Underactuated Finger Mechanism Research Articles

A Back-Drivable Rotational Force Actuator for Adaptive Grasping

In this paper, a back-drivable and miniature rotary series elastic actuator (RSEA) is proposed for robotic adaptive grasping. A compact arc grooves design has been proposed to effectively reduce the dimension of the RSEA system. The elastic elements could be reliably embedded in the arc grooves without any additional installation structures. The whole RSEA system is characterized as compact, miniature, and modular. The actuating force is controlled via a PI controller by tracking the deformation trajectory of the elastic elements. An underactuated finger mechanism has been adopted to investigate the effectiveness of the RSEA in robotic adaptive grasping. Results reveal that the underactuated finger mechanism could achieve adaptive grasping via the RSEA in a back-drive approach without the requirement of a fingertip force sensor. The RSEA could also exhibit an actuating compliance and a self-sensing characteristic. The actuating compliance characteristic helps in in guaranteeing the safety of human–robot interaction. The RSEA could estimate the external disturbance due to its self-sensing characteristic, which has the potential to replace the fingertip force sensor in grasping force perception applications.

Sensor-Less Grasping Force Control of a Pneumatic Underactuated Robotic Gripper

Abstract The primary motivation of this study is to develop a sensor-less, easily controlled, and passively adaptive robotic gripper. A back-drivable pneumatic underactuated robotic gripper (PURG), based on the pneumatic cylinder and underactuated finger mechanism, is presented to accomplish the above goals. A feedforward grasping force control method, based on the learned kinematics of the underactuated finger mechanism, is proposed to achieve sensor-less grasping force control. To enhance the grasping force control accuracy, a state-based actuating force modeling method is presented to compensate the hysteresis error which exists in the transmission mechanism. Actuating force control experiment is performed to validate the effectiveness of the state-based actuating pressure modeling method. Results reveal that compared with the non-state-based modeling method, the proposed state-based actuating force modeling method could reduce the modeling error and control error by about 37.0% and 77.2%, respectively. Results of grasping experiments further reveal that grasping force could be accurately controlled by the state-based feedforward control model in a sensor-less approach. Adaptive grasping experiments are performed to exhibit the effectiveness of the sensor-less grasping force control approach.

Modeling, Design, and Implementation of an Underactuated Gripper with Capability of Grasping Thin Objects

Underactuated robotic grippers have the advantage of lower cost, simpler control, and higher safety over the fully actuated grippers. In this study, an underactuated robotic finger is presented. The design issues that should be considered for stable grasping are discussed in detail. This robotic finger is applied to design a two-fingered underactuated gripper. Firstly, a new three-DOF linkage-driven robotic finger that combines a five-bar mechanism and a double parallelogram is presented. This special architecture allows us to put all of the required actuators into the palm. By adding a torsion spring and a mechanical stopper at a passive joint, this underactuated finger mechanism can be used to perform parallel grasping, shape-adaptive grasping, and environmental contact-based grasp. Secondly, the dynamic model of this robotic finger is developed to investigate how to select an appropriate torsion spring. The dynamic simulation is performed with a multi-body dynamic simulator to verify our proposed approach. Moreover, static grasp models of both two-point and three-point contact grasps are investigated. Finally, different types of grasping modes are verified experimentally with a two-fingered underactuated robotic gripper.

Design and Optimization of Coupled and Self-Adaptive of An Underactuated Robotic Hand Using Particle Swarm Optimization

A large work has been devoted to create and design the novel underactuated robotic hand that mimic human hand in terms of motion and grasps. The objective of this paper is to design and development of four-finger underactuated robotic hand mechanisms with 2-DOF for each finger that is highly underactuated which controlled by single actuator that can be used with wide applications. The principle of this hand mechanism is to use the linkage seesaw differentials and the design of robotic finger integrates segments by pin joints and a tendon, that allowing it easily of grasping and adaptable different objects. Furthermore, the robotic finger was designed with combines advantages of the concept of rigid coupled and selfadaptive into one unit to achieve better performance with simple design. To plan the trajectory of the robotic finger and force-isotropic that resembled the human finger in motion and grasping operation, Underactuated finger mechanism was preliminary analysis to predict the relationship between the joint angles of robotic finger related to mechanical parameters as well as contact forces then, modified by optimized set of parameters using particle swarm optimization (PSO). Where, the parameter design constraints were formulated for a multi objective optimization problem using the evaluation criteria for human finger in motion and grasping. Experiments were conducted in order to validate the theoretical analysis by addition of angles sensors on each segment of fingers and the results show that the proposed hand is able to mimic human hand in terms of motion and adaptive grasps.

