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The selection of a suitable inertial measurement unit (IMU) is a critical step in an inertial navigation system (INS) design. Nevertheless, inertial sensors manufacturers are unwilling to publish their products’ accurate performance parameters along with a price. This paper aims to summarise the current IMU market review and point out parameters important for short-term inertial navigation.

The market review is based on the information published by manufacturers in brochures, datasheets and websites. Some information, including price, was also collected from sensors distributors. The entire collection of data includes data of over 150 sensors from 32 manufacturers and is valid for the first half of the year 2020.

This paper answers the following questions: •Why and where use inertial navigation? •Which parameters should one emphasise during IMU selection?•What is currently available on the IMU market? •Which parameters have a significant influence on price? •What are the advantages of specific sensor technology?

This paper gathers data published by IMU manufacturers, allowing for a quick overview of the current market. Based on real data, different sensor technologies are compared. The performed analysis presents the statistical basis for the IMU selection. By theoretical considerations a significance of sensor parameters is drawn and an approach to an IMU selection based on limited number of parameters is proposed. Although the considerations have been carried out regarding inertial navigation, the results from an extensive analysis of commercially available sensors may also be useful for other applications.

Continuum manipulators are often used in complex and narrow space in recent years because of their flexibility and safety. Vision is considered to be one of the most direct methods to obtain its spatial shape. However, with the improvement of the cooperation requirements of multiple continuum manipulators and the increase of space limitation, it is impossible to obtain the complete spatial shape information of multiple continuum manipulators only by several cameras.

This paper proposes a fusion method using inertial navigation sensors and cameras to reconstruct the shape of continuum manipulators in the whole workspace. The camera is used to obtain the position information, and the inertial navigation sensor is used to obtain the attitude information. Based on the above two information, the shape of the continuum manipulator is reconstructed by fitting Bézier curve.

The experiment result of single continuum manipulator shows that the cubic Bézier curves is applicable to curve fitting of variable curvature, the maximum fitting error is about 2 mm. Meanwhile, the experiment result shows that this method is not affected by obstacles and can still reconstruct the shape of the continuum manipulators in 3-D space by detecting the position and attitude information of the end.

According to the authors’ knowledge, this is the first study on spatial shape reconstruction of multiple continuum manipulators and the first study to introduce inertial navigation sensors and cameras into the field of shape reconstruction of multiple continuum manipulators in narrow space. This method is suitable for shape reconstruction of manipulator with variable curvature continuum manipulator. When the vision of multiple continuum manipulators is blocked by obstacles, the spatial shape can still be reconstructed only by exposing the end point. The structure is simple, but it has certain accuracy within a certain range.

This study aims to design an optimized algorithm for low-cost pedestrian navigation system (PNS) to correct the heading drift and altitude error, thus achieving high-precise pedestrian location in both two-dimensional (2-D) and three-dimensional (3-D) space.

A novel heading correction algorithm based on smoothing filter at the terminal of zero velocity interval (ZVI) is proposed in the paper. This algorithm adopts the magnetic sensor to calculate all the heading angles in the ZVI and then applies a smoothing filter to obtain the optimal heading angle. Furthermore, heading correction is executed at the terminal moment of ZVI. Meanwhile, an altitude correction algorithm based on step height constraint is proposed to suppress the altitude channel divergence of strapdown inertial navigation system by using the step height as the measurement of the Kalman filter.

The verification experiments were carried out in 2-D and 3-D space to evaluate the performance of the proposed pedestrian navigation algorithm. The results show that the heading drift and altitude error were well corrected. Meanwhile, the path calculated by the novel algorithm has a higher match degree with the reference trajectory, and the positioning errors of the 2-D and 3-D trajectories are both less than 0.5 per cent.

Besides zero velocity update, another two problems, namely, heading drift and altitude error in the PNS, are solved, which ensures the high positioning precision of pedestrian in indoor and outdoor environments.

This paper aims to describe a novel hybrid inertial measurement unit (IMU) for motion capturing via a new configuration of strategically distributed inertial sensors, and a calibration approach for the accelerometer and gyroscope sensors mounted in a flight vehicle motion tracker built on the inertial navigation system.

The hybrid-IMU is designed with five accelerometers and one auxiliary gyroscope instead of the accelerometer and gyroscope triads in the conventional IMU.

