In order to improve the positioning accuracy of industrial robots, this paper proposes a global calibration method for planar parallel robot considering joint errors, which solves the problem that the existing calibration methods only consider part of the error sources and the calibration accuracy is poor, and improves the calibration efficiency and robot positioning accuracy. Consequently, it improves calibration efficiency and the overall precision of robot positioning. Firstly, the error model of overdetermined equations combined with structural parameters is established, and the global sensitivity of each error source is analyzed. Based on the measurement data of laser tracker, the local error source is identified by the least square method, which improves the local error accuracy by 88.6%. Then, a global error spatial interpolation method based on inverse distance weighting method is proposed, and the global accuracy is improved by 59.16%. Finally, the radial basis function neural network error prediction model with strong nonlinear approximation function is designed for global calibration, and the accuracy is improved by 63.05%. Experimental results verify the effectiveness of the proposed method. This study not only provides technical support for the engineering application of this experimental platform but also provides theoretical guidance for the improvement of the accuracy of related robot platforms.

This paper proposes a method for self-calibrating the star sensor on the Mars rover considering several years of exploration on the surface of Mars. The natural stars in the night sky are considered the control points, and a self-calibration model is deduced in detail according to an imaging model. An adaptive celestial positioning (ACP) algorithm is then introduced, and the calculation procedure is presented in detail to realise self-adjustment based on the self-calibration of the star sensor. Three field tests were conducted on Earth, the results of which show good self-calibration and celestial positioning performances. The positioning results indicate an obvious accuracy improvement using the ACP algorithm compared with that without calibration. Multiple positionings in one night can improve the celestial positioning accuracy to approximately 15 m. For future studies, this self-calibration model will be useful not only for star sensors but also for other optical sensors, such as sun sensors and binocular or stereo-vision cameras.

The single initial Global Positioning System (GPS) has been expanded into multiple global and regional navigation satellite systems (multi-GNSS/RNSS) as the Global Navigation Satellite System (GLONASS) is restored and the BeiDou Navigation Satellite System (BDS), Galileo Satellite Navigation System (Galileo) and Quasi-Zenith Satellite System (QZSS) evolve. Using the differences among these five systems, the paper constructs a consolidated multi-GNSS/RNSS precise point positioning (PPP) observation model. A large number of datasets from Multi-GNSS Experiment (MGEX) stations are employed to evaluate the PPP performance of multi-GNSS/RNSS. The paper draws three main conclusions based on the experimental results. (1) The combined GPS/GLONASS/Galileo/BDS/QZSS presents the PPP with the shortest mean convergence time of 11·5 min, followed by that of GPS/GLONASS/Galileo/BDS (12·4 min). (2) The combined GPS/GLONASS/BDS/Galileo/QZSS shows the optimal PPP performance when the cut-off elevation angle is basically the same because of the rich observation data due to a large number of satellites. To be specific, for combined GPS/GLONASS/BDS/Galileo/QZSS, the PPP convergence percentage is 80·9% higher relative to other combined systems under 35° cut-off elevation angle, and the percentages of the root mean square values of PPP within 0–5 cm are enhanced by 80·5%, 81·5% and 87·3% in the North, East and Up directions relative to GPS alone at 35° cut-off elevation angle. (3) GPS alone fails to conduct continuous positioning due to the insufficiency of visible satellites at 40° cut-off elevation angle, while the kinematic PPP of multi-GNSS/RNSS remains capable of obtaining positioning solutions with relatively high accuracy, especially in the horizontal direction.

One critical issue in network real-time kinematic (NRTK) is the interpolation of atmospheric delay for user stations. Some classic interpolation algorithms, such as linear interpolation method (LIM), ignore the strong correlation between tropospheric delay and height factors, and the interpolation accuracy is poor in areas with large height difference. To solve this problem, a troposphere modelling method based on error compensation, namely ECDIM (Error Compensation-Based DIM), is proposed, and this method can be applied to both conventional single Delaunay triangulated network (DTN) and multi-station scenarios. The results of California Real Time Network (CRTN) with large height difference show that compared with LIM, the overall modelling accuracy with ECDIM has been improved by 50.1% to 67.3%, and especially for low elevation satellites (e.g., 10–20 degree), the accuracy is increased from tens of centimetres to a few centimetres. At user end, the positioning error in up direction with LIM has an obvious systematic deviation, and the fix rate of epoch is relatively low. This situation has been improved significantly after using ECDIM. The results of Tianjin Continuously Operating Reference System (TJCORS) show that in areas with small height difference, both methods have achieved high precision interpolation accuracy, and the positioning accuracy with ECDIM in up direction is improved by 21.2% compared with LIM.

