We proved a new necessary and sufficient condition for 2D three finger equilibrium grasps and implemented an geometrical algorithm for computing force closure grasps of arbitrary 2D objects in this article. The algori...We proved a new necessary and sufficient condition for 2D three finger equilibrium grasps and implemented an geometrical algorithm for computing force closure grasps of arbitrary 2D objects in this article. The algorithm is quite simple and only needs some algebraic calculations. Finally, we implemented the algorithm and confirmed its usefulness by an example.展开更多
Stability is a significant property for a robot hand grasp to perform complextasks similar to human hands. The common method to investigate the stability of roboticmulti-fingered grasp system is Lyapunov direct method...Stability is a significant property for a robot hand grasp to perform complextasks similar to human hands. The common method to investigate the stability of roboticmulti-fingered grasp system is Lyapunov direct method, but usually it is rather difficult toconstruct a proper Lyapunov function. Avoiding the hard work of constructing a Lyapunov function, wepropose the sufficient conditions for stability of the robotic grasp system.展开更多
This research characterizes grasping by multifingered robot hands through investiga- tion of the space of contact forces into four subspaces , a method is developed to determine the di- mensions of the subspaces with ...This research characterizes grasping by multifingered robot hands through investiga- tion of the space of contact forces into four subspaces , a method is developed to determine the di- mensions of the subspaces with respect to the connectivity of the object. The relationship reveals the differences between three types of grasps classified and indicates how the contact force can be decomposed corresponding to each type of grasp. The subspaces and the determination of their di- mensions are illlustrated by examples.展开更多
This paper deals with the problem of force-closure analysis for soft multi-fingered grasps. The first step is the study of the relationship between the external wrench space and the manipulation force space at any con...This paper deals with the problem of force-closure analysis for soft multi-fingered grasps. The first step is the study of the relationship between the external wrench space and the manipulation force space at any contact. Constraint force set, strictly constraint force set and normal force set are defined in the contact force space, followed by an investigation of their relationships. Based on the convexity of the friction constraints for soft finger contact, the necessary and sufficient conditions for force-closure grasps are derived. Accordingly an efficient algorithm for testing force-closure is presented. Some illustrative examples are given.展开更多
Deep learning has become integral to robotics,particularly in tasks such as robotic grasping,where objects often exhibit diverse shapes,textures,and physical properties.In robotic grasping tasks,due to the diverse cha...Deep learning has become integral to robotics,particularly in tasks such as robotic grasping,where objects often exhibit diverse shapes,textures,and physical properties.In robotic grasping tasks,due to the diverse characteristics of the targets,frequent adjustments to the network architecture and parameters are required to avoid a decrease in model accuracy,which presents a significant challenge for non-experts.Neural Architecture Search(NAS)provides a compelling method through the automated generation of network architectures,enabling the discovery of models that achieve high accuracy through efficient search algorithms.Compared to manually designed networks,NAS methods can significantly reduce design costs,time expenditure,and improve model performance.However,such methods often involve complex topological connections,and these redundant structures can severely reduce computational efficiency.To overcome this challenge,this work puts forward a robotic grasp detection framework founded on NAS.The method automatically designs a lightweight network with high accuracy and low topological complexity,effectively adapting to the target object to generate the optimal grasp pose,thereby significantly improving the success rate of robotic grasping.Additionally,we use Class Activation Mapping(CAM)as an interpretability tool,which captures sensitive information during the perception process through visualized results.The searched model achieved competitive,and in some cases superior,performance on the Cornell and Jacquard public datasets,achieving accuracies of 98.3%and 96.8%,respectively,while sustaining a detection speed of 89 frames per second with only 0.41 million parameters.To further validate its effectiveness beyond benchmark evaluations,we conducted real-world grasping experiments on a UR5 robotic arm,where the model demonstrated reliable performance across diverse objects and high grasp success rates,thereby confirming its practical applicability in robotic manipulation tasks.展开更多
