Multi-fingered Gripper Research Articles

Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning

Humans possess dexterous hands that surpass those of other animals, enabling them to perform intricate, complex movements. Soft hands, known for their inherent flexibility, aim to replicate the functionality of human hands. This article provides an overview of the development processes and key directions in soft hand evolution. Starting from basic multi-finger grippers, these hands have made significant advancements in the field of robotics. By mimicking the shape, structure, and functionality of human hands, soft hands can partially replicate human-like movements, offering adaptability and operability during grasping tasks. In addition to mimicking human hand structure, advancements in flexible sensor technology enable soft hands to exhibit touch and perceptual capabilities similar to humans, enhancing their performance in complex tasks. Furthermore, integrating machine learning techniques has significantly promoted the advancement of soft hands, making it possible for them to intelligently adapt to a variety of environments and tasks. It is anticipated that these soft hands, designed to mimic human dexterity, will become a focal point in robotic hand development. They hold significant application potential for industrial flexible gripping solutions, medical rehabilitation, household services, and other domains, offering broad market prospects.

From grasping to manipulation with gecko-inspired adhesives on a multifinger gripper.

Anthropomorphic robotic manipulators have high grasp mobility and task flexibility but struggle to match the practical strength of parallel jaw grippers. Gecko-inspired adhesives are a promising technology to span that gap in performance, but three key principles must be maintained for their efficient usage: high contact area, shear load sharing, and evenly distributed normal stress. This work presents an anthropomorphic end effector that combines those adhesive principles with the mobility and stiffness of a multiphalange, multifinger design. Adhesive suspensions use buckling ribs to deliver shear load sharing and normal compliance in a deployable form factor. We use an elastic foundation model and fundamentals of grasping theory to motivate kinematic changes when shifting from Coulomb friction to adhesive manipulation. These design considerations integrate with the necessary control infrastructure in a prototype called farmHand, on which we perform tests to confirm shear load sharing and demonstrate adhesive use in manipulation beyond pick and place grasping.

Beyond Soft Hands: Efficient Grasping With Non-Anthropomorphic Soft Grippers

Grasping and manipulation are challenging tasks that are nonetheless critical for many robotic systems and applications. A century ago, robots were conceived as humanoid automata. While conceptual at the time, this viewpoint remains influential today. Many robotic grippers have been inspired by the dexterity and functionality of the prehensile human hand. However, multi-fingered grippers that emulate the hand often integrate many kinematic degrees-of-freedom, and thus complex mechanisms, which must be controlled in order to grasp and manipulate objects. Soft fingers can facilitate grasping through intrinsic compliance, enabling them to conform to diverse objects. However, as with conventional fingered grippers, grasping via soft fingers involves challenges in perception, computation, and control, because fingers must be placed so as to achieve force closure, which depends on the shape and pose of the object. Emerging soft robotics research on non-anthropomorphic grippers has yielded new techniques that can circumvent fundamental challenges associated with grasping via fingered grippers. Common to many non-anthropomorphic soft grippers are mechanisms for morphological deformation or adhesion that simplify the grasping of diverse objects in different poses, without detailed knowledge of the object geometry. These advantages may allow robots to be used in challenging applications, such as logistics or rapid manufacturing, with lower cost and complexity. In this perspective, we examine challenges associated with grasping via anthropomorphic grippers. We describe emerging soft, non-anthropomorphic grasping methods, and how they may reduce grasping complexities. We conclude by proposing several research directions that could expand the capabilities of robotic systems utilizing non-anthropomorphic grippers.

Force transmission analysis of surface coating materials for multi-fingered robotic grippers.

