Force Sensor Research Articles

Toward Damage-Less Robotic Fragile Fruit Grasping: A Closed-Loop Force Control Method for Pneumatic-Driven Soft Gripper.

Fragile fruit uploading and packaging are labor-intensive and time-consuming steps in postharvest industry. With the aging of the global population, it is supposed to develop robotic grasping systems to replace manual labor. However, damage-less grasping of fragile fruit is the key problem in robotization. Inappropriate grasping force will result in damage, early-stage bruise, or slip. Benefits from the advantages of softness and compliance of a pneumatic-driven soft gripper have been widely adopted for agricultural product and food manipulation. Nevertheless, pneumatic gripper is a complex, multivariable, nonlinear, and long time-delay control system, which is difficult to achieve robust closed-loop grasping force control. In this study, we aim to solve this problem and developed a robotic grasping force control system with pneumatic gripper and matrix force sensor. The force distribution condition was explored to tackle the problem in changing of the main contact point. A double closed-loop control method was proposed based on Kalman filter (KF) and proportion integration differentiation controller with dead band. The external and internal control loops were force controller and air pressure of the pump controller, respectively. The double closed-loop controller with dead band achieved robust grasping force control through air pressure. The experimental results validated the effectiveness of the KF method for denoising and the matrix force visualization method for exploring grasping mechanism. Ablation studies were carried out to demonstrate the effectiveness of the multiple grasping force sensing units in matrix form and the dead band in the controller. The maximum steady-state error was 0.07 N. In addition, the generalization performance and the antidisturbance ability of the grasping force control system was also validated. In summary, the problem in closed-loop control of the grasping force for pneumatic gripper has been solved in our study, and the method in this research is potential to be deployed in fruit postharvest industry.

A capacitive tactile force sensor with mutual fringe effect and parallel plate design for robot assisted surgery

This paper presents a unique design of a single-axis tactile force sensor by a mutual parallel plate and fringing effect of an electric field that is generated between stationary patterned electrodes in the sensor. The proposed sensor can measure the normal and shear forces with high sensitivity and linear response. The capacitive tactile sensor is fabricated by low-cost rapid prototyping techniques using conductive ink for electrode printing that is printed on a polyethylene terephthalate sheet by an inkjet printer. Ecoflex 00-30 and silicone rubber RTV-528 are used as the dielectric medium and dome for force application. A finite element method analysis is performed for deciding the dimensions of the sensor's stationary electrodes. The force measurement ranges of the sensor for the normal and shear axis are 4 N and 2 N, respectively. The proposed tactile sensor shows a highly linear response, which makes it a suitable match for force feedback in robotic surgery.

Influence of clinical risk factors for preterm premature rupture of membranes (PPROM) on the elastic strength of fetal membranes at term: A prospective study.

Premature rupture of membranes (PROM) before 37 weeks of gestation is a common obstetrical event, whose pathophysiology is still poorly understood. Our objective was to study the mechanical strength of fetal membranes in women with a clinical risk factor for preterm premature rupture of membranes (PPROM). We included, in a prospective, descriptive, single-center study, patients scheduled for cesarean section at term (≥ 37 weeks of gestation). For each patient, we performed uniaxial tensile tests on fetal membranes with a universal testing machine equipped with a force sensor (EZ20®, Lloyds), allowing the recording of an applied force/time curve. We collected maximum force (Fmax), maximum stress (σMax), and Young's modulus of elasticity. The thickness of each membrane sample was also measured. We compared the values obtained according to certain clinical risk factors for PPROM such as age, body mass index, gravidity, parity, a history of PPROM or preterm birth, smoking, gestational diabetes, geographic origin, and socioeconomic level. We analyzed 31 patients and found no association between the studied risk factors and σMax. Fmax was lower in primiparous patients (p = 0.02) but increased with patient parity (p = 0.005). Gestational diabetes was associated with a higher Fmax (p = 0.033) and sub-Saharan geographical origin with a greater thickness (p = 0.0043). As membrane thickness increased, σMax (p = 0.009) and Young's modulus decreased (p = 0.037). Primiparous patients have lower membrane mechanical strength than patients who have had one or more deliveries. Mechanically, the thicker membranes are less rigid and less resistant.

Using an electronic balance to measure the kinetic friction coefficient in class experiment

Abstract In this paper, we propose an experimental method for measuring the kinetic friction coefficient using an electronic balance. We measured the kinetic friction coefficient of the wooden block on the paper tape using this method and compared the result with that using the force sensor method. The results of the two methods were in good agreement. This method is convenient and can be implemented in many laboratories, and at the same time it can measure the kinetic friction coefficients between different materials easily. Therefore, it is a simple and practical experimental method for high school students or first-year college students to measure the kinetic friction coefficient in class experiment.

