Grippers

The manipulator robots are devices used to perform dangerous tasks and impossible missions that humans cannot perform without paying too much effort and time. Therefore, they are used in a wide range of applications without any interaction with humans. This type of robot can carry different types of endeffectors to perform various kinds of applications. According to the Application, the robot end-effector types can be applied to perform the task accurately. Grippers are mainly used for grasping. The grasping process can be defined as the act of holding objects. One of the essential types of grippers is the reconfigurable type. This type of gripper is very excited because of its adaptation and reconfigurability features that they have. The problem of grasping different objects with different shapes and geometries is a crucial enigma. When the manipulators are utilized to automate the tasks in industrial plants, the gripper tool is changed according to the application requirement, which will cause longer cycle times and more expensive grippers. The possibility of having a gripper that adapts to the applications without changing it is significant in reducing the time and cost of manufacturing. This paper will review the studies conducted around re-configurable grippers and classify the literature based on the number of fingers. Many critical parameters, objectives, structural and mechanisms of the re-configurable grippers will be presented separately using tables for each class. We proposed a new type of re-configurable gripper to be studied, and it will be the axis of the subsequent research.

El presente trabajo de investigación hace referencia al diseño y construcción de un gripper para un brazo robótico, debido a que el gripper debe ser acoplado a uno de los brazos robóticos que han sido desarrollados por investigadores de la facultad de ciencias de la electrónica ubicados en el laboratorio de robótica y control, el diseño no debe tener efectos significativos en peso, corriente consumida y debe ser de fácil montaje. Este prototipo será parte de un sistema de reconocimiento de tarjetas de desarrollo electrónico, que por medio de una cámara que tiene un algoritmo de visión desarrollado en Matlab para poder detectar componente faltantes, algunas anormalidades en las tarjetas y con esa información poder activar al brazo y una secuencia del gripper para poder retirar la tarjeta, realizar la soldadura de algún componente y con ello automatizar una línea de producción de tarjetas de desarrollo electrónico.

A mechanical gripper is used as an end effector in a robot for grasping the objects with its mechanically operated fingers. In industries, two fingers are enough for holding purposes. More than three fingers can also be used based on the application. As most of the fingers are of replaceable type, it can be easily removed and replaced. The force that a robotic gripper applies to a part is typically used by engineers to select grippers but in actual practice it is not enough to select gripper. There are so many factors are to be considered while designing the gripper like mechanism for gripping, trajectories, parameters that influencing gripping task etc. So in this paper those factors are discussed in brief.

Adaptive grippers should be able to detect and recognize grasping objects. To be able to do it control algorithm need to be established to control gripper tasks. Since the gripper movements are highly nonlinear systems it is desirable to avoid using of conventional control strategies for robotic manip-ulators. Instead of the conventional control strategies more advances algorithms can be used. In this study several soft computing methods are analyzed for robotic gripper applications. The gripper structure is fully compliant with embedded sensors. The sensors could be used for grasping shape detection. As soft computing methods, extreme learning machine (ELM) and support vector regression (SVR) were established. Also other soft computing methods are analyzed like fuzzy, neuro-fuzzy and artificial neural network approach. The results show the highest accuracy with ELM approach than other soft computing methods.

Over the past decades, automation industry has seen a major shift from traditional, hard-tooled lines to reconfigurable and reprogrammable robotic cells. Robots have added increasing value to the industry with special focus on robotic arms which enable many repetitive tasks to be carried out with high repeatability, reliability, flexibility, and speed. Grasping, carrying and placement of objects are the basic capabilities of robotic arms. However, with the integration of new technologies the capabilities, of robotic arms can be extended. As such, grippers being an essential component of robots play an important role in many handling tasks since they serve as end-of-arm tools. The aim of this paper is to propose a new end effector design, which is integrated with a sensing system, for improving the adaptivity and flexibility of a robotic cell in comparison with the State-of-the-Market end effector solutions. The proposed design is used to extend this research work and to develop an intelligent end effector based on the implementation of a Machine Vision algorithm, for the recognition of the part, the gripper, and 3D scanning the produced part. The recognition of the part is essential in order for the robot to grasp the object appropriately and facilitate the machining process. The 3D scanning of the part geometry will be utilized for CAD comparison versus the original drawings. Finally, based on the Finite Element Analysis (FEA) and the topology optimization, a reduction of the material used for the 3D printing of the gripper has been reduced by 19.57%.