Soft grippers research is gaining increasing attention for their flexibility.However,the conventional soft gripper primar-ily focuses on soft fingers,without considering the palm.This makes grasping forces concentrate...Soft grippers research is gaining increasing attention for their flexibility.However,the conventional soft gripper primar-ily focuses on soft fingers,without considering the palm.This makes grasping forces concentrated in the fingertip areas,resulting in objects being prone to damage and instability during handling,especially for delicate items.Additionally,pre-transportation classification faces challenges:tactile methods are complex,visual methods are environment-sensitive,and both struggle with similar objects.To address these problems,inspired by the human hand's transition between finger grasp and palm support and the lotus's hierarchical structure,this paper proposes a dual-layer gripper,named IOSGrip-per.It features four pneumatic soft fingers and a rotational soft-rigid palm.Through coordinated control of the fingers and palm,it transitions concentrated fingertip squeeze force to distributed palm support force,reducing squeeze force and squeeze duration.Moreover,it integrates a range sensor and four load cells,enabling stable and accurate measurements of the object's height and weight.Furthermore,a classifier is developed based on K-nearest neighbor algorithm,allowing real-time object classification.Experiments demonstrate that compared to only using soft fingers,the IOSGripper signifi-cantly reduces the squeeze force on the objects(with 0 N squeeze force during palm support)and damage on the delicate object,while improving grasping stability.Its height and weight measurement errors are within 2 mm and 1 g,respectively.And it achieves high accuracy in three test scenarios,including classifying similar objects.This study provides useful insights for the design of soft grippers capable of human-like grasping and sorting tasks.展开更多
This paper presents an approach to algebraic detection of relative form closure for a multi-fingered grasp G and gives an attention to the classification of relative form closures.Whether or not a grasp G is of relati...This paper presents an approach to algebraic detection of relative form closure for a multi-fingered grasp G and gives an attention to the classification of relative form closures.Whether or not a grasp G is of relative form closure has been verified by the geometric criterion 0?rintC[G](Xiong Y L,Xiong X R.Algebraic structure and geometric interpretation of rigid complex fixture system.IEEE Trans Autom Sci Eng,2007,4:252–264;Xiong Y L.Theory of point contact restraint and qualitative analysis of robot grasping.Sci China Ser A-Math,1994,37:629–640).Our aim is at transferring the geometric criterion into an algebraic formulation by a theorem that a grasp G is relative form closure,if,and only if the origin 0 can be represented as a positive convex combination of G.So we develop a constructive procedure called ri-simplex algorithm to find a positive convex combination of G when it has relative form closure.Form closure is considered as a special case of relative form closure,when the grasp G can affinely span the whole space,while partly relative form closure is referred to as form closed relative to a subset G1 of G.展开更多
文摘We proved a new necessary and sufficient condition for 2D three finger equilibrium grasps and implemented an geometrical algorithm for computing force closure grasps of arbitrary 2D objects in this article. The algorithm is quite simple and only needs some algebraic calculations. Finally, we implemented the algorithm and confirmed its usefulness by an example.
文摘Stability is a significant property for a robot hand grasp to perform complextasks similar to human hands. The common method to investigate the stability of roboticmulti-fingered grasp system is Lyapunov direct method, but usually it is rather difficult toconstruct a proper Lyapunov function. Avoiding the hard work of constructing a Lyapunov function, wepropose the sufficient conditions for stability of the robotic grasp system.
文摘This research characterizes grasping by multifingered robot hands through investiga- tion of the space of contact forces into four subspaces , a method is developed to determine the di- mensions of the subspaces with respect to the connectivity of the object. The relationship reveals the differences between three types of grasps classified and indicates how the contact force can be decomposed corresponding to each type of grasp. The subspaces and the determination of their di- mensions are illlustrated by examples.
文摘This paper deals with the problem of force-closure analysis for soft multi-fingered grasps. The first step is the study of the relationship between the external wrench space and the manipulation force space at any contact. Constraint force set, strictly constraint force set and normal force set are defined in the contact force space, followed by an investigation of their relationships. Based on the convexity of the friction constraints for soft finger contact, the necessary and sufficient conditions for force-closure grasps are derived. Accordingly an efficient algorithm for testing force-closure is presented. Some illustrative examples are given.
基金funded by Guangdong Basic and Applied Basic Research Foundation(2023B1515120064)National Natural Science Foundation of China(62273097).