Grasp configuration planning for a low-cost and easy-operation underactuated three-fingered robot hand

This paper proposes a method for modeling and planning the grasping configuration of a robotic hand with underactuated finger mechanisms. The proposed modeling algorithm is based on analysis and mimicking of human grasping experience. Results of the analysis is preprocessed and stored in a database. The grasp configuration planning algorithm can be used within a real time online grasp control as based on artificial neural networks. Namely, shapes and sizes of task objects are described by taxonomy data, which are used to generate grasp configurations. Then, a robot hand grasp control system is designed as based on the proposed grasp planning with close-loop position and force feedback. Simulations and experiments are carried out to show the basic features of the proposed formulation for identifying the grasp configurations while dealing with target objects of different shapes and sizes. It is hoped that the well-trained underactuated robot hand can solve most of grasping tasks in our life. The research approach is aimed to research low-cost easy-operation solution for feasible and practical implementation.

A multi-jointed underactuated robot hand with fluid-driven stretchable tubes

Inspired from flexible bending of octopus’ tentacles and outside-driving kind of traditional exoskeletons, this paper proposed a novel self-adaptive underactuated finger mechanism, called OS finger. OS finger is similar to an octopus’ tentacle and consists of an artificial muscle which is through all joints and driven by fluid, eight serial-hinged joints, and force-changeable assembly. The force-changeable assembly is mainly composed of a spring and elastic rubber membrane, which is coordinated for stable grasping by a layer of rubber material in the surface of the finger. OS finger can execute different grasping modes depending on the shapes and dimensions of the grasped objects and grip objects in a gentle and form-fitting manner. The OS finger combines good qualities of both rigid grasp of traditional fingers and form-fitting grasp of flexible fingers. Kinematic analysis and experimental results show that the OS robot Hand with four OS fingers is valid for precise pinching, self-adaptive powerful encompassing, and grasping forces that are freely changeable in a wide range. With the advantage of high self-adaptation, various grasp configurations and large range of grasping forces, the OS Hand has a wide range of applications in the area of service robotics which requires a lot of flexible operations of general grasping, moving and releasing.

A 3D-printed Robot Hand with Three Linkage-driven Underactuated Fingers

In this study, we improved an underactuated finger mechanism by using Solidworks to simulate the grasp operation of a finger in some different situations. In addition, a robot palm is designed for the three-finger robot hand with the designed underactuated fingers. A Solidworks simulation was used to verify the rationality of the design. Some parts of the hand were modified to fit for 3D printing, and a prototype of the hand was produced by 3D printing, which could reduce the cost of the production process, as well as provide design flexibility and other advantages. Finally, some grasping experiments were made with the prototype. The results showed that the robot could grasp objects with different sizes, and further verified the rationality of the design and feasibility of fabricating the robot hand using 3D printing.

Humanoid design of mechanical fingers using a motion coupling and shape-adaptive linkage mechanism

This paper proposes a novel underactuated finger mechanism based on a motion coupling and shape-adaptive linkage design that combines anthropomorphic free motion and adaptive grasping. The proposed three-joint finger mechanism with one active Degree of Freedom (DOF) consists of a five-linkage mechanism in the proximal phalanx and a mechanism comprising two parallel planar four-bar linkages in the middle phalanx. The respective mechanism allows the simultaneously rotation of their corresponding phalanges in the plane before making contact with an object, and can fully envelop an object, even if certain phalanges are blocked. The duel parallel four-bar linkage mechanism is adopted to improve the grasping capacity of the distal phalanx. An optimal design of the finger is presented according to anthropomorphic phalanx trajectories and maximized grasping forces obtained with consideration for the angular velocity relationships of the three phalanges and their force transmission performances. The functionality of the proposed finger mechanism is verified through multiple simulations and grasping experiments using a prototype finger.

