation of China(No.62173230)the Program of Science and Technology Commission of Shanghai Municipality(No.22511101400)。
文摘Robot grasp detection is a fundamental vision task for robots.Deep learning-based methods have shown excellent results in enhancing the grasp detection capabilities for model-free objects in unstructured scenes.Most popular approaches explore deep network models and exploit RGB-D images combining colour and depth data to acquire enriched feature expressions.However,current work struggles to achieve a satisfactory balance between the accuracy and real-time performance;the variability of RGB and depth feature distributions receives inadequate attention.The treatment of predicted failure cases is also lacking.We propose an efficient fully convolutional network to predict the pixel-level antipodal grasp parameters in RGB-D images.A structure with hierarchical feature fusion is established using multiple lightweight feature extraction blocks.The feature fusion module with 3D global attention is used to select the complementary information in RGB and depth images suficiently.Additionally,a grasp configuration optimization method based on local grasp path is proposed to cope with the possible failures predicted by the model.Extensive experiments on two public grasping datasets,Cornell and Jacquard,demonstrate that the approach can improve the performance of grasping unknown objects.
文摘Grasping is one of the most fundamental operations in modern robotics applications.While deep rein-forcement learning(DRL)has demonstrated strong potential in robotics,there is too much emphasis on maximizing the cumulative reward in executing tasks,and the potential safety risks are often ignored.In this paper,an optimization method based on safe reinforcement learning(Safe RL)is proposed to address the robotic grasping problem under safety constraints.Specifically,considering the obstacle avoidance constraints of the system,the grasping problem of the manipulator is modeled as a Constrained Markov Decision Process(CMDP).The Lagrange multiplier and a dynamic weighted mechanism are introduced into the Proximal Policy Optimization(PPO)framework,leading to the development of the dynamic weighted Lagrange PPO(DWL-PPO)algorithm.The behavior of violating safety constraints is punished while the policy is optimized in this proposed method.In addition,the orientation control of the end-effector is included in the reward function,and a compound reward function adapted to changes in pose is designed.Ultimately,the efficacy and advantages of the suggested method are proved by extensive training and testing in the Pybullet simulator.The results of grasping experiments reveal that the recommended approach provides superior safety and efficiency compared with other advanced RL methods and achieves a good trade-off between model learning and risk aversion.
基金supported by the Natural Science Foundation of Jiangsu Province of China(Grant No.BK20220649)the Natural Science Foundation of the Jiangsu Higher Education Institutions(Grant No.23KJB460010)+1 种基金the Key R&D Program of Jiangsu Province(Grant No.BE2022062)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.SJCX23_2143).
文摘Research of capture mechanisms with strong capture adaptability and stable grasp is important to solve the problem of launch and recovery of torpedo-shaped autonomous underwater vehicles(AUVs).A multi-loop coupling capture mechanism with strong adaptability and high retraction rate has been proposed for the launch and recovery of torpedo-shaped AUVs with different morphological features.Firstly,the principle of capturing motion retraction is described based on the appearance characteristics of torpedo-shaped AUVs,and the configuration synthesis of the capture mechanism is carried out using the method of constrained chain synthesis.Secondly,the screw theory is employed to analyze the degree of freedom(DoF)of the capture mechanism.Then,the 3D model of the capture mechanism is established,and the kinematics and dynamics simulations are carried out.Combined with the capture orientation requirements of the capture mechanism,the statics and vibration characteristics analyses are carried out.Furthermore,considering the capture process and the underwater working environment,the motion characteristics and hydraulics characteristics of the capture mechanism are analyzed.Finally,a principle prototype is developed and the torpedo-shaped AUVs capture experiment is completed.The work provides technical reserves for the research and development of AUV capture special equipment.
基金funded by the National Natural Science Foundation of China under Grant 62073305 and the Natural Science Foundation of Hubei Province under Grant 2022CFA041.
