Fingertip Force Sensor Research Articles

Highly sensitive and easy-to-attach wearable sensor for measuring finger force based on curvature changes in an ellipse-shaped finger ring

Technologies for digitizing worker actions to enhance human labor tasks, mitigate accidents, and prevent disabling injuries have garnered significant attention. This study focuses on monitoring the force exerted by the fingers and developing a wearable fingertip force sensor based on a simple elliptical ring structure in conjunction with a commercially available resistive bend sensor. Resembling a ring accessory, the sensor is easy to attach and detach, and exhibits high sensitivity, with a resistance change of approximately 9% for a fingertip load of 1 N. Furthermore, to mitigate crosstalk during finger flexion, we propose a combined configuration employing this ring-shaped sensor alongside another sensor designed for measuring and rectifying finger flexion angles. Additionally, we introduce an empirically derived fitting function and a straightforward calibration procedure to extract the function’s parameters. The proposed system achieves an average RMS error of 0.53 N for force estimations of approximately 5 N, even during finger flexion and postural changes.

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.

Design, Analysis, and Experiment of an Underactuated Robotic Gripper Actuated by Linear Series Elastic Actuator

Abstract The primary motivation of this study is to develop a cost-effective, safe, easily controlled, and passively adaptive robotic gripper. A novel linear series elastic actuated robotic gripper (LSEA-RG) is proposed to accomplish the aforementioned goals. The LSEA-RG has the ability to adaptively grasp objects with different shapes and sizes by grasping force control. First, the mechanical design, including the transmission scheme, the finger mechanism, and the actuating mechanism is presented. Subsequently, the kinematic analysis is performed to explore the transmission characteristic of the actuating displacement and force. Then a model-free control method based on the lookup functions of the kinematic transmission characteristics is presented to achieve the grasping range and force control. Finally, several grasping experiments are carried out based on the LSEA-RG prototype to evaluate the grasping performance. The results demonstrate that the presented grasping control method which based on the lookup functions is valid. The LSEA-RG could estimate the grasping force without the help of a fingertip force sensor and grasp objects with different shapes and hardness adaptively.

Design and Characterization of a New Soft Fingertip Force Sensor for Precision Robotic Grasping Task

Nowadays, a new robotic field has emerged, called Soft Robotics, and it is a new field that involves new challenges, such as soft manipulation, considering external force measure or contact sensors. Thus, in this paper, a new soft fingertip force sensor is introduced. The methodology proposed consists in a quantitative applied research aiming to propose a device able to detect and measure external applied forces. In order to reach the above target, the following steps have been performed: i.) requirements identification, ii) transductor selection, ii) rigid structure design, iii.) soft structure design, iv.) definition of variables parameters for sensor characterization, v.) implementation of the experiments to quantify the relation between external forces and output voltage for different operation conditions, and vi.) proposition of the mathematical model. The mathematical model is defined to describe applied external force and sensor output voltage, demonstrating different mathematical models for two soft materials (polyaddition and polycondensation silicones). It has been found out that using a softer silicone increases the sensor sensitivity. However, the selection of silicone depends on the application requirements. Moreover, the use of soft materials gives a high compliance level with contact objects. On the other hand, a new sensor structure that could be implemented using a 3D print and a FSR traductor, easily implemented by a 3D Printer, has been proposed. Then the mathematical model presented could be used by researchers Moreover, researchers could modify the parameters explained in order to obtain different soft sensor performance. Thus, the soft sensor is endowed with versatility, compliance, and molding.

Design and Experiment of an Anthropomorphic Robot Hand for Variable Grasping Stiffness

This paper introduces an anthropomorphic robot hand that has variable grasping stiffness to unknown objects without damage. The robot hand has four fingers, 13 DoFs (Degrees of Freedom) with three SEA (Series Elastic Actuator) modules in the index, middle, and ring finger. The performance for broader grasping stiffness using variable impedance control based on the parameter update block and the procedure of grasping capability evaluations of the robot hand are explained. The robot finger modules are constructed with a thumb, index, middle, and ring finger to complete the anthropomorphic type robot hand. The robot finger module has three DoFs and functions as one actuator based on an under-actuated mechanism. Additionally, external force measurement is possible in the fingertip force sensor and SEA (Series Elastic Actuator) module. For the variable impedance control implementation, a parameter update block is added to adjust the desired impedance parameter. To implement the parameter update block, we define and evaluate the correlation equation between the fingertip force, shore hardness, and damping ratio.

Qualitative Stability Analysis of Soft Hand Exoskeleton Based on Tendon-driven Mechanism

There exist several hand exoskeletons systems that provide assistive force to the user for strength enhancement or rehabilitation. However, the lack of stability analyses for such systems has made it difficult to ensure that these systems can apply assistance forces corresponding to the user’s intended motion. In this study, a tendon-driven soft hand exoskeleton was developed to provide assistive grip force, and the qualitative stability condition of the system was investigated during system operation. The proposed exoskeleton assisted the middle finger, index finger, and thumb, based on the fingertip force estimated using a previously developed fingertip force sensor. This system applies a flexion force for the middle and index fingers, as well as flexion and abduction forces for the thumb. Because the stability of the system is important during the operation of the system, we qualitatively analyzed the stability condition of the system based on the modified form of the generalized unstructured model comprising the user’s finger, exoskeleton, and external environment. An experimental verification of the stability criterion was performed to determine the approximate range of the stably applicable assistance gain. This study is the first to quantify the stability of fingertip sensor-based assistive power being applied to the hand.