Robotic systems are generally used for grasping, carrying, holding, and many similar operations, typically in industrial applications. One of the most important components of robotic systems is robot grippers for the aforementioned operations, which are not only mission-critical but also represent a significant operational cost due to the time and expense associated with replacement. Grasping operations require sensitive and dexterous manipulation ability. As a consequence, tactile materials and sensors are an essential element in effective robot grippers; however, to date, little effort has been invested in the optimization of these systems. This study has set out to develop inexpensive, easily replaced pads, testing two different chemical compositions that are used to produce a tactile material for robot grippers, with the objective of generating cost, time, and environmental savings. Each tactile material produced has its specific individual dimension and weight. First, each of the materials under construction was tested under different constant pressures, and its characteristics were analyzed. Second, each tactile material was mounted on a two-fingered robot gripper and its characteristics. Material characteristics were tested and analyzed as regards their ability to grasp different sizes and types of objects using the two-fingered robot gripper. Based on the analysis of the results the most sensitive and cost-effective material for industrial type multi-fingered grippers was identified.

Enhancing the Universality of a Pneumatic Gripper via Continuously Adjustable Initial Grasp Postures

Recently, various soft universal grippers have been developed due to their reduced control complexity and satisfying grasping capability. The gripping range of a gripper plays a key role in its universality. This article presents a pneumatically actuated soft-rigid hybrid multifinger gripper that has a wide gripping range by adjusting its initial grasp postures. The gripper is compact (dimensions: <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{100} \times \text{60} \times \text{170}$</tex-math></inline-formula> mm), lightweight (weight: 380 g), and modular. It consists of four modules, with each module containing three pneumatic actuators (a distance-adjusting actuator, an angle-adjusting actuator, and a finger actuator) and rigid connectors. Through initial grasp posture adjustment, and fingers with tapered angles to generate nonconstant bending while grasping, the gripper can grasp objects of a wide variety of sizes and weights, thus increasing its universality. The gripper is tested to characterize its distance adjustment range, angle adjustment range, and stiffnesses in load-bearing directions, at continuously changing pneumatic pressures. The distance adjustment range and angle adjustment range of the gripper are 0–64.4 mm (64.4% of the initial gripper length) and 0 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ}$</tex-math></inline-formula> –140 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ}$</tex-math></inline-formula> , respectively. The maximum stiffnesses of distance-adjusting actuator and angle-adjusting actuator are 3331 and 1.15 N <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\cdot$</tex-math></inline-formula> m/rad, respectively. Finally, grasping experiments show that our gripper can successfully grasp objects with diameters ranging from 0.5 to 180 mm, lengths ranging from 10 to 325 mm, and the heaviest object it can grasp is 2.1 kg (more than five folds of its own weight). The results demonstrated that our pneumatic gripper has an increased gripping range without adding other types of energy sources and its enhanced universality will expedite various applications in daily life and industry.

Untethered Single Cell Grippers for Active Biopsy

Single cell manipulation is important in biosensing, biorobotics, and quantitative cell analysis. Although microbeads, droplets, and microrobots have been developed previously, it is still challenging to simultaneously excise, capture, and manipulate single cells in a biocompatible manner. Here, we describe untethered single cell grippers, that can be remotely guided and actuated on-demand to actively capture or excise individual or few cells. We describe a novel molding method to micropattern a thermally responsive wax layer for biocompatible motion actuation. The multifingered grippers derive their energy from the triggered release of residual differential stress in bilayer hinges composed of silicon oxides. A magnetic layer enables remote guidance through narrow conduits and fixed tissue sections ex vivo. Our results provide an important advance in high-throughput single cell scale biopsy tools important to lab-on-a-chip devices, microrobotics, and minimally invasive surgery.

Proposal of Tracing Grip of Spine-Type Robot Gripper on Uneven Terrain

A steep cliff wall is one of the extreme terrains and inaccessible for conventional mobile robots. To cope with such a difficult terrain, multi-limbed free-climbing robots have been studied. However, development of an adaptive robot gripper to terrain roughness with mechanical efficiency still remain to be realized. In related works, although a spine-type multi-fingered gripper has been validated for robotic free-climbing, the previous grippers are oversized, hyper-redundant, and non-durable systems. This study proposes a tracing grip such that minimum fingers can achieve more adaptive spine-type gripping to the terrain surface. The tracing motion enables to guide the spine to a suitable point on the rough surface to be gripped or hooked. The developed gripper was validated through the gripping experiments using simulated terrains.The gripping performance of the gripper is quantitatively evaluated, and the effectiveness of the tracing grip is also shown.