Modular and Fault-Tolerant Three-Axial FBG-Based Force Sensing for Transoral Surgical Robots

Modular and Fault-Tolerant Three-Axial FBG-Based Force Sensing for Transoral Surgical Robots

Machine learning-based risk of fall estimation using insole with force sensors while performing a sequence of activities in the TUG test

Machine learning-based risk of fall estimation using insole with force sensors while performing a sequence of activities in the TUG test

Motion Planning and Control with Environmental Uncertainties for Humanoid Robot

Humanoid robots are typically designed for static environments, but real-world applications demand robust performance under dynamic, uncertain conditions. This paper introduces a perceptive motion planning and control algorithm that enables humanoid robots to navigate and operate effectively in environments with unpredictable kinematic and dynamic disturbances. The proposed algorithm ensures synchronized multi-limb motion while maintaining dynamic balance, utilizing real-time feedback from force, torque, and inertia sensors. Experimental results demonstrate the algorithm’s adaptability and robustness in handling complex tasks, including walking on uneven terrain and responding to external disturbances. These findings highlight the potential of perceptive motion planning in enhancing the versatility and resilience of humanoid robots in uncertain environments. The results have potential applications in search-and-rescue missions, healthcare robotics, and industrial automation, where robots operate in unpredictable or dynamic conditions.

Optical fiber membrane-based Fabry–Perot tactile force sensing platform powered by LED ambient lighting

This study introduces an optical fiber tactile force sensing platform powered by ambient LED lighting. Based on the interaction between a multimode optical fiber and a micro-polymer membrane, it is possible to excite an Extrinsic Fabry-Perot Interferometer (EFPI); this EFPI is pumped by collected incident light from the ambient LED lighting environment; here, a Fresnel lens and multimode fiber collect this light. The collector system maintains suitable light intensity even during 360° rotation. When transversal loads between 0 to 1 N are applied over the membrane, the tactile force sensor shows a wavelength shift towards shorter wavelengths; consequently, a 6.5 nm/N sensitivity and resolution of 0.15 N are obtained. Moreover, the phase analysis of the Fourier spectrum addresses intensity variations during rotation, revealing a sensitivity of 3 rad/N. The sensor offers stability, minimal hysteresis, minimal temperature modulation, and suitable time response across four sensing areas. Moreover, the statistical analysis and tactile force sensor performance ensure reliable tactile measurement with a null probability of overlap upon force application. It is crucial to note that this tactile force sensor provides a genuinely low-cost implementation due to the utilization of ambient LED lighting as the light source. This aspect represents an exciting advancement in fiber sensing technology.

Interactive Haptic System with Multimodal Tactile Sensing and Hydraulic Feedback for Realistic Human–Machine Interaction

With the increasing demand for immersive haptic experiences, multimodal tactile sensing and feedback have become crucial for enhancing user interaction. In this work, an interactive haptic system comprising a robotic hand and wearable tactile feedback device is introduced to facilitate tactile information exchange between humans and robots. The robotic hand, equipped with force and temperature sensors, mimics human movements through vision recognition and captures detailed tactile data. The data are then transmitted to the user through a hydraulic feedback device, providing realistic touch sensations. The dual capabilities of the hydraulic mechanism to simultaneously simulate both pressure and temperature sensations simplify the device structure and enhance reliability compared to systems that require multiple tactile actuators. The force feedback system delivers pressures ranging from 0.5 to 10.5 N across five levels while the temperature feedback mechanism provides thermal sensations ranging from 3 to 50 °C across three levels. Extensive experimental validations demonstrate the system's effectiveness in applications such as remote robotic surgery and telepresence, enabling users to perceive real‐time contact pressure and temperature during remote manipulation tasks. The proposed system, capable of delivering multimodal tactile feedback through a single actuator, represents a significant step toward more immersive and realistic haptic experiences, highlighting its broad applicability.

