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In this study, an indoor sensor information fusion positioning system of the quadrotor unmanned aerial vehicle (UAV) was investigated to solve the problem of unstable indoor flight positioning.

The presented system was built on Light Detection and Ranging (LiDAR), Inertial Measurement Unit (IMU) and LiDAR-Lite devices. Based on this, one can obtain the aircraft's current attitude and the position vector relative to the target and control the attitudes and positions of the UAV to reach the specified target positions. While building a UAV positioning model relative to the target for indoor positioning scenarios under limited Global Navigation Satellite Systems (GNSS), the system detects the environment through the NVIDIA Jetson TX2 (Transmit Data) peripheral sensor, obtains the current attitude and the position vector of the UAV, packs the data in the format and delivers it to the flight controller. Then the flight controller controls the UAV by calculating the posture to reach the specified target position.

The authors used two systems in the experiment. The first is the proposed UAV, and the other is the Vicon system, our reference system for comparison purposes. Vicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.

Vicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.

Vision-based positioning without camera calibration, using uncalibrated industrial robots, is a challenging research problem. To address the issue, an uncalibrated industrial robot real-time positioning system has been developed in this paper. The paper aims to discuss these issues.

The software and hardware of this system as well as the methodology are described. Direct and inverse kinematics equations that map joint space into “camera space” are developed. The camera-space manipulation (CSM) algorithm has been employed and improved with varying weights on camera samples of the robot end effector, and the improved CSM is named VW-CSM. The experiments of robot positioning have been conducted using the traditional CSM algorithm and the varying-weight CSM (VW-CSM) algorithm, respectively, both without separate camera calibration. The impact on the accuracy and real-time performance of the system caused by different weights has been examined and discussed.

The experimental results show that the accuracy and real-time performance of the system with the VW-CSM algorithm is better than the one with using the original CSM algorithm, and the impact on the accuracy and real-time performance of the system caused by different weights has been revealed.

The accuracy and real-time performance of the system with the VW-CSM algorithm is verified. These results prove that the developed system using the VW-CSM algorithm can satisfy the requirements of most industrial applications and can be widely used in the field of industrial robots.

The purpose of this paper is to relate to the real-time navigation and tracking of pedestrians in a closed environment. To restrain accumulated error of low-cost microelectromechanical system inertial navigation system and adapt to the real-time navigation of pedestrians at different speeds, the authors proposed an improved inertial navigation system (INS)/pedestrian dead reckoning (PDR)/ultra wideband (UWB) integrated positioning method for indoor foot-mounted pedestrians.

This paper proposes a self-adaptive integrated positioning algorithm that can recognize multi-gait and realize a high accurate pedestrian multi-gait indoor positioning. First, the corresponding gait method is used to detect different gaits of pedestrians at different velocities; second, the INS/PDR/UWB integrated system is used to get the positioning information. Thus, the INS/UWB integrated system is used when the pedestrian moves at normal speed; the PDR/UWB integrated system is used when the pedestrian moves at rapid speed. Finally, the adaptive Kalman filter correction method is adopted to modify system errors and improve the positioning performance of integrated system.

The algorithm presented in this paper improves performance of indoor pedestrian integrated positioning system from three aspects: in the view of different pedestrian gaits at different speeds, the zero velocity detection and stride frequency detection are adopted on the integrated positioning system. Further, the accuracy of inertial positioning systems can be improved; the attitude fusion filter is used to obtain the optimal quaternion and improve the accuracy of INS positioning system and PDR positioning system; because of the errors of adaptive integrated positioning system, the adaptive filter is proposed to correct errors and improve integrated positioning accuracy and stability. The adaptive filtering algorithm can effectively restrain the divergence problem caused by outliers. Compared to the KF algorithm, AKF algorithm can better improve the fault tolerance and precision of integrated positioning system.

The INS/PDR/UWB integrated system is built to track pedestrian position and attitude. Finally, an adaptive Kalman filter is used to improve the accuracy and stability of integrated positioning system.

Global positioning system (GPS) kinematic positioning suffers from performance degradation in constrained environments such as urban canyons, which then restricts the application of high-precision vehicle positioning and navigation within the city. In December 2012, the BeiDou Navigation Satellite System (BDS) regional service was announced, and the combined BDS/GPS kinematic positioning has been enabled in the Asia-Pacific area. Previous studies have mainly focused on the performance evaluations of combined BDS/GPS static positioning. Not much work has been performed for kinematic vehicle positioning under constrained observation conditions. This study aims to analyze the performance of BDS/GPS kinematic vehicle positioning in various conditions.