文摘Soft grippers have great potential applications in daily life,since they can compliantly grasp soft and delicate objects.However,the highly elastic fingers of most soft grippers are prone to separate from each other while grasping objects due to their low stiffness,thus reducing the grasping stability and load-bearing capacity.To tackle this problem,inspired from the venus flytrap plant,this work proposes a mutual-hook mechanism to restrain the separation and improve the grasping performance of soft fingers.The novel soft gripper design consists of three modules,a soft finger-cot,two Soft Hook Actuators(SHAs)and two sliding mechanisms.Here,the soft finger-cot covers on the soft finger,increasing the contact area with the target object,two SHAs are fixed to the left and right sides of the finger-cot,and the sliding mechanisms are designed to make SHAs stretch flexibly.Experiments demonstrate that the proposed design can restrain the separation of soft fingers substantially,and the soft fingers with the finger-cots can grasp objects three times heavier than the soft fingers without the proposed design.The proposed design can provide invaluable insights for soft fingers to restrain the separation while grasping,thus improving the grasping stability and the load-bearing capacity.
基金supported by the Jiangxi Provincial Natural Science Foundation(No.20232BAB202027)the National Natural Science Foundation of China(No.62367006)the Natural Science Foundation of Hubei Province of China(No.2022CFB536).
文摘With the rapid development of robotics,grasp prediction has become fundamental to achieving intelligent physical interactions.To enhance grasp detection accuracy in unstructured environments,we propose a novel Cross-Multiscale Adaptive Collaborative and Fusion Grasp Detection Network(CMACF-Net).Addressing the limitations of conventional methods in capturing multi-scale spatial features,CMACF-Net introduces the Quantized Multi-scale Global Attention Module(QMGAM),which enables precise multi-scale spatial calibration and adaptive spatial-channel interaction,ultimately yielding a more robust and discriminative feature representation.To reduce the degradation of local features and the loss of high-frequency information,the Cross-scale Context Integration Module(CCI)is employed to facilitate the effective fusion and alignment of global context and local details.Furthermore,an Efficient Up-Convolution Block(EUCB)is integrated into a U-Net architecture to effectively restore spatial details lost during the downsampling process,while simultaneously preserving computational efficiency.Extensive evaluations demonstrate that CMACF-Net achieves state-of-the-art detection accuracies of 98.9% and 95.9% on the Cornell and Jacquard datasets,respectively.Additionally,real-time grasping experiments on the RM65-B robotic platform validate the framework’s robustness and generalization capability,underscoring its applicability to real-world robotic manipulation scenarios.
文摘“Multidimensional international world”refers to understanding the world through multiple dimensions beyond traditional economic or political measures,fostering cross-cultural collaboration,and creating systems that balance global integration with local needs.This also includes management of global business operations across diverse cultures in a multipolar international landscape.The paper briefs the developed and already tested in numerous applications high-level Spatial Grasp Model and Technology(SGT),which can help investigate and manage complex systems with a holistic spatial approach effectively covering various physical and virtual dimensions,their interrelations,and integration as a whole.Different areas will be investigated with examples of practical solutions in them and their combinations in a high-level Spatial Grasp Language(SGL),the key element of SGT.This allows for the creation and distributed management of very large spatial networks with different orientation which can be self-spreading,self-analyzing,self-modifying,and self-recovering in complex terrestrial and celestial environments,and also organize dynamic multi-networking solutions supporting global evolution and integrity.
文摘The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.
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Program for Innovative Research Team in University(IRT520)CAST of China (20090703)
文摘When the space robot captures a floating target, contact impact occurs inevitably and frequently between the manipulator hand and the target, which seriously impacts the position and attitude of the robot and grasping security. ＂Dynamic grasping area＂ is introduced to describe the collision process of manipulator grasping target, and grasping area control equation is established. By analyzing the impact of grasping control parameters, base and target mass on the grasping process and combining the life experience, it is found that if the product of speed control parameter and dB adjustment parameter is close to but smaller than the minimum grasping speed, collision impact in the grasping process could be reduced greatly, and then an ideal grasping strategy is proposed. Simulation results indicate that during the same period, the strategy grasping is superior to the accelerating grasping, in that the amplitude of impact force is reduced to 20%, and the attitude control torque is reduced to 15%, and the impact on the robot is eliminated significantly. The results would have important academic value and engineering significance.