Underactuated Finger Mechanism Using Contractible Slider-Cranks and Stackable Four-Bar Linkages

This paper presents an underactuated finger mechanism that is able to conduct both self-adaptive grasping and natural motions, such as flexion and extension. The robotic finger is realized with a three degrees-of-freedom mechanism composed of stackable four-bar linkages and contractible slider-cranks having a linear spring in each mechanism layer. Kinematics and static force analysis are performed to reveal the operation principle of the proposed finger mechanism. The procedure for synthesizing the linkages is also suggested using Freudenstein's equation. Finally, both simulations and experiments are conducted to confirm the design feasibility.

Kinematic Analysis of a Novel Couple-Adaptive Underactuated Finger Mechanism

This paper presents the design of finger mechanism with one active DOF that combines underactuation mechanism and spring elements. The three phalanges of human finger can not only rotate simultaneously with a certain ratio before touching the grasped object, but can also envelop the object successively even if some of them are blocked, called the Couple-Adaptive feature. To realize this function in the finger mechanism, a novel underactuated four-bar mechanism is proposed in this paper. The kinematics model has been derived based on a vector analysis. The simulations of kinematic analysis show that this underactuated finger mechanism has anthropomorphic motion and grasping feature. And its workspace indicates that this prosthetic finger could complete most of grasping tasks.

Fully Rotational Joint Underactuated Finger Mechanism and Its Kinematics Analysis

Fully Rotational Joint Underactuated Finger Mechanism and Its Kinematics Analysis

Underactuated Finger Mechanism for Body-Powered Partial Prosthesis

Underactuated Finger Mechanism for Body-Powered Partial Prosthesis

Analyzing of flexible gripper by computational intelligence approach

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. Compliant underactuated mechanisms with passive behavior can be used for modelling of adaptive robotic fingers. Undearactuation is a feature which allows fully adaptability of robotic fingers for different objects. In this study gripper with two fingers was established. Finite element method (FEM) procedure was used to optimize the gripper structural topology. Kinetostatic model of the underactuated finger mechanism was analyzed. This design of the gripper 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 specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. The sensors could be used for grasping shape detection. Given that the contact forces of the finger depend on contact position of the finger and object, it is suitable to make a prediction model for the contact forces in function of contact positions of the finger and grasping objects. The prediction of the contact forces was established by using a soft computing (computational intelligence) approach. To perform the contact forces estimation adaptive neuro-fuzzy (ANFIS) methodology was used. FEM simulations were performed in order to acquire experimental data for ANFIS training. The main goal was to apply ANFIS network in order to find correlation between sensors’ stresses and finger contact forces. Afterwards ANFIS results were compared with benchmark models (extreme learning machine (ELM), extreme learning machine with discrete wavelet algorithm (ELM-WAVELET), support vector machines (SVM), support vector machines with discrete wavelet algorithm (SVM-WAVELET), genetic programming (GP) and artificial neural network (ANN)). The reliability of these computational models was analyzed based on simulation results.

A fully rotational joint underactuated finger mechanism and its kinematics analysis

The characteristic features of underactuated finger are compact structure, large grasping force, and simple operation. It has a wide application prospect in the fields of industrial robot, humanoid robot, human artificial limb, and space robot. A new type of fully rotating joint linkage-based underactuated mechanism is proposed, and a new method based on the law of minimum resistance is presented to realize the equivalent mechanism at different contact conditions of the finger and the kinematical analysis based on the equivalent mechanism. The kinematic equations and the limit moving position of the mechanism are derived using the proposed method. Finally, the numerical simulation is carried out by MATLAB program. The correctness and effectiveness of the proposed method are verified. The simulation results show that the proposed mechanism has a large grasp space and can achieve good grasp trajectory.

Design and simulation of an underactuated finger mechanism for LARM Hand

SUMMARYAn underactuated mechanism is presented as a new finger design for improving grasp adaptability of LARM Hand fingers. Underactuation is discussed as a feasible solution through several design structures for finger adaptability to shape and size of objects to be grasped. The proposed underactuated solution for a new LARM finger is characterized through simulation results in ADAMS environment for operation feasibility and performance.