In this study, three vehicle experiments under three observation conditions, an open suburban area, a less dense non-central urban area and a dense central urban area, are investigated using both the code-based differential global navigation satellite system (DGNSS) and phase-based real-time kinematic (RTK) modes. The comparison between combined BDS/GPS and GPS-only vehicle positioning solutions is conducted in terms of positioning availability and positioning precision.

Numerical results show that the combined BDS/GPS system significantly outperforms the GPS-only system under poor observation conditions, whereas the improvement was less significant under good observation conditions.

Thus, this paper studies the performance of combined BDS/GPS kinematic relative positioning under various observation conditions.

To describe the architecture of iPOS (short for iPAQ positioning system), a novel fault‐tolerant and adaptive self‐positioning system with quality‐of‐service (QoS) guarantees for resource‐limited mobile devices.

The iPOS architecture is based on a novel sensor modelling technique in combination with a probabilistic data‐fusion engine, which is capable of efficiently combining the location information obtained from an arbitrary number of heterogeneous location sensors. As a proof of concept, the paper present a prototypical implementation for handheld devices, which was evaluated by means of practical experiments.

A major advantage of the iPOS positioning system is its extensibility and flexibility, which is achieved by means of an open plugin architecture and the support of global positioning coordinates according to the WGS‐84 standard. The iPOS system scales very well with respect to the number of sensor plugins that can be operated in parallel. The main limiting factor for the number of supported active plugins is the amount of available system resources on the MoD. With regard to recognition, the experimental results indicate a good accuracy of the fusion‐based positioning system in comparison to the accuracy of the individual sensing technologies. Thanks to the explicit modelling of reliable sensor events, the iPOS system is capable of providing QoS guarantees to applications with regard to the achieved positioning accuracy.

During the experiments, the author recognized time synchronisation as an important challenge that should be addressed as part of future work.

The system enables resource‐restricted mobile devices and computerised objects to exploit computing resources found in their immediate physical vicinity (locality).

The paper presents a novel lightweight sensor‐fusion architecture for fault‐tolerant and adaptive self‐positioning that performs well on resource‐limited mobile devices. A special feature of the developed data‐fusion architecture is the application of a novel event modelling technique that enables the positioning system to give QoS guarantees under certain conditions.

Component positioning is an important part of aircraft assembly, aiming at the problem that it is difficult to accurately fall into the corresponding ball socket for the ball head connected with aircraft component. This study aims to propose a ball head adaptive positioning method based on impedance control.

First, a target impedance model for ball head positioning is constructed, and a reference positioning trajectory is generated online based on the contact force between the ball head and the ball socket. Second, the target impedance parameters were optimized based on the artificial fish swarm algorithm. Third, to improve the robustness of the impedance controller in unknown environments, a controller is designed based on model reference adaptive control (MRAC) theory and an adaptive impedance control model is built in the Simulink environment. Finally, a series of ball head positioning experiments are carried out.

During the positioning of the ball head, the contact force between the ball head and the ball socket is maintained at a low level. After the positioning, the horizontal contact force between the ball head and the socket is less than 2 N. When the position of the contact environment has the same change during ball head positioning, the contact force between the ball head and the ball socket under standard impedance control will increase to 44 N, while the contact force of the ball head and the ball socket under adaptive impedance control will only increase to 19 N.

In this paper, impedance control is used to decouple the force-position relationship of the ball head during positioning, which makes the entire process of ball head positioning complete under low stress conditions. At the same time, by constructing an adaptive impedance controller based on MRAC, the robustness of the positioning system under changes in the contact environment position is greatly improved.

Automatic robots can improve the efficiency of liquefied petroleum gas (LPG) tank inspection and maintenance, but it is difficult to achieve high-precision spatial positioning and navigation on tank surfaces. The purpose of this paper is to develop a spatial positioning robotic system for tank inspection. The robot can accurately identify and track weld paths. The positioning system can complete robot’s spatial positioning on tank surfaces.

A tank inspection robot with curvature-adaptive transmission mechanisms is designed in this study. A weld path recognition method based on deep learning is proposed to accurately identify and extract weld paths. Integrated multiple sensors, the positioning system is developed to improve the robot’s spatial positioning accuracy. Experiments are conducted on a cylindrical tank to test weld seam tracking accuracy and spatial positioning performance of the robotic system. The practicality of the robotic system is then verified in field tests.

The robot can accurately identify and track weld seams with a maximum drift angle of 4° and a maximum offset distance of ±30 mm. The positioning system has excellent positioning accuracy and stability. The maximum angle and height errors are 3° and 0.08 m, respectively.

The positioning system can improve the autonomous performance of inspection robots and solve the problems of weld path recognition and spatial positioning. Application of the robotic system can promote the automatic inspection and maintenance of LPG tanks.

