Texture sensing is one of the types of information sensed by humans through touch, and is thus of interest to robotics that this type of information can be acquired and processed. In this work we present a texture topography sensor based on a ciliary structure, a biological structure found in many organisms. The device consists of up to 9 elastic cilia with permanent magnetization assembled on top of a highly sensitive tunneling magnetoresistance (TMR) sensor, within a compact footprint of 6×6 mm2. When these cilia brush against some textured surface, their movement and vibrations give rise to a signal that can be correlated to the characteristics of the texture being measured. We also present an electronic signal acquisition board, used in this work. Various configurations of cilia sizes are tested, with the most precise being capable of differentiating different types of sandpaper from 9.2 μm to 213 μm average surface roughness with a 7 μm resolution. As a topography scanner the sensor was able to scan a 20 μm high step in a flat surface.

The growing consumer demand for large volumes of high quality fruit has generated an increasing need for auto-mated fruit quality control during production. Optical methods have been proved successful in a few cases, but with limitations related to the variability of fruit colors and lighting conditions during tests. Tactile sensing provides a valuable alternative, although it comes with the need of a physical interaction that could damage the fruit. To overcome these limitations, we propose the usage of a recently developed soft tactile sensor for non-invasive fruit quality control. The ability of the sensor to detect very small forces and to finely analyze surfaces allows the collection of relevant information about the fruit by performing a very delicate physical interaction, that does not cause any damage. We report experiments in which such information is used to determine whether apples and strawberries are ripe or senescent. We test different configurations of the sensor and different classification algorithms, achieving very good accuracy for both apples (96%) and strawberries (83%).

In this paper we present a low-cost and easy to fabricate 3-axis tactile sensor based on magnetic technology. The sensor consists in a small magnet immersed in a silicone body with an Hall-effect sensor placed below to detect changes in the magnetic field caused by displacements of the magnet, generated by an external force applied to the silicone body. The use of a 3-axis Hall-effect sensor allows to detect the three components of the force vector, and the proposed design assures high sensitivity, low hysteresis and good repeatability of the measurement: notably, the minimum sensed force is about 0.007N. All components are cheap and easy to retrieve and to assemble; the fabrication process is described in detail and it can be easily replicated by other researchers. Sensors with different geometries have been fabricated, calibrated and successfully integrated in the hand of the human-friendly robot Vizzy. In addition to the sensor characterization and validation, real world experiments of object manipulation are reported, showing proper detection of both normal and shear forces.

This paper describes how magnetoresistive materials can be optimized and integrated in magnetic field sensor devices. Giant magnetoresistive (GMR) and tunnel magnetoresistive (TMR) can provide advantageous solutions for a wide range of applications, of which some are described here. Considerations on field sensitivities, intrinsic noise mechanisms, biasing, and integration schemes are presented.