Retraction Note to: Input Displacement Neuro-fuzzy Control and Object Recognition by Compliant Multi-fingered Passively Adaptive Robotic Gripper

The requirement for new flexible adaptive grippers is the ability to detect and recognize objects in their environments. It is known that robotic manipulators are highly nonlinear systems, and an accurate mathematical model is difficult to obtain, thus making it difficult make decision strategies using conventional techniques. Here, an adaptive neuro fuzzy inference system (ANFIS) for controlling input displacement and object recognition of a new adaptive compliant gripper is presented. The grasping function of the proposed adaptive multi-fingered gripper relies on the physical contact of the finger with an object. This design of the each finger has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize particular shapes of the grasping objects. Fuzzy based controllers develop a control signal according to grasping object shape which yields on the firing of the rule base. The selection of the proper rule base depending on the situation can be achieved by using an ANFIS strategy, which becomes an integrated method of approach for the control purposes. In the designed ANFIS scheme, neural network techniques are used to select a proper rule base, which is achieved using the back propagation algorithm. The simulation results presented in this paper show the effectiveness of the developed method.

Algorithm for Planning and Selection of Deformable Object Grasp by Multi-Finger Gripper of Robotic Manipulator

Principal advantage of robotic systems is the ability to perform tasks of dexterous manipulation with objects with sufficient removal of the person from the operating area. Particularly relevant are issues of robotics operations when working with explosive objects that pose a threat to human life and health. The simplest manipulation tasks include object grasping, which is the initial stage of most operations. Grasp of object is a problem of its immobilization inside the robot's gripper. Solving this problem makes it possible to hold object in the presence of external perturbations. An algorithm for selection of deformable object grasp is considered, taking into account the minimization of contact forces. Distinctive features of the algorithm - taking into consideration the change in the shape of the object's surface and the displacement of its center of mass, caused by deformation of the object during grasping and execution of the manipulation task, and verification of the object desired position reachability at the grasp planning stage. The algorithm for grasp planning includes: an algorithm for generating grasp hypotheses; algorithm for planning the trajectories of gripper's links for object grasping; algorithm for determining the intersections of object's and gripper's links'polygonal model; algorithm for calculating the forces of contact interaction between object and gripper's links; algorithm for determining the center of mass of the object, deformed during grasping; algorithm for estimating the stability of grasp; algorithm for verifying the reachability of the object desired position; algorithm for planning the gripper's joints movement for moving object during manipulation task; algorithm for determining the grasp method.

The Capturing of Space Debris with a Spaceborne Multi-fingered Gripper

With the massive launching of spacecraft, more and more space debris are making the low Earth orbit (LEO) much more crowded which seriously affects the normal flight of other spacecrafts. Space debris removal has become a very urgent issue concerned by numerous countries. In this paper, using SwissCube as a target, the capturing of space debris with a spaceborne four-fingered gripper was studied in order to obtain the key factors that affect the capturing effect. The contact state between the gripper fingers and SwissCube was described using a defined contact matrix. The law of momentum conservation was used to model the motion variations of the gripper and SwissCube before and after the capturing process. A zero-gravity simulation environment was built using ADAMS software. Two typical kinds of capturing processes were simulated considering different stiffness of fingers and different friction conditions between fingers and SwissCube. Comparisons between results obtained with the law of momentum conservation and those from ADAMS simulation show that the theoretical calculations and simulation results are consistent. In addition, through analyzing the capturing process, a valuable finding was obtained that the contact friction and finger flexibility are two very important factors that affect the capturing result.

