Experimental characterization of a flexible thermal slip sensor

A Microfabricated Dual Slip-Pressure Sensor with Compliant Polymer-Liquid Metal Nanocomposite for Robotic Manipulation

Conventional grippers fall behind their human counterparts as they do not have integrated sensing capabilities. Piezoresistive and capacitive sensors are popular choices because of their design and sensitivity, but they cannot measure pressure and slip simultaneously. It is imperative to measure slip and pressure concurrently. We demonstrate a dual slip-pressure sensor based on a thermal approach. The sensor comprises two concentric microfabricated heaters maintained at constant temperature. An elastic dome, with embedded liquid metal droplets, is placed on top of concentric heaters. Heat transfer between sensor and the object in contact occurs through the elastic dome. This heat transfer causes changes in the power absorbed by the sensor to maintain its temperature and allows for measurement of pressure while identifying slip events. Liquid metal droplets contribute to enhanced thermal conductivity (0.37 W/m-K) and reduced specific heat (0.86 kJ/kg-K) of the polymer without compromising on mechanical properties (Young's modulus-0.5 MPa). For pressure monitoring, sensor measures change in power ratio against increase in applied force, demonstrating a highly linear performance, with a high sensitivity of 0.0356 N^-1 (pressure only) and 0.0189 N^-1 (slip with simultaneous pressure applied). The sensor discriminates between different contact types with a 96% accuracy. Response time of the sensor (60-75 ms) matches the measured response time in human skin. The sensor does not get affected by mechanical vibrations paving way for easy integration with robotic manipulators and prosthetics.

A Novel Event-Based Incipient Slip Detection Using Dynamic Active-Pixel Vision Sensor (DAVIS)

In this paper, a novel approach to detect incipient slip based on the contact area between a transparent silicone medium and different objects using a neuromorphic event-based vision sensor (DAVIS) is proposed. Event-based algorithms are developed to detect incipient slip, slip, stress distribution and object vibration. Thirty-seven experiments were performed on five objects with different sizes, shapes, materials and weights to compare precision and response time of the proposed approach. The proposed approach is validated by using a high speed constitutional camera (1000 FPS). The results indicate that the sensor can detect incipient slippage with an average of 44.1 ms latency in unstructured environment for various objects. It is worth mentioning that the experiments were conducted in an uncontrolled experimental environment, therefore adding high noise levels that affected results significantly. However, eleven of the experiments had a detection latency below 10 ms which shows the capability of this method. The results are very promising and show a high potential of the sensor being used for manipulation applications especially in dynamic environments.

Grasping Force Control for a Robotic Hand by Slip Detection Using Developed Micro Laser Doppler Velocimeter

The purpose of this paper is to show the feasibility of grasping force control by feeding back signals of the developed micro-laser Doppler velocimeter (μ-LDV) and by discriminating whether a grasped object is slipping or not. LDV is well known as a high response surface velocity sensor which can measure various surfaces—such as metal, paper, film, and so on—thus suggesting the potential application of LDV as a slip sensor for grasping various objects. However, the use of LDV as a slip sensor has not yet been reported because the size of LDVs is too large to be installed on a robotic fingertip. We have solved the size problem and enabled the performance of a feasibility test with a few-millimeter-scale LDV referred to as micro-LDV (μ-LDV) by modifying the design which was adopted from MEMS (microelectromechanical systems) fabrication process. In this paper, by applying our developed μ-LDV as a slip sensor, we have successfully demonstrated grasping force control with three target objects—aluminum block, wood block, and white acrylic block—considering that various objects made of these materials can be found in homes and factories, without grasping force feedback. We provide proofs that LDV is a new promising candidate slip sensor for grasping force control to execute target grasping.

Studying the magnetic stimulation of nervous tissues: A calculation framework to investigate stimulation areas

The electromagnetic stimulation of nervous tissue has represented an alternative to electrical stimulation since the 1980s. The growing number of potential applications has led to an increasing interest in the development of modeling tools that can help the design of novel electromagnetic stimulators. In this context, the aim of this paper is to provide a versatile calculation framework to investigate the properties of the electric field generated by a plurality of miniature coils, arranged in cuff configuration. Furthermore, the capability of the miniature coils to elicit a neuronal response in specific portions of the (peripheral) nerve will be investigated. Starting from Jefimenko's equations, a model was implemented in MATLAB. It calculates the electromagnetic field induced by coils, with arbitrary shape and spatial orientation, and the activating function around the coils through simple numerical integration. By studying the activating functions, it is possible to determine where the neurons can be excited. The model was validated by comparison with FEM simulations. A dimensional analysis was conducted to compare in terms of shape and depth of the stimulation volumes different coil geometries, regardless of design parameters such as current, number of turns and coil sizes.The dimensionless groups identified according to Buckingham's theorem provide a direct estimate of the stimulation depth reached within the nerve.The calculation tools developed in this paper can be used in the design of coils to quickly compare different geometries and spatial distribution of coils in order to identify the optimal configurations for the specific application addressed by the designer.

A theoretical framework for studying the electromagnetic stimulation of nervous tissue

In this paper we present a model for calculating the electric field, and its spatial derivatives, produced by arbitrarily shaped, oriented and placed coils carrying time-varying currents. The model has been validated by comparing its results with those obtained using FEM simulations. The model provides a simple and fast computation framework to investigate the electromagnetic stimulation of neural tissues. Some example applications are also provided.