Study on fingertip force sensor based on measurement of tendon tension

Study on fingertip force sensor based on measurement of tendon tension

The MUSHA underactuated hand for robot-aided minimally invasive surgery.

Keyhole surgery is characterized by loss of dexterity of surgeon's movements because of the limited workspace, nonintuitive motor skills of the surgical systems, and loss of tactile sensation that may lead to tissue damage and bad execution of the tasks. In this paper, a three-fingered underactuated miniature tool for robot-aided laparoscopic surgery is presented. The design is conceived to realize a closed-hand configuration allowing the insertion of the tool into the abdominal cavity through the trocar in one step and to reach different grasping as well as pushing/holding configurations once in the cavity. Aiming to replicate human hand dexterity and versatility, different solutions for the kinematic structure of the hand are analyzed using quality indices to evaluate the manipulability and stability of the grasp. Furthermore, a first prototype of fingertip force sensor based on fiber Bragg grating (FBG) technology has been realized and tested. The design choices of the prototype are described and discussed with the aid of experiments. The whole concept and the need for such anthropomorphic tool are discussed with surgeons to highlight constraints and potentials in surgical tasks. The feedback by expert surgeons is used to provide specifications and improvements to the kinematics and mechanical design. The investigations of different designs allow identifying the optimal solution to improve grasping and manipulation capabilities. The tests on FBG sensors led to the conclusion that this technology guarantees good performance and can be a good solution for applications in surgical robotics.

An Optical-based Fingertip Force Sensor

This work introduces the design and prototype development of a novel optical-based fingertip force sensor, which is integrated in a bio-mimetic finger for robotic and prosthetic manipulation. Given the optical nature of the sensor, the proposed device is free of any electrical and metal components. Accordingly, the design improves manipulation of objects with high electromagnetic compatibility performance, reducing sensor’s susceptibility in the presence of these disturbances. The sensor has inherently high SNR and low-power consumption. The concept of using simplified and low cost optical based fingertip force sensor for bio-mimetic anthropomorphic fingers has not been widely implemented so far. The sensor is based on a cantilever design combined with a couple of fiber optics and a reflective surface, it is integrated on the distal phalange of a novel bio-mimetic and anthropomorphic robotic finger. Sensor design was performed and optimized throughout a 3D printing process and Finite Element Analysis. The sensor’s sensitivity (0.098V/N), resolution (0.01N), accuracy (3% of full scale output (FS)) and hysteresis (9.24% of FS) were characterized through a calibration processes. Various applications like surgical manipulation or handling in harsh environment (i.e. high voltage, high temperature and explosive environments) will benefit from the proposed sensor’s performance, reliability, simplicity and bio-compatibility.

Study on characteristics evaluation of ring-type fingertip force sensor in various finger postures

Study on characteristics evaluation of ring-type fingertip force sensor in various finger postures

Fingertip Fiber Optical Tactile Array with Two-Level Spring Structure.

Tactile perception is a feature benefiting reliable grasping and manipulation. This paper presents the design of an integrated fingertip force sensor employing an optical fiber based approach where applied forces modulate light intensity. The proposed sensor system is developed to support grasping of a broad range of objects, including those that are hard as well those that are soft. The sensor system is comprised of four sensing elements forming a tactile array integrated with the tip of a finger. We investigate the design configuration of a separate force sensing element with the aim to improve its measurement range. The force measurement of a single tactile element is based on a two-level displacement that is achieved thanks to a hybrid sensing structure made up of a stiff linear and flexible ortho-planar spring. An important outcome of this paper is a miniature tactile fingertip sensor that is capable of perceiving light contact, typically occurring during the initial stages of a grasp, as well as measuring higher forces, commonly present during tight grasps.

Design of an optical soft sensor for measuring fingertip force and contact recognition

Among the various ways to estimate user intention in hand exoskeletons, a contact force measurement is definitely the most straightforward and intuitive method. A force sensor, located at the center of a fingertip usually, hinders the tactile sensation of the user by blocking the contact between an object and the fingertip. To overcome this problem, a soft force sensor with horse shoe shape is utilized to measure the contact force and provide the tactile sensation to the user. This work presents the mechanical design, implementation and evaluation of a soft fingertip force sensor. To maximize tactile sensation of the user, we adopted a horse shoe shape structure to leave the finger pad exposed. An optical sensing mechanism was selected for its relatively fast response compared to other soft sensors. The whole sensor system has a soft exterior providing flexibility and a user-friendly interface. To evaluate the sensor’s performance, we carried out sensor optimization process and calibration experiment with a customized test bed. Then, we investigated both static and dynamic response and observed the mechanical behavior and light intensity changes caused by the cross sectional shape and base/agent ratio of PDMS. Lastly, we applied the proposed sensor to the glove type fingertip force monitoring system. The sensor estimates the index finger tip force with high accuracy (R 2 = 0:96) within 5N range.