文摘Endoscopic submucosal dissection(ESD) has allowed the achievement of histologically curative en bloc resection of gastrointestinal neoplasms regardless of size,permitting the resection of previously non-resectable tumors.The ESD technique for treatment of early gastric cancer has spread rapidly in Japan and a few other Asian countries due to its excellent eradication rate compared to endoscopic mucosal resection.Although numerous electrosurgical knives have been developed for ESD,technical difficulties and high complication rates(bleeding and perforation) have limited their use worldwide.We developed the grasping type scissor forceps(GSF) to resolve such ESD-related problems.Our animal and preliminary clinical studies showed that ESD using GSF is a safe(no intraoperative complication) and technically efficient(curative en bloc resection rate 92%) method for dissection of early gastrointestinal tumors.The use of GSF is a promising option for performing ESD on early stage GI tract tumors both safely and effectively.
基金This project is supported by National Natural Science Foundation of China (No.59985001)Doctoral Grant of Education Ministry of China (No.2000000605)
文摘It is important for robotic hands to obtain optimal grasping performance inthe meanwhile balancing external forces and maintaining grasp stability. The problem of forceoptimization of grasping is solved in the space of joint torques. A measure of grasping performanceis presented to protect joint actuators from working in heavy payloads. The joint torques arecalculated for the optimal performance under the frictional constraints and the physical limits ofmotor outputs. By formulating the grasping forces into the explicit function of joint torques, thefrictional constraints imposed on the grasping forces are transformed into the constraints on jointtorques. Without further simplification, the nonlinear frictional constraints can be simply handledin the process of optimization. Two numerical examples demonstrate the simplicity and effectivenessof the approach.
基金supported by National Natural Science Foundation of China(No.61210009)Beijing Municipal Science and Technology(Nos.D16110400140000 and D161100001416001)+1 种基金Fundamental Research Funds for the Central Universities(No.FRF-TP-15-115A1)the Strategic Priority Research Program of the CAS(No.XDB02080003)
文摘Grasping is a significant yet challenging task for the robots. In this paper, the grasping problem for a class of dexterous robotic hands is investigated based on the novel concept of constrained region in environment, which is inspired by the grasping operations of the human beings. More precisely, constrained region in environment is formed by the environment, which integrates a bio-inspired co-sensing framework. By utilizing the concept of constrained region in environment, the grasping by robots can be effectively accomplished with relatively low-precision sensors. For the grasping of dexterous robotic hands, the attractive region in environment is first established by model primitives in the configuration space to generate offline grasping planning. Then, online dynamic adjustment is implemented by integrating the visual sensory and force sensory information, such that the uncertainty can be further eliminated and certain compliance can be obtained. In the end, an experimental example of BarrettHand is provided to show the effectiveness of our proposed grasping strategy based on constrained region in environment.
基金The National Natural Science Foundation of China(No.U1613201,51275107)Shenzhen Research Funds(No.JCYJ20170413104438332)
文摘The stable grasping gesture of a novel cable-driven robotic hand is analyzed. The robotic hand is underactuated, using tendon-pulley transmission and a parallel four-linkage mechanism to realize grasp. The structure design and a basic grasping strategy of one finger was introduced. According to the established round object enveloping grasp model, the relationship between the contacting and driving forces in a finger and stable grasping conditions were expounded. A method of interpolation and iteration was proposed to obtain the stable grasping gesture of the cable-driven hand grasping a round target. Quasi-statics analysis in ADAMS validated the variation of grasping forces, which illustrated the feasibility and validity of the proposed analytical method. Three basic types of grasping gestures of the underactuated hand were obtained on the basis of the relationship between the contact forces and position of a grasped object.
