Tactile sensors enabling human-like perception are crucial for modern intelligent robotics. This study developed a biomimetic magnetostrictive tactile sensor consisting of Galfenol wires, permanent magnets, and a Hall sensor. This novel tactile sensor exhibits a static sensitivity of 23.86 mV/N and a measurement range up to 3 N. The sensitivity is stable up to 4 Hz. A theoretical model of the tactile sensor unit was derived to correlate the output voltage with the applied force. The modeling result shows an error of 1.65% in sensitivity compared to the experimental data. The response time and recovery time of the sensor are only 11 ms and 10 ms, faster than nanoscale type of sensor. A 3×3 magnetostrictive sensor array was constructed by integrating multiple magnetostrictive tactile sensors on a flexible printed circuit board. Since the outputs of the sensing units are not affected by each other, the array can be expanded as needed. Experimental results show that the sensor array is able to detect the geometry of the object in contact.

A new high-sensitivity magnetostrictive tactile sensor array is designed based on the inverse magnetostrictive effect and tunnel magnetoresistance to enable intelligent robots to have a sensitive sense of touch and perform delicate operations. The output voltage model of the tactile sensor is developed. The optimal bias field and spacing of the sensor unit are determined using COMSOL Multiphysics. Test platforms for static and dynamic characteristics are built. The output characteristics of the tactile sensor under static and dynamic forces are tested. The sensitivity is compared with that of other types of tactile sensors. The tactile sensor units are set into a $2\times3$ sensor array and the coupling effect of the output voltage of each unit in the array is tested. The experimental results show that the experimental value of the output voltage matches the calculated value with a maximum error of 3.47%. The sensitivity of the tactile sensor is 323 mV/N at 0–4 N static force, which is higher compared to other types of tactile sensors. The sensitivity of the sensor unit changes less than 1.15% at 1–4 Hz dynamic force. The interaction of output voltage between units in the $2\times3$ tactile sensor array does not exceed 1.5% and is negligible. The $2\times3$ tactile sensor array is attached to a three-finger manipulator for grasping objects with a different hardness. The results of the study have guiding significance to the design of high-sensitivity tactile sensors for intelligent robots.

According to the actual operation conditions, a kind of high-frequency losses testing system of magnetostrictive materials under dc bias is built. The dynamic hysteresis loops for Terfenol-D samples at different ac driving frequencies and magnetic densities are studied experimentally under variable dc bias excitation. The magnetic energy losses are obtained from these dynamic hysteresis loops. The three-variable magnetic energy loss matrix is established by these measured data. On the basis of Bertotti loss separation theory, the high-frequency losses calculating model of magnetostrictive materials considering variable dc bias excitation is proposed by using the algorithm of Levenberg–Marquardt and the method of matrix transformation. In this model, according to the multivariate parametric regression, the loss coefficients are modified by introducing dc bias-related terms. The loss comparison at different operating conditions shows that the computed results in this proposed model are in good agreement with the experimental ones.

This paper presents a fully coupled, nonlinear electromagnetic-mechanical-thermal model for Terfenol-D devices which include active magnetostrictive materials and passive components. The model includes two parts: (1) a material-level discrete energy-averaged model (DEAM) to describe the magnetomechanical coupling and thermal effect of Terfenol-D and (2) a system-level finite element model formulated in weak form using Maxwell's equations, Newton's law, and heat transfer equations. The objective is to describe the electromagnetic, mechanical, and thermal dynamics of the device. The system finite element model is constructed in COMSOL Multiphysics, and the nonlinear behavior of Terfenol-D is coupled through lookup tables generated by the DEAM. Preliminary results of the output capacity of a Terfenol-D actuator with respect to ambient temperature are presented in terms of blocked force, free displacement, and output power. The blocked force and free displacement decrease by 8.0% and 29.8%, respectively, for a 12 A (RMS) excitation current, as the temperature increases from 20 °C to 180 °C. One of the key contributions of this study is that it accounts for both the temperature-dependent Terfenol-D properties and the thermal effects of surrounding passive systems.

A magnetostrictive tactile sensor unit with a large force measurement range and high sensitivity is designed using L-shaped Galfenol wires, tunnel magnetoresistive elements, and cylindrical permanent magnets. The output voltage model of the sensor unit is established based on the inverse magnetostrictive effect, tunnel magnetoresistance, and elastodynamic theory. Structures of the sensor unit and array are optimized using COMSOL. The static, dynamic, and temperature characteristics are tested. The interaction between the output voltages of each unit in a $3\times $ 3 tactile sensor array is described. The experimental results show that the sensitivity of the sensor unit is 85.5 mV/N at 0-10 N and 28.4 mV/N at 10-16 N under a biased magnetic field of 1.671 kA/m. The dynamic force sensitivity of the sensor unit does not vary by more than 1.4%. The magnetic field lateral coupling and longitudinal coupling of the sensor array do not exceed a maximum of 2.3%. The array can accurately distinguish the force distribution when multiple contacts are subjected to force at the same time. The sensitivity does not vary by more than 3.9% over the ambient temperature range of 23- $59~^{\circ }\text{C}$ . The tactile sensor array is mounted on the mechanical fingertips to grasp bar-shaped objects with different tilt angles. The output voltage of the sensor array obtained from the robotic grasping experiments is analyzed using Probabilistic Neural Network, which can determine the tilt angle of the grasped objects, and the accuracy rate of object tilt recognition is 96.74%.

To enable robots to perform precise operations, it is essential to equip them with extensive electronic skin to enhance their perceptual capabilities for sensing external information. Mimicking the structure of human skin, we have designed a flexible tactile electronic skin array capable of timely responses to external tactile stimuli. The electronic skin features a sandwich structure, comprising magnetic thin film, a silicone buffer layer, and tunnel magnetoresistive elements. Experiments on point pressure, point distance, and point angle are used to understand the basic characteristics of the magnetic sensing element, and the size of the position sensing unit is determined with COMSOL simulation. The size of the array can be expanded as necessary, based on specific requirements and practical considerations. Based on the flexible tactile electronic skin array, we propose a novel position recognition method that utilizes the co-coupling of multiple magnetic sensing elements to determine the position information of contact forces. We designed a 10×10 grid experiment using CNNs to classify each grid position, and the results show a recognition accuracy of 91.2% and a resolution of 1mm.