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The purpose of this study is to explore a signal processing method to improve the angular rate accuracy of micro-electro-mechanical system (MEMS) gyroscope by combining numerous gyroscopes.

To improve the dynamic performance of the signal processing method, the interacting multiple model (IMM) can be applied to the fusion of gyroscope array. However, the standard IMM has constant Markov parameter, which may reduce the model switching speed. To overcome this problem, an adaptive IMM filter is developed based on the kurtosis of the gyroscope output, in which the transition probabilities are adjusted online by utilizing the dynamic information of the rate signal.

The experimental results indicate that the precision of the gyroscope array composed of six gyroscopes increases significantly and the kurtosis-based adaptive Markov parameter IMM filter (K-IMM) performs better than the baseline methods, especially under dynamic conditions. These experiments prove the validity of the proposed fusion method.

The proposed method can improve the accuracy of MEMS gyroscopes without breakthrough on hardware, which is necessary to extend their utility while not restricting the overwhelming advantages.

A K-IMM algorithm is proposed in this paper, which is used to improve the angular rate accuracy of MEMS gyroscope by combining numerous gyroscopes.

The purpose of this paper is to develop a highly miniaturized wireless inertial sensor system based on a novel 3D packaging technique using a flexible printed circuit (FPC). The device is very suitable for wearable applications in which small size and lightweight are required such as body area network, medical, sports and entertainment applications.

Modern wireless inertial measurement units are typically implemented on a rigid 2D printed circuit board (PCB). The design concept presented here is based around the use of a novel planar, six‐faceted, crucifix or cross‐shaped FPC instead of a rigid PCB. A number of specific functional blocks (such as microelectromechanical systems gyroscope and accelerometer sensors, microcontroller (MCU), radio transceiver, antenna, etc.) are first assigned to each of the six faces which are each 1 cm² in area. The FPC cross is then developed into a 1 cm³, 3D configuration by folding the cross at each of five bend planes. The result is a low‐volume and lightweight, 1 cm³ wireless inertial sensor that can sense and send motion sensed data wirelessly to a base station. The wireless sensor device has been designed for low power operation both at the hardware and software levels. At the base station side, a radio receiver is connected to another MCU unit, which sends received data to a personal computer (PC) and graphical user interface. The industrial, scientific and medical band (2.45 GHz) is used to achieve half duplex communication between the two sides.

A complete wireless sensor system has been realized in a 3D cube form factor using an FPC. The packaging technique employed during the work is shown to be efficient in fabricating the final cubic system and resulted in a significant saving in the final size and weight of the system. A number of design issues are identified regarding the use of FPC for implementing the 3D structure and the chosen solutions are shown to be successful in dealing with these issues.

Currently, a limitation of the system is the need for an external battery to power the sensor system. A second phase of development would be required to investigate the possibility of the integration of a battery and charging system within the cube structure. In addition, the use of flexible substrate imposes a number of restrictions in terms of the ease of manufacturability of the final system due to the requirement of the required folding step.

The small size and weight of the developed system is found to be extremely useful in different deployments. It would be useful to further explore the system performance in different application scenarios such as wearable motion tracking applications. In terms of manufacturability, component placement needs to be carefully considered, ensuring that there is sufficient distance between the components, bend planes and board edges and this leads to a slightly reduced usable area on the printed circuit.

This paper provides a novel and useful method for realizing a wireless inertial sensor system in a 3D package. The value of the chosen approach is that a significant reduction in the required system volume is achieved. In particular, a 78.5 per cent saving in volume is obtained in decreasing the module size from a 25 to a 15 mm³ size.

To present the design and control of a low cost, two‐wheeled, self‐balancing robot for detecting and reporting fire and intruders in a small home/office setting.

Implement an intelligent control system to make up for instabilities of low‐cost components.

Biologically inspired suppression system can effectively eliminate undesired sensor noises.

Improving self‐balancing robots' tolerant to impulsive forces from the sides allows them to be designed with smaller front‐prints.

Inherited high maneuverability together with miniature design enables self‐balancing robots to navigate smoothly through tight space.

Demonstrates the control of a dynamically unstable system can be controlled using a simple suppression mechanism.

A high-precision gyroscope is an important tool for accurate positioning, and the amplitude stability and frequency tracking ability of the drive control system are important and necessary conditions to ensure the precision of micro-electro-mechanical systems (MEMS) gyroscopes. To improve the precision of MEMS gyroscopes, this paper proposes a method to improve the amplitude stability and frequency tracking ability of a drive control system.

A frequency tracking loop and an amplitude control loop are proposed to improve the frequency tracking ability and amplitude stability of the drive control system for a MEMS gyroscopes. The frequency tracking loop mainly includes a phase detector, a frequency detector and a loop filter. And, the amplitude control loop mainly includes an amplitude detector, a low-pass filter and an amplitude control module. The simulation studies on the frequency tracking loop, amplitude control loop and drive control system composed of these two loops are implemented. The corresponding digital drive control algorithm is realized by the Verilog hardware description language, which is downloaded to the application-specific integrated circuits (ASIC) platform to verify the performances of the proposed method.

The simulation experiments in Matlab/Simulink and tests on the ASIC platform verify that the designed drive control system can keep the amplitude stable and track the driving frequency in real time with high precision.

This study shows a way to design and realize a drive control system for MEMS gyroscopes to improve their tracking ability. It is helpful for improving the precision of MEMS gyroscopes.