文摘Deep learning has become integral to robotics,particularly in tasks such as robotic grasping,where objects often exhibit diverse shapes,textures,and physical properties.In robotic grasping tasks,due to the diverse characteristics of the targets,frequent adjustments to the network architecture and parameters are required to avoid a decrease in model accuracy,which presents a significant challenge for non-experts.Neural Architecture Search(NAS)provides a compelling method through the automated generation of network architectures,enabling the discovery of models that achieve high accuracy through efficient search algorithms.Compared to manually designed networks,NAS methods can significantly reduce design costs,time expenditure,and improve model performance.However,such methods often involve complex topological connections,and these redundant structures can severely reduce computational efficiency.To overcome this challenge,this work puts forward a robotic grasp detection framework founded on NAS.The method automatically designs a lightweight network with high accuracy and low topological complexity,effectively adapting to the target object to generate the optimal grasp pose,thereby significantly improving the success rate of robotic grasping.Additionally,we use Class Activation Mapping(CAM)as an interpretability tool,which captures sensitive information during the perception process through visualized results.The searched model achieved competitive,and in some cases superior,performance on the Cornell and Jacquard public datasets,achieving accuracies of 98.3%and 96.8%,respectively,while sustaining a detection speed of 89 frames per second with only 0.41 million parameters.To further validate its effectiveness beyond benchmark evaluations,we conducted real-world grasping experiments on a UR5 robotic arm,where the model demonstrated reliable performance across diverse objects and high grasp success rates,thereby confirming its practical applicability in robotic manipulation tasks.
基金the Major research program of national natural science foundation of China(91848206).
文摘Soft grippers research is gaining increasing attention for their flexibility.However,the conventional soft gripper primar-ily focuses on soft fingers,without considering the palm.This makes grasping forces concentrated in the fingertip areas,resulting in objects being prone to damage and instability during handling,especially for delicate items.Additionally,pre-transportation classification faces challenges:tactile methods are complex,visual methods are environment-sensitive,and both struggle with similar objects.To address these problems,inspired by the human hand's transition between finger grasp and palm support and the lotus's hierarchical structure,this paper proposes a dual-layer gripper,named IOSGrip-per.It features four pneumatic soft fingers and a rotational soft-rigid palm.Through coordinated control of the fingers and palm,it transitions concentrated fingertip squeeze force to distributed palm support force,reducing squeeze force and squeeze duration.Moreover,it integrates a range sensor and four load cells,enabling stable and accurate measurements of the object's height and weight.Furthermore,a classifier is developed based on K-nearest neighbor algorithm,allowing real-time object classification.Experiments demonstrate that compared to only using soft fingers,the IOSGripper signifi-cantly reduces the squeeze force on the objects(with 0 N squeeze force during palm support)and damage on the delicate object,while improving grasping stability.Its height and weight measurement errors are within 2 mm and 1 g,respectively.And it achieves high accuracy in three test scenarios,including classifying similar objects.This study provides useful insights for the design of soft grippers capable of human-like grasping and sorting tasks.
基金supported by the National Natural Science Foundation of China(Grant No.51327801)the National Key Basic Research Program of China(Grant No.2013CB035803)
文摘This paper presents an approach to algebraic detection of relative form closure for a multi-fingered grasp G and gives an attention to the classification of relative form closures.Whether or not a grasp G is of relative form closure has been verified by the geometric criterion 0?rintC[G](Xiong Y L,Xiong X R.Algebraic structure and geometric interpretation of rigid complex fixture system.IEEE Trans Autom Sci Eng,2007,4:252–264;Xiong Y L.Theory of point contact restraint and qualitative analysis of robot grasping.Sci China Ser A-Math,1994,37:629–640).Our aim is at transferring the geometric criterion into an algebraic formulation by a theorem that a grasp G is relative form closure,if,and only if the origin 0 can be represented as a positive convex combination of G.So we develop a constructive procedure called ri-simplex algorithm to find a positive convex combination of G when it has relative form closure.Form closure is considered as a special case of relative form closure,when the grasp G can affinely span the whole space,while partly relative form closure is referred to as form closed relative to a subset G1 of G.