This paper presents the fuzzy logic design and control for three finger gripper system to grasp an object. Two objectives are mainly considered in this work, which are the analysis of different membership types and the gripper performance with feedback and without feedback control to support current research findings. The comparison is also including different number of rules analysis as well as the fuzzy membership types. The simulation and analysis are carried by using MATLAB Simulink and SimMechanics toolboxes to analyze the system performance. The result shows that the gripper system with trapezoidal memberships achieved faster response and good grasp. Besides that, the proposed system with feedback has produced the best result to grasp the object with suitable torques and angles in comparison to the non-feedback gripper system.

In the developing technological scenario, the researchers are looking for a material that is highly reliable and having unique property to retaining its shape in certain high and low temperature. The shape memory alloy is having prescribed qualities and one of its unique property is to recover shape upon heating can be effectively packaged into compact, light, powerful silent actuators to replace DC motors and electrical motors. The objective of the paper is to design, fabricate and analysis of gripper on the principle of slide crank mechanism, which is actuate with Shape Memory Alloy spring. The characteristics targeted in this experiment are of ensuring mechanical actions if stimulated with electrical current allows the development of simple, more compact and reliable actuators.

In this paper, we describe the conceptual design and implementation of the Soft Compliant Manipulator for Broad Applications (SIMBA) manipulator, which is designed and developed for participating in the RoboSoft Grand Challenge 2016. In our novel design, we have proposed (1) a modular continuum arm with independent actuation units for each module, to increase maintainability; (2) a soft reconfigurable hand, for a better adaptation of the fingers to objects of different shapes and size; (3) a moving base for increasing the workspace. We used a hybrid approach in designing and manufacturing by integrating soft and hard components, in both materials and actuation, providing high lateral stiffness in the arm through flat springs, soft joints in fingers for more compliancy and tendon-motor actuation mechanism providing flexibility but at the same time precision and speed. The SIMBA manipulator has demonstrated excellent grasping and manipulation capabilities by being able to grasp objects with different fragility, geometry, and size; and by lifting objects with up to 2 kg of weight it demonstrate also to be robust and reliable. The experimental results pointed out that our design and approach can lead to the realization of robots able to act in unknown and unstructured environments in synergy with humans, for a variety of applications where compliancy is fundamental, preserving robustness and safety.

This paper reports a novel structure of a shape-memory-alloy (SMA) micromanipulator with gripping mechanism. A featured integration of multiple SMA bimorph microactuators has been utilized to form a micromanipulator with three degrees of freedom. The design consists of two links (SMA sheets) and a gripper at the end of the second joint. The overall dimensions of the micromanipulator are 33 mm × 9 mm × 3 mm. The displacement of each actuator is controlled by a heating circuit that generates a pulse-width modulation signal. Theoretical modeling of SMA actuators is studied and verified with simulation. The SMA micromanipulator is able to move in the x- and y-axis by 7.1 mm and 5.2 mm, respectively, resulting in a maximum displacement of 8.9 mm. The micro-gripper has a maximum opening gap between its fingers of 1.15 mm. The micromanipulator has a temporal response of 7.5 s and 9 s for its x- and y-axis. The maximum actuation force generated by the x- and y-axis was around 100 mN and 130 mN, respectively. The developed micromanipulator has been successfully used to move a small object.

Piezoelectric bimorphs have been used as a micro-gripper in many applications, but the system might be complex and the response performance might not have been fully characterized. In this study the dynamic characteristics of bending piezoelectric bimorphs actuators were theoretically and experimentally investigated for micro-gripping applications in terms of deflection along the length, transient response, and frequency response with varying driving voltages and driving signals. In addition, the implementation of a parallel micro-gripper using bending piezoelectric bimorphs was presented. Both fingers were actuated separately to perform mini object handling. The bending piezoelectric bimorphs were fixed as cantilevers and individually driven using a high voltage amplifier and the bimorph deflection was measured using a non contact proximity sensor attached at the tip of one finger. The micro-gripper could perform precise micro-manipulation tasks and could handle objects down to 50 μm in size. This eliminates the need for external actuator extension of the microgripper as the grasping action was achieved directly with the piezoelectric bimorph, thus minimizing the weight and the complexity of the micro-gripper. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

