The detection of small forces is of great interest in any robotic application that involves interaction with the environment (e.g., objects manipulation, physical human-robot interaction, minimally invasive surgery), since it allows the robot to detect the contacts early on and to act accordingly. In this letter, we present a sensor design inspired by the ciliary structure frequently found in nature, consisting of an array of permanently magnetized cylinders (cilia) patterned over a giant magnetoresistance sensor (GMR). When these cylinders are deformed in shape due to applied forces, the stray magnetic field variation will change the GMR sensor resistivity, thus enabling the electrical measurement of the applied force. In this letter, we present two 3 mm × 3 mm prototypes composed of an array of five cilia with 1 mm of height and 120 and 200 μm of diameter for each prototype. A minimum force of 333 μN was measured. A simulation model for determining the magnetized cylinders average stray magnetic field is also presented.

Back and spine-related issues are frequent maladies that most people have or will experience during their lifetime. A common and sensible observation that can be made is regarding the posture of an individual. We present a new approach that combines accelerometer, gyroscope, and magnetometer sensor data in combination with permanent magnets assembled as a wearable device capable of real-time spine posture monitoring. An independent calibration of the device is required for each user. The sensor data is processed by a probabilistic classification algorithm that compares the real-time data with the calibration result, verifying whether the data point lies within regions of confidence defined by a computed threshold. An incorrect posture classification is considered if both accelerometer and magnetometer classify the posture as incorrect. A pilot trial was performed in a single adult test subject. The combination of the magnets and magnetometer greatly improved the posture classification accuracy (89%) over the accuracy obtained when only accelerometer data were used (47%). The validation of this method was based on image analysis.

The detection of force with higher resolution than observed in humans (~1 mN) is of great interest for emerging technologies, especially surgical robots, since this level of resolution could allow these devices to operate in extremely sensitive environments without harming these. In this work, we present a force sensor fabricated with a miniaturized footprint (9 mm $$^{2} ), based on the detection of the magnetic field generated by magnetized flexible pillars over a giant magnetoresistive sensor. When these flexible pillars deflect due to external preloads, the stray field emitted by these will change, thus varying the GMR sensor resistance. A sensor with an array of 5 pillars with 200 μm diameter and 1 mm height was fabricated, achieving a 0 mN to 26 mN measurement range and capable of detecting a minimum force feature of 630 μN. A simulation model to predict the distribution of magnetic field generated by the flexible pillars on the sensitive area of the GMR sensor in function of the applied force was developed and validated against the experimental results reported in this work. The sensor was finally tested as a texture classification system, with the ability of differentiating between 4 distinct surfaces varying between 0 μm and 162 μm RMS surface roughness.

Tactile sensing is crucial for robots to manipulate objects successfully. However, integrating tactile sensors into robotic hands is still challenging, mainly due to the need to cover small multi-curved surfaces with several components that must be miniaturized. In this paper, we report the design of a novel magnetic-based tactile sensor to be integrated into the robotic hand of the humanoid robot Vizzy. We designed and fabricated a flexible 4 × 2 matrix of Si chips of magnetoresistive spin valve sensors that, coupled with a single small magnet, can measure contact forces from 0.1 to 5 N on multiple locations over the surface of a robotic fingertip; this design is innovative with respect to previous works in the literature, and it is made possible by careful engineering and miniaturization of the custom-made electronic components that we employ. In addition, we characterize the behavior of the sensor through a COMSOL simulation, which can be used to generate optimized designs for sensors with different geometries.

We present the fabrication process and characterization of a tunnel magnetoresistance sensor based monolithic device assembled in a Wheatstone bridge architecture, capable of measuring magnetic field in both planar sensitive directions simultaneously. This process is simplified in comparison with other fabrication strategies, as it does not require annealing or the usage of auxiliary structures to achieve 2D sensitivity, by using amorphous ${\rm{AL_{2}O_{x}}}$ tunnel barriers combined with Ni-Fe and Co-Fe-B electrodes and Mn-Ir as bias exchange material to define sensors sensitivity to orthogonal directions in the wafer plane. The used fabrication process achieved a maximum sensitivity of 16.1 mV/V/mT. A proof-of-concept device as an angular sensor was also performed, reaching an RMS error of 1.5°.