This research aims to focus on providing interventions to alleviate usability challenges to strengthen the overall accuracy and the navigation effectiveness in indoor and stringent environments through the experiential manipulation of technical attributes of the positioning and navigation system.

The study followed a quantitative and experimental method of empirical enquiry and software engineering and synthesis research methods. The study further entails three implementation processes, namely, map generation, positioning framework and navigation service using a prototype mobile navigation application that uses the near field communication (NFC) technology.

The approach and findings revealed that the capability of NFC in leveraging its low-cost infrastructure of passive tags, its availability in mobile devices and the ubiquity of the mobile device provided a cost-effective solution with impressive accuracy and usability. The positioning accuracy achieved was less than 9 cm. The usability improved from 44 to 96 per cent based on feedbacks given by respondents who tested the application in an indoor environment. These showed that NFC is a viable alternative to resolve the challenges identified in previous solutions and technologies.

The major limitation of the navigation application was that there is no real-time update of user position. This can be investigated and extended further by using NFC in a hybrid make-up with WLAN, radio-frequency identification (RFID) or Bluetooth as a cost-effective solution for real-time indoor positioning because of their coverage and existing infrastructures. The hybrid positioning model, which merges two or more techniques or technologies, is becoming more popular and will improve its accuracy, robustness and usability. In addition, it will balance complexity, compensate for the limitations in the technologies and achieve real-time mobile indoor navigation. Although the presence of WLAN, RFID and Bluetooth technologies are likely to result in system complexity and high cost, NFC will reduce the system’s complexity and balance the trade-off.

Whilst limitations in existing indoor navigation technologies meant putting up with poor signal and poor communication capabilities, outcomes of the NFC framework will offer valuable insight. It presents new possibilities on how to overcome signal quality limitations at improved turn-around time in constrained indoor spaces.

The innovations have a direct positive social impact in that it will offer new solutions to mobile communications in the previously impossible terrains such as underground platforms and densely covered spaces. With the ability to operate mobile applications without signal inhibitions, the quality of communication – and ultimately, life opportunities – are enhanced.

While navigating, users face several challenges, such as infrastructure complexity, high-cost solution, inaccuracy and usability. Hence, as a contribution, this paper presents a symbolic map and path architecture of a floor of the test-bed building that was uploaded to OpenStreetMap. Furthermore, the implementation of the RFID and the NFC architectures produced new insight on how to redress the limitations in challenged spaces. In addition, a prototype mobile indoor navigation application was developed and implemented, offering novel solution to the practical problems inhibiting navigation in indoor challenged spaces – a practical contribution to the community of practice.

This paper aims to present the problem of the integration of the global positioning system (GPS)/global navigation satellite system (GLONASS) data for the processing of aircraft position determination.

The aircraft coordinates were obtained based on GPS and GLONASS code observations for the single point positioning (SPP) method. The numerical computations were executed in the aircraft positioning software (APS) package. The mathematical scheme of equation observation of the SPP method was solved using least square estimation in stochastic processing. In the research experiment, the raw global navigation satellite system data from the Topcon HiperPro onboard receiver were applied.

In the paper, the mean errors of an aircraft position from APS were under 3 m. In addition, the accuracy of aircraft positioning was better than 6 m. The integrity term for horizontal protection level and vertical protection level parameters in the flight test was below 16 m.

The paper presents only the application of GPS/GLONASS observations in aviation, without satellite data from other navigation systems.

The presented research method can be used in an aircraft based augmentation system in Polish aviation.

The paper is addressed to persons who work in aviation and air transport.

The paper presents the SPP method as a satellite technique for the recovery of an aircraft position in an aviation test.

The positioning and grasping of large-size objects have always had problems of low positioning accuracy, slow grasping speed and high application cost compared with ordinary small parts tasks. This paper aims to propose and implement a binocular vision-guided grasping system for large-size object with industrial robot.

To guide the industrial robot to grasp the object with high position and pose accuracy, this study measures the pose of the object by extracting and reconstructing three non-collinear feature points on it. To improve the precision and the robustness of the pose measuring, a coarse-to-fine positioning strategy is proposed. First, a coarse but stable feature is chosen to locate the object in the image and provide initial regions for the fine features. Second, three circular holes are chosen to be the fine features whose centers are extracted with a robust ellipse fitting strategy and thus determine the precise pose and position of the object.

Experimental results show that the proposed system has achieved high robustness and high positioning accuracy of −1 mm and pose accuracy of −0.5 degree.

It is a high accuracy method that can be used for industrial robot vision-guided and grasp location.