Untangling the Relationship Between AI‐Mediated Informal Digital Learning of English (AI‐IDLE), foreign Language Enjoyment and the Ideal L2 Self: Evidence From Chinese University EFL Students

ABSTRACTArtificial intelligence‐mediated informal digital learning of English (AI‐IDLE) might strengthen second language (L2) learners' motivational self‐concept (e.g., the ideal L2 self) and enhance their foreign language enjoyment (FLE) by enabling them to build confidence, engagement, and willingness to practice their English skills in a self‐directed, instant feedback, and non‐judgemental learning environment. In our explanatory mixed‐method study, we collected questionnaire data from 299 Chinese undergraduate English as a foreign language (EFL) learners and interviewed 12 of them. Structural equation modelling showed that students who participated in AI‐IDLE more often reported a clearer ideal L2 self and greater FLE, but those with a greater ideal L2 self did not report more FLE. In addition, gender did not moderate the impact of AI‐IDLE on FLE. Analysis of the interview data not only corroborated the quantitative results but also highlighted that while EFL learners can acquire a sense of FLE and vivid ideal L2 selves as they agentively negotiate the affordances of generative AI for informal language learning purposes, the sense of FLE and motivational force may shift across contexts to shape their continued investment in AI‐IDLE practices. By comparing and integrating the quantitative and qualitative insights, this study highlights the pedagogical potential of AI‐IDLE activities that can strengthen EFL learners' motivation, enjoyment, and commitment to English learning.

Design and application of a new high-performance flexible six-axis force/torque sensor for massage therapy

Precise sensing of force magnitude and direction in massage therapy can significantly enhance treatment effectiveness. Despite advancements in flexible multidimensional force sensors, achieving comprehensive spatial force sensing with soft materials remains challenging. This study presents a novel flexible six-axis force/torque sensor, calibrated using a deep neural network. The calibrated sensor exhibits a maximum class I error of 0.603%F.S. and a maximum class II error of 0.751%F.S., indicating excellent measurement performance. Demonstrated in massage physiotherapy, the sensor effectively distinguishes between various techniques and accurately detects subtle force variations within the same technique. The present work introduces a novel strategy for designing flexible six-axis force/torque sensors, thereby laying the groundwork for advancements in intelligent robotics, human–computer interfaces, as well as in the fields of rehabilitation and medicine.

Dynamics Modelling and Adaptive Identification: Towards Improved Human-Robot Interaction in Collaborative Systems

This article presents a novel approach to enhancing human-robot collaboration and safety through advanced dynamic modelling and adaptive identification techniques. We introduce a comprehensive methodology that integrates motion trajectory design with real-time torque detection, addressing the critical limitations of conventional systems that rely on costly joint torque sensors. By simultaneously identifying friction forces in an integrated joint and a simplified two-bar mechanism, our approach leverages existing kinematic and dynamic models to achieve precise dynamic parameter identification. The proposed method significantly advances the fields of drag-teaching and collision detection by eliminating the need for force sensors, thus making it more feasible for mass-produced robotic systems. Our findings demonstrate that accurate dynamic modelling is essential for effective zero-force control, particularly in high-speed drag-teaching scenarios, where inertia and friction present substantial challenges. Experimental validation confirms the efficacy of our dynamic feed-forward controller design and the adaptability of drag-teaching parameters, leading to improved operational flexibility and safety in collaborative environments. This research contributes a critical framework for future developments in intelligent robotic systems, providing a robust basis for integrating advanced human-robot interactions in industrial applications.

Transparency-enhanced observer-based adaptive backstepping torque–position control for teleoperation systems with position error constraint and time-varying delay

Nonlinear teleoperation systems are susceptible to significant problems, including transparency, safety, stability and external torques/forces measurement. In order to deal with these limitations, an observer-based adaptive backstepping torque–position control approach is proposed in this paper. In order to achieve this objective, a novel external torque observer is proposed to alleviate the limitations associated with the use of force sensors. This paper’s main idea is to employ a three-channel architecture using a force sensor-less reflecting signal, which can improve transparency and increase algorithm performance. Furthermore, the another point of this paper is to enhance the safeness of operations in the presence of time-varying delays in the communication channel, a position error constraint control strategy is employed in the core of the proposed approach. Moreover, the primary advantage of this paper is that, the proposed observer-based control algorithm is relieved from the joints acceleration measurement of the leader and follower manipulators which is difficult in robotic systems. Finally, the stability analysis of the controller and observer together is conducted by the Barrier Lyapunov functional and series of simulations, comparisons and practical experiments are performed to validate the performance of the proposed algorithm.

Flexible Piezoelectric Sensor Enhanced by Ordered Piezoelectric Composite Material for Three-Dimensional Force Detection.