Prediction of contact forces of underactuated finger by adaptive neuro fuzzy approach

To obtain adaptive finger passive underactuation can be used. Underactuation principle can be used to adapt shapes of the fingers for grasping objects. The fingers with underactuation do not require control algorithm. In this study a kinetostatic model of the underactuated finger mechanism was analyzed. The underactuation is achieved by adding the compliance in every finger joint. Since the contact forces of the finger depend on contact position of the finger and object, it is suitable to make a prediction model for the contact forces in function of contact positions of the finger and grasping objects. In this study prediction of the contact forces was established by a soft computing approach. Adaptive neuro-fuzzy inference system (ANFIS) was applied as the soft computing method to perform the prediction of the finger contact forces.

A Low-Cost Open-Source 3-D-Printed Three-Finger Gripper Platform for Research and Educational Purposes

Robotics research and education have gained significant attention in recent years due to increased development and commercial deployment of industrial and service robots. A majority of researchers working on robot grasping and object manipulation tend to utilize commercially available robot-manipulators equipped with various end effectors for experimental studies. However, commercially available robotic grippers are often expensive and are not easy to modify for specific purposes. To extend the choice of robotic end effectors freely available to researchers and educators, we present an open-source low-cost three-finger robotic gripper platform for research and educational purposes. The 3-D design model of the gripper is presented and manufactured with a minimal number of 3-D-printed components and an off-the-shelf servo actuator. An underactuated finger and gear train mechanism, with an overall gripper assembly design, are described in detail, followed by illustrations and a discussion of the gripper grasping performance and possible gripper platform modifications. The presented open-source gripper platform computer-aided design model is released for downloading on the authors research lab website (<;uri xlink:href="http://www.alaris.kz" xlink:type="simple">www.alaris.kz<;/uri>) and can be utilized by robotics researchers and educators as a design platform to build their own robotic end effector solutions for research and educational purposes.

Optimization of a Novel Anthropomorphic Three-Jointed Underactuated Finger Mechanism

A novel underactuated finger mechanism based on linkage and spring elements is proposed. The kinematic characteristic of the mechanism is analyzed to obtain the fingertip displacement and relationships between three joints. Considering the motion feature of human finger and actuation efficiency of the driving motor, the dimensional design of the finger mechanism is formulated as an optimization problem. The numerical simulation result shows that the finger mechanism can not only realize the anthropomorphic coupling motion, but also envelope objects with various shapes and sizes self-adaptively.

Analysis and optimal design of an underactuated finger mechanism for LARM hand

This paper aims to present general design considerations and optimality criteria for underactuated mechanisms in finger designs. Design issues related to grasping task of robotic fingers are discussed. Performance characteristics are outlined as referring to several aspects of finger mechanisms. Optimality criteria of the finger performances are formulated after careful analysis. A general design algorithm is summarized and formulated as a suitable multi-objective optimization problem. A numerical case of an underactuated robot finger design for Laboratory of Robotics and Mechatronics (LARM) hand is illustrated with the aim to show the practical feasibility of the proposed concepts and computations.

Grasp planning analysis and strategy modeling for underactuated multi-fingered robot hand using in fruits grasping

To solve the unfixed grasping tasks during the fruits picking and rating, grasping modeling is researched as the most important part of the robot hand solutions. A survey for grasping synthesis method with dexterous robot hand is presented in this paper. The difference of grasping characters is introduced between dexterous hand and underactuated hand. Especially, the feature of self-adaptive enveloping grasp achieved by underactuated finger mechanism is outlined, which has good performance in grasping unknown objects. In order to generate valid grasps for unknown target objects and apply in real-time control system for underactuated robot hand, a grasping strategy synthesis model for universal grasp tasks is proposed based on human knowledge analysis. It is composed by off-line neural networks training section and on-line compute section. Firstly, daily grasped objects are used to build a sample space by human experience. Then the discrete sample space is computed by fuzzy clustering method. The data is used to generate grasp decision scheme by rough set mixed artificial neural networks. An examination is simulated for grasp configurations choice of the underactuated robot hand with the aim to show the practical feasibility of the proposed grasp strategy. Key words: Underactuated robot hand, grasp planning, neural network, fruits grasping.