惣菜を円錐状に盛付可能な２自由度多指グリッパの開発

In recent years, industrial robots have been applied to food production due to its huge potential market size. Although cooking large amount of foods are done by specially designed cooking machines, dishing up the cooked foods remains as a labor-intensive task. To solve this problem, this paper proposes a new food handling gripper that is suitable for lunch box setout considering appetizing shape of presentation. A two degree-of-freedom multi-fingered gripper with a sliding push part was developed, and evaluated by grasping experiments with noodles and simmered foods. The gripper could put the food with a circular cone shape and control the amount of grasped food.

RETRACTED ARTICLE: Input Displacement Neuro-fuzzy Control and Object Recognition by Compliant Multi-fingered Passively Adaptive Robotic Gripper

The requirement for new flexible adaptive grippers is the ability to detect and recognize objects in their environments. It is known that robotic manipulators are highly nonlinear systems, and an accurate mathematical model is difficult to obtain, thus making it difficult make decision strategies using conventional techniques. Here, an adaptive neuro fuzzy inference system (ANFIS) for controlling input displacement and object recognition of a new adaptive compliant gripper is presented. The grasping function of the proposed adaptive multi-fingered gripper relies on the physical contact of the finger with an object. This design of the each finger has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize particular shapes of the grasping objects. Fuzzy based controllers develop a control signal according to grasping object shape which yields on the firing of the rule base. The selection of the proper rule base depending on the situation can be achieved by using an ANFIS strategy, which becomes an integrated method of approach for the control purposes. In the designed ANFIS scheme, neural network techniques are used to select a proper rule base, which is achieved using the back propagation algorithm. The simulation results presented in this paper show the effectiveness of the developed method.

An Empirical Framework for Controlling Artificial Hand Gripper System Using Smart Glove

A human hand is a very complex grasping architecture which can handle objects of different sizes and shapes. When such important feature is lost, the replacement artificial hand should capable to imitate the real hand capability, hence ensuring user comfort. This paper proposes a system to control multi finger grippers with emphasis on the finger tips and finger joints. It consists of two modules namely smart glove in master module and hand gripper in slave module. The former responsible to infer user control command while the latter controlling the robot arm movement according to the user instruction. In master module, the system comprises combination of flex sensors and force sensor mounted under the glove to determine fingers bending angle and the force value. Such information is useful to control the artificial gripper for grasping objects in various shapes with right amount of force. In the slave module, the robot arm consist combination of power window motor and servos to initiate the arm and finger movement. Experimental results have shown the feasibility of the proposed system for controlling the artificial gripper and arm precisely according to the user command.

Compliant multi-fingered passively adaptive robotic gripper

Purpose – The paper aims to discuss a new design methodology for multi-fingered robotic grippers. Design/methodology/approach – Optimization of the compliant mechanism with underactuation. Findings – A new robotic gripper principle without active control. Originality/value – Design of multi-fingered robotic gripper as a monolithic structure without joints.

Ionic Polymer Conductor Nano-Composites as Distributed Nanosensors, Nanoactuators and Artificial Muscles - A Review

ABSTRACTBasic recent results, properties and characteristics of ionic polymer conductor nano-composites (IPCNC) as biomimetic distributed nanosensors, nanoactuators and artificial muscles are briefly discussed in this paper. Some fundamental considerations on biomimetic distributed nanosensing and nanoactuation are first presented and then expanded to cover some recent advances in manufacturing techniques, force optimization, 3-D fabrication of IPMC's, recent modeling and simulations, sensing and transduction and product development. This paper also covers some recent industrial and medical applications including a multi-fingered grippers (macro, micro, nano), biomimetic robotic fish and caudal fin actuators, diaphragm micropump, multi-string musical instruments, linear actuators made with IPMNC's, IPMNC-based data glove and attire, IPMNC-based heart compression/assist devices and systems, wing flapping flying system made with IPMNC's and a host of others.

