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

Design and Fabrication of a Thin and Micro-Optical Sensor for Rapid Prototyping

Optical sensing offers several advantages owing to its non-invasiveness and high sensitivity. The miniaturization of optical sensors will mitigate spatial and weight constraints, expanding their applications and extending the principal advantages of optical sensing to different fields, such as healthcare, Internet of Things, artificial intelligence, and other aspects of society. In this study, we present the development of a miniature optical sensor for monitoring thrombi in extracorporeal membrane oxygenation (ECMO). The sensor, based on a complementary metal-oxide semiconductor integrated circuit (CMOS-IC), also serves as a photodiode, amplifier, and light-emitting diode (LED)-mounting substrate. It is sized 3.8 × 4.8 × 0.75 mm3 and provides reflectance spectroscopy at three wavelengths. Based on semiconductor and microelectromechanical system (MEMS) processes, the design of the sensor achieves ultra-compact millimeter size, customizability, prototyping, and scalability for mass production, facilitating the development of miniature optical sensors for a variety of applications.

Current State of Knowledge in Ocular Blood Flow in Glaucoma: A Narrative Review

Glaucoma is a multifactorial disease that is dependent on Intra Ocular Pressure (IOP) and associated with risk factors related to reduced ocular blood flow (OBF). In clinical practice, it is instrumental to update and review the considerable evidence of the current imaging technologies utilized in the investigation of OBF involved in both the onset and progression of glaucoma. Bibliographic databases, including PubMed and Google Scholar, were searched for articles on OBF techniques published between 2018 and 2023 using keywords such as "ocular blood flow", "glaucoma", "invasive ocular blood flow measurement", and "non-invasive ocular blood flow measurement". All types of methodologies were considered, except for editorials, letters to the editor, and animal studies. This review provides comprehensive information on the recent state-of-the-art imaging innovations used to monitor and measure the ocular blood flow in glaucoma.

Fabrication and Experimental Validation of a Sensitive and Robust Tactile Sensing Array with a Micro-Structured Porous Dielectric Layer

The development of pressure sensors of high sensitivity and stable robustness over a broad range is indispensable for the future progress of electronic skin applicable to the detection of normal and shear pressures of various dynamic human motions. Herein, we present a flexible capacitive tactile sensing array that incorporates a porous dielectric layer with micro-patterned structures on the surface to enable the sensitive detection of normal and shear pressures. The proposed sensing array showed great pressure-sensing performance in the experiments, with a broad sensing range from several kPa to 150 kPa of normal pressure and 20 kPa of shear pressure. Sensitivities of 0.54%/kPa at 10 kPa and below, 0.45%/kPa between 10 kPa and 80 kPa, and 0.12%/kPa at 80 kPa and above were achieved for normal pressures. Meanwhile, for shear pressures, sensitivities up to 1.14%/kPa and 1.08%/kPa in x and y directions, respectively, and below 10 kPa, 0.73%/kPa, and 0.75%/kPa under shear pressure over 10 kPa were also validated. The performance of the finger-attached sensing array was also demonstrated, demonstrating which was a potential electronic skin to use in all kinds of wearable devices, including prosthetic hands, surgical robots, and other pressure monitoring systems.

Design of a fuzzy safety margin derivation system for grip force control of robotic hand in precision grasp task

In this study, the aim was to grasp and lift an unknown object without causing any permanent change on its shape using a robotic hand. When people lift objects, they add extra force for safety above the minimum limit value of the grasp force. This extra force is expressed as the “safety margin” in the literature. In the conducted study, the safety margin is minimized and the grasp force was controlled. For this purpose, the safety margin performance of human beings for object grasping was measured by the developed system. The obtained data were assessed for a fuzzy logic controller (FLC), and the fuzzy safety margin derivation system (SMDS) was designed. In the literature, the safety margin rate was reported to vary between 10% and 40%. To be the basis for this study, in the experimental study conducted to measure the grip performance of humans, safety margin ratios ranging from 9% to 20% for different surface friction properties and different weights were obtained. As a result of performance tests performed in Matlab/Simulink environment of FLC presented in this study, safety margin ratios ranging from 8% to 21% for different surface friction properties and weights were obtained. It was observed that the results of the performance tests of the developed system were very close to the data of human performance. The results obtained demonstrate that the designed fuzzy SMDS can be used safely in the control of the grasp force for the precise grasping task of a robot hand.

Force transmission analysis of surface coating materials for multi-fingered robotic grippers

Robotic systems are generally used for grasping, carrying, holding, and many similar operations, typically in industrial applications. One of the most important components of robotic systems is robot grippers for the aforementioned operations, which are not only mission-critical but also represent a significant operational cost due to the time and expense associated with replacement. Grasping operations require sensitive and dexterous manipulation ability. As a consequence, tactile materials and sensors are an essential element in effective robot grippers; however, to date, little effort has been invested in the optimization of these systems. This study has set out to develop inexpensive, easily replaced pads, testing two different chemical compositions that are used to produce a tactile material for robot grippers, with the objective of generating cost, time, and environmental savings. Each tactile material produced has its specific individual dimension and weight. First, each of the materials under construction was tested under different constant pressures, and its characteristics were analyzed. Second, each tactile material was mounted on a two-fingered robot gripper and its characteristics. Material characteristics were tested and analyzed as regards their ability to grasp different sizes and types of objects using the two-fingered robot gripper. Based on the analysis of the results the most sensitive and cost-effective material for industrial type multi-fingered grippers was identified.

Fast Visual Tracking Based on Convolutional Networks

Recently, an upsurge of deep learning has provided a new direction for the field of computer vision and visual tracking. However, expensive offline training time and the large number of images required by deep learning have greatly hindered progress. This paper aims to further improve the computational performance of CNT which is reported to deliver 5 fps performance in visual tracking, we propose a method called Fast-CNT which differs from CNT in three aspects: firstly, an adaptive k value (rather than a constant 100) is determined for an input video; secondly, background filters used in CNT are omitted in this work to save computation time without affecting performance; thirdly, SURF feature points are used in conjunction with the particle filter to address the drift problem in CNT. Extensive experimental results on land and undersea video sequences show that Fast-CNT outperforms CNT by 2~10 times in terms of computational efficiency.