http://www.mdpi.com/1424-8220/13/5/5826

This paper reports a novel structure of a shape-memory-alloy (SMA) micromanipulator with gripping mechanism. A featured integration of multiple SMA bimorph microactuators has been utilized to form a micromanipulator with three degrees of freedom. The design consists of two links (SMA sheets) and a gripper at the end of the second joint. The overall dimensions of the micromanipulator are 33 mm × 9 mm × 3 mm. The displacement of each actuator is controlled by a heating circuit that generates a pulse-width modulation signal. Theoretical modeling of SMA actuators is studied and verified with simulation. The SMA micromanipulator is able to move in the x- and y-axis by 7.1 mm and 5.2 mm, respectively, resulting in a maximum displacement of 8.9 mm. The micro-gripper has a maximum opening gap between its fingers of 1.15 mm. The micromanipulator has a temporal response of 7.5 s and 9 s for its x- and y-axis. The maximum actuation force generated by the x- and y-axis was around 100 mN and 130 mN, respectively. The developed micromanipulator has been successfully used to move a small object.

Adaptivegrippersshouldbeabletodetectandrecognizegraspingobjects.Tobeabletodoitcontrol algorithm needtobeestablishedtocontrolgrippertasks.Sincethegrippermovementsarehighly nonlinear systemsitisdesirabletoavoidusingofconventionalcontrolstrategiesforroboticmanip- ulators. Insteadoftheconventionalcontrolstrategiesmoreadvancesalgorithmscanbeused.Inthis study severalsoftcomputingmethodsareanalyzedforroboticgripperapplications.Thegripperstruc- ture isfullycompliantwithembeddedsensors.Thesensorscouldbeusedforgraspingshapedetection. As softcomputingmethods,extremelearningmachine(ELM)andsupportvectorregression(SVR)were established. Alsoothersoftcomputingmethodsareanalyzedlikefuzzy,neuro-fuzzyandartificial neural networkapproach.TheresultsshowthehighestaccuracywithELMapproachthanothersoftcomputing methods.

The design and development of robotic end effectors for a specific operation in Industry has been an active research area for a long while. The main objective here is to design a robotic gripper for achievement of sufficient level of dexterity in the domain of grasping and manipulation when attached to any Remote Handling (RH) arm. The work presented includes a thorough study of different gripper mechanisms along with kinematic assessment of gripper for pick-and-place operation, design & FEA analysis of the gripper frame. The gripper designed is within a specified envelope with a maximum opening of 5cm and payload capacity 1 kg.
This thesis presents the structural analysis of two fingered gripper working with a parallelogram mechanism and a single actuator. Analytical calculations and analysis were performed to verify the structural integrity of the gripper mechanism and to calculate the necessary reaction forces required during component handling.

The  authors  experimentally  investigated  the  friction  and adherence  between  small cylindrical objects and human fingers. The experiments were realized for low normal loads between small cylinders and human fingers and low sliding speed. Were obtained variation of adherence and sliding forces as function of time during the reciprocating-sliding of the small cylindrical bodies on soft skin of the human finger. Were evidenced cyclically deformed and relaxed of the lateral skin as a result of reciprocating motion of the cylinders and were determined the corresponding forces. Also,  was  evidenced  the  “butterfly”  configuration  between  the  tangential  force  and  lateral
displacement.

Grippers and robotic hands are an important field in robotics. Recently, the combination of grasping devices and haptic feedback has been a promising avenue for many applications such as laparoscopic surgery and spatial telemanipulation. This paper presents the work behind a new self-adaptive, a.k.a. underactuated, gripper with a proprioceptive haptic feedback in which the apparent stiffness of the gripper as seen by its actuator is used to estimate contact location. This system combines many technologies and concepts in an integrated mechatronic tool. Among them, underactuated grasping, haptic feedback, compliant joints and a differential seesaw mechanism are used. Following a theoretical modeling of the gripper based on the virtual work principle, the authors present numerical data used to validate this model. Then, a presentation of the practical prototype is given, discussing the sensors, controllers, and mechanical architecture. Finally, the control law and the experimental validation of the haptic feedback are presented.