With the rapid development of intelligent devices, the demand for high-performance flexible sensors with three-dimensional force perception capabilities has become increasingly prominent. In this study, we utilized dielectrophoresis regulation to achieve an ordered arrangement of lead zirconate titanate particles in piezoelectric composite films, enhancing the pressure sensitivity by approximately 4.06 times compared to randomly distributed composite films. Furthermore, an additional bump structure was constructed to convert three-dimensional forces into different compression states on the sensing units of the film, enabling effective decoupling of three-dimensional forces. Experimental results demonstrated that the three-dimensional piezoelectric force sensor exhibited sensitivity values of 0.2524, 0.1702, and 0.1946 V/N in three directions within the range of 1-9 N. Additionally, the sensor possesses significant advantages such as rapid response (4 ms), good repeatability, and simple manufacturing. These characteristics offer a viable strategy for self-powered wearable devices and human-machine interactions in intelligent devices.

Small-scale magnetic soft robotic catheter for in-situ biomechanical force sensing

Miniaturized magnetic soft robotic catheters offer significant potential in minimally invasive surgery by enabling remote active steering and reduced radiation exposure. However, existing magnetic catheters are limited by the absence of in-situ biomechanical force sensing, which is crucial for controlling the contact force exerted on surrounding tissues during surgical procedures. Here, we report an in-situ force sensing strategy for small-scale magnetic robotic catheters. A coaxial integration of ring-shaped permanent and fibre-based force sensors at the catheter's distal end enables both active steering and precise force measurement. The force sensor is designed to be sensitive exclusively to contact forces perpendicular to its plane, achieving a sensitivity of 0.69 nm/kPa (or 0.38 nm/mN). By manipulating magnetic field patterns, the catheter can actively generate and control contact forces to tissues, using real-time feedback from the force sensor. We demonstrate the system's force-sensing and force-control capability in isolated organs and tissue phantom during passage, verifying the catheter's high force sensitivity and high steerability. The feedback-loop force control enhances procedural safety and efficacy for minimally invasive surgery, making it especially suitable for procedures such as transbronchial microwave ablation of lung nodules and cardiac ablation for atrial fibrillation.

Design, Evaluation, and Implementation of a Novel Magnetic Resonance Imaging-Compatible Physiologic Loading Simulator for Ex-Vivo Joints.

Quantitative magnetic resonance imaging (qMRI), in combination with mechanical testing, offers potential to investigate how loading (e.g., from daily physical exercise) is related to joint and tissue function. However, current testing devices compatible with magnetic resonance imaging (MRI) are often limited to uniaxial compression, often applying low loads, or loading individual tissues (instead of multiple), while more complex simulators do not facilitate MRI. Hence, in this work, we designed, built and tested (N = 1) an MRI-compatible multi-axial load-control system, which enables scanning cadaveric joints (healthy or pathologic) loaded to physiologically relevant levels. Testing involved estimating and validating physiologic loading conditions before implementing them experimentally on cadaver knees to simulate and image gait loading (stance and swing). The resulting design consisted of a portable loading device featuring pneumatic actuators to reach a combined loading scenario, including axial compression (≤2.5 kN), shear (≤1 kN), bending (≤30 N·m) and muscle tension. Initial laboratory testing was carried out; specifically, the device was instrumented with force and pressure sensors to evaluate loading and contact response repeatability in one cadaver knee specimen. This loading system was able to simulate healthy or pathologic gait with reasonable repeatability (e.g., 1.23-2.91% coefficient of variation for axial compression), comparable to current state-of-the-art simulators, leading to generally consistent contact responses. Contact measurements demonstrated a tibiofemoral to patellofemoral load transfer with knee flexion and large contact pressures concentrated over small sites between the femoral cartilage and menisci, agreeing with experimental studies and numerical simulations in the literature.

A high sensitivity, low cost and fully decoupled multi-axis capacitive tactile force sensor for robotic surgical systems.

This paper presents the design of a multi-axis capacitive tactile force sensor with a fully decoupled output response for input normal and shear forces. A patterned elastomer is used as a dielectric layer between capacitive electrodes of the sensor that allows to achieve relatively higher sensitivity. The sensor is fabricated utilizing a low-cost rapid prototyping technique and is characterized for normal and shear forces in the range of 0 ~ 10 N and 0 ~ 3.1 N respectively. The achieved force sensitivity for the normal axis is 2.03%/N and for shear axes is 1.67%/N. The difference between the estimated force from the sensor and actual force applied is negligible, which demonstrates the accuracy of the sensor. The reliability of the sensor is analysed by performing hysteresis and repeatability tests. The hysteresis error is found to be 4.94% and 4.69% for normal and shear forces respectively. The repeatability error of the sensor is less than 5%, which shows the stability of the sensor. The high sensitivity, linear output response, high force measurement range, reliability and low cost make the proposed tactile sensor suitable for the force feedback in the robotic surgical systems.