Technological capabilities of manufacturing microelectromechanical system (MEMS) gyroscopes are still insufficient if compared to manufacturing high-efficient gyroscopes and accelerometers. This creates weaknesses in their mechanical structure and restrictions in the measurement accuracy, stability and reliability of MEMS gyroscopes and accelerometers. This paper aims to develop a new architectural solutions for optimization of MEMS gyroscopes and accelerometers and propose a multi-axis MEMS inertial module combining the functions of gyroscope and accelerometer.

The finite element modeling (FEM) and the modal analysis in FEM are used for sensing, drive and control electrode capacitances of the multi-axis MEMS inertial module with the proposed new architecture. The description is given to its step-by-step process of manufacturing. Algorithms are developed to detect its angular rates and linear acceleration along three Cartesian axes.

Experimental results are obtained for eigenfrequencies and capacitances of sensing, drive and control electrodes for 50 manufactured prototypes of the silicon electromechanical sensor (SES). For 42 SES prototypes, a good match is observed between the calculated and simulated capacitance values of comb electrodes. Thus, the mean-square deviation is not over 20 per cent. The maximum difference between the calculated and simulated eigenfrequencies in the drive channel of 11 SES prototypes is not over 3 per cent. The same difference is detected for eigenfrequencies in the first sensing channel of 17 SES prototypes.

This study shows a way to design and optimize the structure and theoretical background for the development of the MEMS inertial module combining the functions of gyroscope and accelerometer. The obtained results will improve and expand the manufacturing technology of MEMS gyroscopes and accelerometers.

This aims to provide details of new sensor technologies and developments with potential applications in robotic tactile sensing and navigation.

Following a short introduction, this provides examples of tactile sensing research. This is followed by details of research into inertial sensors and other navigation techniques. Finally, brief conclusions are drawn.

This shows that tactile sensing and navigation techniques are the topic of a technologically diverse research effort which has prospects to impart various classes of robots with significantly enhanced capabilities.

This provides a technically detailed insight into recent sensor research with applications in robotic tactile sensing and navigation.

The purpose of this paper is to report the development trends and emerging applications of non‐GPS localisation sensors.

The principles of gyroscopes and micro‐electro‐mechanical systems‐based inertial sensors are introduced, followed by a review of products from various companies, and their applications.

Highly integrated systems in robust solid‐state materials are being packed into smaller housings, opening up new applications for inertial navigation sensors. The Kalman filter algorithm is widely used to remove noise from multi‐sensor data and provide reliable attitude and heading measurements. Applications range from stabilising cameras and detecting the motion of towed sonar arrays, to autonomous robot navigation, motion analysis in sports science, and navigating first‐response rescue workers in disaster zones.

Concentrates on non‐GPS localisation technology, and shows that new developments are revolutionising position‐finding and position‐controlling applications.

The purpose of this paper is to provide a technical review of silicon micro‐electromechanical systems (MEMS) technology and its applications.

Following an introduction, the paper describes silicon MEMS fabrication and assembly techniques, considers a selection of commercially important products and their applications and concludes with a brief review of power MEMS research.

Silicon MEMS fabrication technology is derived from techniques used in semiconductor manufacture and has yielded a diverse and ever‐growing range of sensors, actuators and other miniaturised devices that find applications in a multitude of industries.

This paper provides a detailed technical review of MEMS technology and its applications.

The paper aims to describe the sensors used for interfacing with consumer electronic devices.

The paper describes the types of sensors employed in user‐interface devices such as trackballs, mice, touch pads, touch screens and gesture‐based systems. It concludes with a brief consideration of brain‐computer interface technology.

It is shown that a diverse range of sensors is used to interface with consumer electronics. They are based on optical, electrical, acoustic and solid‐state (MEMS) technologies. In the longer term, many may ultimately be replaced by sensors that interpret thought by detecting brain waves.

The paper provides a timely review of the sensors used to interface with consumer electronics. These constitute a very large and rapidly growing market.

This paper aims to review the shape sensing techniques using large area flexible electronics (LAFE). Shape perception of humanoid robots using tactile data is mainly focused.

Research papers on different shape sensing methodologies of objects with large area, published in the past 15 years, are reviewed with emphasis on contact-based shape sensors. Fiber optics based shape sensing methodology is discussed for comparison purpose.

LAFE-based shape sensors of humanoid robots incorporating advanced computational data handling techniques such as neural networks and machine learning (ML) algorithms are observed to give results with best resolution in 3D shape reconstruction.

The literature review is limited to shape sensing application either two- or three-dimensional (3D) LAFE. Optical shape sensing is briefly discussed which is widely used for small area. Optical scanners provide the best 3D shape reconstruction in the noncontact-based shape sensing; here this paper focuses only on contact-based shape sensing.

Contact-based shape sensing using polymer nanocomposites is a very economical solution as compared to optical 3D scanners. Although optical 3D scanners can provide a high resolution and fast scan of the 3D shape of the object, they require line of sight and complex image reconstruction algorithms. Using LAFE larger objects can be scanned with ML and basic electronic circuitory, which reduces the price hugely.

LAFE can be used as a wearable sensor to monitor critical biological parameters. They can be used to detect shape of large body parts and aid in designing prosthetic devices. Tactile sensing in humanoid robots is accomplished by electronic skin of the robot which is a prime example of human–machine interface at workplace.

This paper reviews a unique feature of LAFE in shape sensing of large area objects. It provides insights from mechanical, electrical, hardware and software perspective in the sensor design. The most suitable approach for large object shape sensing using LAFE is also suggested.