Simulation studies for tracking with both attitude angles and translational movement of a flight vehicle are conducted to illustrate the effectiveness of the proposed method.

The cross-quadratic terms of angular velocity are selected to process the direct measurements of angular velocities of body frame and to avoid the integration of angular acceleration vector compared with gyro-free configuration based on only accelerometers. The inertial sensors are selected from the commercial microelectromechanical system devices to realize its low-cost applications.

Before designing a navigation system, it is necessary to analyse possible approaches in terms of expected accuracy, existing limitations and economic justification to select the most advantageous solution. This paper aims to collect possible navigation methods that can provide correction for inertial navigation and to evaluate their suitability for use on a manoeuvring tactical missile.

The review of existing munitions was based on data collected from the literature and online databases. The data collected included dimensions, performance, applied navigation and guidance methods and their achievable accuracy. The requirements and limitations identified were confronted with the range of sensor parameters available on the market. Based on recent literature, navigation methods were reviewed and evaluated for applicability to inertial navigation system (INS) correction in global navigation satellite system-denied space.

The performance analysis of existing munition shows that small and relatively inexpensive micro-electro-mechanical system-type inertial sensors are required. A review of the parameters of existing devices of this type has shown that they are subject to measurement errors that do not allow them to achieve the delivery accuracy expected of precision missiles. The most promising navigation correction methods for manoeuvring flying objects have been identified.

The information presented in this paper is the result of the first phase of a project and presents the results of the requirements selection, initial sizing and preliminary design of the navigation system. This paper combines a review of the current state of the art in missile systems and an analysis of INS accuracy including the selection of sensor parameters.

The aim of this article is to present a PIN (pedestrian inertial navigation) solution that incorporates altitude error correction, which eliminates the altitude error accurately without using external sensors. The main problem of PIN is the accumulation of positioning errors due to the drift caused by the noise in the sensors. Experiment results show that the altitude errors are significant when navigating in multilayer buildings, which always lead to localization to incorrect floors.

The PIN proposed is implemented over an inertial navigation systems (INS) framework and a foot-mounted IMU. The altitude error correction idea is identifying the most probable floor of each horizontal walking motion. To recognize gait types, the walking motion is described with angular rate measured by IMU, and the dynamic time warping algorithm is used to cope with the different dimension samples due to the randomness of walking motion. After gait recognition, the altitude estimated with INS of each horizontal walking is checked for association with one of the existing in a database.

Experiment results show that high accuracy altitude is achieved with altitude errors below 5 centimeters for upstairs and downstairs routes in a five floors building.

The main limitations of the study is the assumption that accuracy floor altitude information is available.

Our PIN system eliminates altitude errors accurately and intelligently, which benefits from the new idea of combination of gait recognition and map-matching. In addition, only one IMU is used which is different from other approach that use external sensors.

This paper aims to present a method for improving the performance of the visual-inertial navigation system (VINS) by using a bio-inspired polarized light compass.

The measurement model of each sensor module is derived, and a robust stochastic cloning extended Kalman filter (RSC-EKF) is implemented for data fusion. This fusion framework can not only handle multiple relative and absolute measurements, but can also deal with outliers, sensor outages of each measurement module.

The paper tests the approach on data sets acquired by a land vehicle moving in different environments and compares its performance against other methods. The results demonstrate the effectiveness of the proposed method for reducing the error growth of the VINS in the long run.

The main contribution of this paper lies in the design/implementation of the RSC-EKF for incorporating the homemade polarized light compass into visual-inertial navigation pipeline. The real-world tests in different environments demonstrate the effectiveness and feasibility of the proposed approach.

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 review recent developments in sensors for application in unmanned vehicles.

This study included in-depth interviews with exhibitors of sensors and sensor integrators at trade shows and contact with providers of such devices to the industry.

Sensor innovation has made giant leaps in producing much smaller and smarter sensors to address unmanned vehicle requirements.

Developers of unmanned vehicles of all types may be surprised at the sensor innovations and new applications to which sensors are being applied in this rapidly advancing field.

A review of some of the latest sensor innovations and applications that one might have seen if they had been on the exhibition floor at the recent trade shows, followed industrial publications or announcements from sensor developers.