Artificial mechano-nociceptive system based on transparent ITO/AlN/ITO memristor nociceptor neuron

Artificial nociceptors demonstrate significant potential in emerging fields such as intelligent prosthetics, humanoid robotics, and electronic skin, capable of transducing external noxious stimuli to the central nervous system. Unlike common sensory neurons, nociceptors exhibit unique characteristics, including “no adaptation,” “relaxation,” “threshold firing,” and “sensitization of allodynia/hyperalgesia.” This study presents a forming-free volatile transparent ITO/AlN/ITO memristor that emulates biological nociceptor behaviors. Leveraging this artificial nociceptor, an artificial mechano-nociceptive system is developed by integrating the ITO/AlN/ITO memristor into a piezoelectric force sensor system for pain sensing and noxious stimuli warning. This research contributes to the advancement of human cognitive capability emulation and artificial intelligence systems, particularly in the domain of pain perception and response.

Position–Force Control of a Lower-Limb Rehabilitation Robot Using a Force Feed-Forward and Compensative Gravity Proportional Derivative Method

The design and control of lower-limb rehabilitation robots for patients after a stroke has gained significant attention. This paper presents the dynamic analysis and control of a 3-degrees-of-freedom lower-limb rehabilitation robot using combined position–force control based on the force feed-forward and compensative gravity proportional derivative methods. In the lower-limb rehabilitation robot, the interaction force between the patient with the joints and links of the robot is uncertain and nonlinear due to the disturbance effect of Coriolis force, centrifugal force, gravitational force, and friction force. During recovery stages, the forces exerted by the patient’s lower limbs are also considered disturbances. Therefore, to meet the quality requirements in using the rehabilitation robot with different recovery stages of patient training, combining position control and force control is essential. In this paper, we proposed a combination of proportional–derivative gravity compensation motion control and force feed-forward control to form an advanced combined controller (position–force feed-forward control—PFFC) for a 3 DOF lower-limb functional rehabilitation robot. The forces can be sensed using a 3-axis force sensor. In addition, the robot’s position parameters are also measured by encoders. The control algorithm is implemented on the STM32F4 Discovery board. A verified test of the proposed control method is shown in the experiments, showing the good performance of the system.

Abstract 4134945: Biomechanical Impact of Crossing Neochords In Mitral Valve Repair Using Ex Vivo Mitral Valve Prolapse Models

Background: Neochord repair is a common technique to mitigate mitral regurgitation (MR). Certain techniques, such as the loop technique, purposefully anchor all neochords to one papillary muscle head, generating crossed configurations. The objective was to evaluate the impact of crossing neochord on mitral valve (MV) biomechanics using ex vivo mitral valve prolapse (MVP) models. Methods: Twenty-four healthy porcine MVs were explanted. The valves were randomly assigned to generate A2 or P2 MVP models by transecting A2 or P2 primary and secondary native chords. For each model, the valves were further randomly assigned to neochord repair by crossing the medial-lateral plane or the anterior-posterior plane. Fiber Bragg grating force sensors were mounted to measure chordal forces. Data were collected using an ex vivo heart simulator for baseline, MVP, and neochord repair in the native and the crossed configuration. Statistical analysis was performed using repeated measures analysis of variance with post-hoc correction. Results: In the P2 MVP model, AP crossed configuration was effective in reducing MR (p=.003) compared with the native configuration (p=.004), but the medial-laterally (ML) crossed configuration was not effective in reducing MR (p=.07) compared with the native configuration (p=.05). In the A2 MVP model, anterior-posteriorly crossed configuration was associated with increased average neochordal force compared with the native configuration (0.16±0.06N vs. 0.09±0.07N, p=.05). The ML crossed configuration was also associated with increased average neochordal force compared with the native configuration (0.05±0.03N vs.0.03±0.03N, p=.03). Peak native secondary chordal forces were increased in the ML crossed configuration compared with the native configuration (0.76±0.45N vs. 0.61±0.38N, p=.05). No differences between the crossed and native configurations were observed in the P2 MVP model. Conclusions: Differences exist in P2 MVP model hemodynamics and A2 MVP model chordal forces when neochords were crossed compared with the native configurations. These findings may provide important biomechanics insight regarding neochord implantation techniques and repair durability.