Miniature large range multi-axis force-torque sensor for biomechanical applications

A miniature force sensor for the measurement of forces and moments at a human fingertip is designed and realized. Thin silicon pillars inside the sensor provide in-plane guidance for shear force measurement and provide the spring constant in normal direction. A corrugated silicon ring around the force sensitive area provides the spring constant in shear direction and seals the interior of the sensor. To detect all load components, capacitive read-out is used. A novel electrode pattern results in a large shear force sensitivity. The fingertip force sensor has a wide force range of up to 60 N in normal direction, ± 30 N in shear direction and a torque range of ± 25 N mm.

A Two Layered Control Architecture for Prosthetic Grasping

AbstractThis paper presents a two layered control architecture - Superior hand control (SHC) followed by Local hand control (LHC) for an extreme upper limb prosthesis. The control architecture is for executing grasping operations involved in 70% of daily living activities. Forearm electromyogram actuated SHC is for recognition of user’s intended grasp. LHC control the fingers to be actuated for the recognized grasp. The finger actuation is controlled through a proportionalintegral- derivative controller customized with fingertip force sensor. LHC controls joint angles and velocities of the fingers in the prosthetic hand. Fingers in the prosthetic hand emulate the dynamic constraints of human hand fingers. The joint angle trajectories and velocity profiles of the prosthetic hand finger are in close approximation to those of the human finger

A fingertip force sensor for underwater dexterous hand

In order to safely grasp an unknown object and accurately perceive its position in the fingers, a finger-tip force sensor which can detect the force and position simultaneously was developed for the underwater dexterous hand. This paper introduced the finger-tip force sensor model which was built by a cylinder elastic body. The principle of force measuring was analyzed theoretically, which proved the reason- ableness of the structure and the equation was inferred for measuring force. Because of nonlinear and coupling, a feedforward artificial neural network was employed to calibrate the sensor utilizing the data which were obtained from the tests. The characteristic tests of the sensor showed the maximum error was below 6% in force measurements and the maximum position error was Ф1.6 mm. Then, the ap- plication experiments were carried out and the results showed the finger system can track the expectation of force trajectory, which indi- cated measurement accuracy of the sensor met the demands of research on the underwater dexterous hand. What's more, the sensor struc- ture can compensate the effect of water pressure. So the sensor can be integrated into the finger of the underwater manipulator and used under the water.

A Potential 4-D Fingertip Force Sensor for an Underwater Robot Manipulator

The latest generation of underwater robots employ manipulators without force sensors. Accordingly, this paper presents a novel 4-D fingertip force sensor based on an E-type membrane for underwater robot manipulators. Specifically, this sensor is aimed at obtaining the accurate interaction force between underwater robot manipulators and other objects. Moreover, a seal technique and natural pressure compensation for the sensor are also described. The experimental results demonstrate strong linearity, high sensitivity, and weak couplings.

The Research on the Static Calibration of Fingertip Force Sensor for Underwater Dexterous Hand on RBF Neural Network

The fingertip force sensor is the key for the complex task of the dexterous underwater hand, in order to safely grasp an unknown object using the dexterous underwater hand and accurately perceive its position in the fingers, a sensor should be developed, which can detect the force and position simultaneously. Furthermore, this sensor should be used underwater. It is difficult to employ the accustomed calibration method for the characteristic of the fingertip force sensor, and the accustomed method is not able to assure the precision. A calibration method based on RBF (Radial-Basis Function) neural network is introduced. Furthermore, the calibration system and program are also designed. The calibration experiment of the sensor is carried out. The results show the nonlinear calibration method based on RBF neural network assure the precision of the sensor, which meets the demand of research on the underwater dexterous hand.

Experiments in robotic sensorimotor control during grasp

A series of experiments is presented, using a robot manipulator, which attempts to reproduce human sensorimotor control during grasping. The work utilizes a multifingered, dextrous robot hand equipped with a fingertip force sensor to explore dynamic grasp force adjustment during manipulation. The work is primarily concerned with the relationship between the weight of an object and the grasp force required to lift it. Too weak a grasp is unstable and the object will slip from the hand. Too strong a grasp may damage the object and/or the manipulator. An algorithm is presented which reproduces observed human behavior during grasp-and-lift tasks. The algorithm uses tactile information from the sensor to dynamically adjust the grasp force during lift. It is assumed that there is no a priori knowledge about the object to be manipulated. The effects of different arm/hand postures and object surfaces is explored. Finally, the use of sensory data to detect unexpected object motion and to signal transitions between manipulation phases-with the coincident triggering of new motor programs-is investigated. >