DEVELOPMENT AND DESIGN OF A MULTI-FINGERED GRIPPER FOR DEXTEROUS MANIPULATION

In this paper, we propose a multi-fingered gripper, which is able to achieve manipulation of objects with six degrees of freedom by actuating exactly six joints. After grasping, adhesion forces, provided, e.g. by an electromagnet or a vacuum cup, ensure that the fingertips remain connected to the object to be manipulated. The resulting closed-loop mechanism, formed by the gripper and the object features a kinematic structure similar to that of parallel manipulators. Such a gripper has many advantages over existing industrial grippers, often used for simple gripping tasks, and existing mechanical hands with a complex and costly control architecture.

Spatial grasp synthesis for complex objects using model‐based simulation

PurposeSelection of an effective grasp of a complex object using a multifingered gripper is a challenging problem because of the many possible grasp positions that are typically available.Design/methodology/approachGiven the geometrical description of the particular object feature to be grasped, all feasible grasps are performed in offline simulation using a geometrically accurate model of the desired gripper. The six‐dimensional convex hull for each grasp is computed and archived. This convex hull indicates the span of forces and torques that the grasp can resist. When a grasp is needed the force/torque due to the total object weight is estimated and the best grasp is selected. The selected grasp has minimum peak contact force consistent with equilibrium.FindingsExperimental trials with several complex object show the method is capable of producing grasps which can support the object and resist external force/torque.Research limitations/implicationsAn accurate geometrical description of the feature to be grasped must be known in advance. This would typically be a cylindrical or prismatic portion of the object.Practical implicationsThere are many environments in which a dexterous multifingered gripper must be used due to the variety of objects which must be grasped. The results indicate that effective grasps can be selected for complex objects from a database of simulated grasps.Originality/valueThe primary contribution of this paper is the use of a database of simulated grasps on simple graspable features to synthesize grasps on complex objects.

Design of a Six DOF Reconfigurable Gripper for Flexible Fixtureless Assembly

In this paper, the design and development of a six degrees-of-freedom (DOF) reconfigurable gripper for implementation of robot based flexible fixtureless assembly (FFA) is described. FFA is a novel technique in which traditional fixtures used, for example, in automotive body assembly industries, are eliminated by the use of several robots, with multifinger grippers that are used to grasp and assemble parts. The objective of this work is to design, build, and test a reconfigurable gripper for the purpose of FFA. The gripper developed in this work is capable of precisely grasping parts of different geometries, rigidly holding the parts in space, and choosing different grasping points while allowing sufficient clearance for welding gun access. The overall design procedure, which is subdivided into the conceptual, configuration and parametric design, includes wrench system determination, kinematic and mechanism design. A novel three-finger gripper is developed. Each finger has two movable joints and two point-contacts with which to grasp the part. Finite element analysis is used to simulate deflections of the gripper components under load to determine critical design parameters. Finally, the workspace and the kinematic model of the reconfigurable gripper have been developed. The gripper was fabricated and tested in grasping experiments using several automotive body panels. The reconfigurable gripper is shown to achieve the objectives set out in this work.

Vision-based action control system of a multi-finger mechanical gripper

A study about the action control of a dexterous mechanical gripper based on stereo-vision system was proposed. The vision-based system was used to replace the data-glove for gesture measurement. The stereo vision theory was applied to calculate the 3D information of the hand gesture. The information was used to generate the grasping action parameters of a 3-finger dexterous mechanical gripper. Combined with a force feedback device, a closed control loop could be constructed. The test for the precision of the algorithms and action control simulation result were shown in the paper.

Development of an Articulated Gripper for an Underwater ROV.

An adaptive multifinger gripper system was developed for underwater ROV. The system, named The Artifact 'K' apture Operator (TAKO) gripper, provides soft and adaptive envelope grasp with three articulated fingers. Each finger comprises five segments and performs like an octopus tentacle. The gripper has 15 segments in total, yet they are coordinately driven by one single motor and tendon mechanisms. This design allows the gripper system compact, light weight, and less expensive. The TAKO gripper is mounted on an underwater ROV named Triton that is a research oriented test platform developed at Santa Clara University. The TAKO-Triton integrated test was carried out successfully for the artifact pick-up operation from the bottom of the water.