This paper analyses for the first time the impact of new GPS signals on positioning accuracy for dynamic urban applications, taking bus operations as an example. The performance assessment addresses both code measurement precision and positioning accuracy. The former is based on signal-to-noise ratio and estimation of multipath and noise by a combination of code and carrier phase measurements. The impact on positioning accuracy is derived by comparing the performance achievable with the conventional single frequency GPS only positioning both relative to reference trajectories from the integration of carrier phase measurements with data from a high grade inertial measurement unit. The results show that L5 code measurements have the highest precision, followed by L1 C/A and L2C. In the positioning domain, there is a significant improvement in two-dimensional and three-dimensional accuracy from dual frequency code measurements over the single frequency measurements, of 39% and 48% respectively, enabling more bus operation services to be supported.

To achieve fast satellite selection for a multi-Global Navigation Satellite System (GNSS), thereby reducing the burden on a receiver's processing element and the cost of hardware, and improving the utilisation ratio of receiver signal channels, the relationship between the number of satellites and Geometric Dilution Of Precision (GDOP), the number of satellites selected and the computation time is analysed. A fast rotating partition algorithm for satellite selection based on equal distribution of the sky is proposed. The algorithm divides the satellite selection process into two parts: rough selection and detailed selection. Unhealthy satellites, according to a health identifier, and low elevation angle satellites with a large troposphere delay are eliminated during the rough selection process. During the detailed satellite selection process, the satellite sky is divided and rotated to match satellites based on the average angle distance between the satellite and central partition line. Static data from the International GNSS Service (IGS) station and dynamic data collected at China University of Mining and Technology were used to verify the algorithm, and the results demonstrated that an inverse matrix could be avoided to reduce computation complexity. Additionally, the new satellite selection algorithm has the merit that there is little effect on the computation when the selected satellites and number of satellites in the field increased. A single system of the Global Positioning System (GPS) and double system of GPS/Globalnaya Navigazionnaya Sputnikovaya Sistema (GLONASS) both passed the hypothesis test for each epoch. By including BeiDou Navigation Satellite System (BDS) data, data utilisation increased to more than 95% using the rotating partition algorithm. Also, the GDOP and positioning performance of a rotating partition algorithm and an optimal Dilution Of Precision (DOP) algorithm are compared in this paper, and the analysis result shows that both of the algorithms have only a small difference of GDOP and have comparable positioning performance.

Differential Global Positioning Systems (DGPS) and the European Geostationary Navigation Overlay Service (EGNOS) are included in a group of supporting systems (Ground-Based Augmentation System (GBAS)/Space-Based Augmentation System (SBAS)) for the American GPS. Their main task is to ensure better positioning characteristics (accuracy, reliability, continuity and availability) compared to GPS. Therefore, they are widely applied wherever GPS failures affect human safety, mainly in aviation, land and marine navigation. The aim of this paper is to assess the predictable positioning accuracy of DGPS and EGNOS receivers using a vessel manoeuvring in the Bay of Gdansk. Two receivers were used in the study: a Simrad MXB5 (DGPS) and a Trimble GA530 (EGNOS), which were simultaneously recording their coordinates. The obtained values were compared with the trajectory computed using a geodetic Global Navigation Satellite System (GNSS) receiver (Trimble R10) connected to a GNSS network, ensuring an accuracy of 2–3 cm (p = 0·95). During a four-hour measurement session, the accuracy statistics of these systems were determined based on around 11,500 positionings. Studies have shown that both positioning systems ensure a similar level of accuracy of their positioning services (approximately 0·5–2 m) and they meet the accuracy requirements set in published standards.

This paper investigates the problem of how to design the distance between a mobile buoy and the target to derive maximum positioning accuracy with a Moving Long Baseline (MLBL). To that end, the positioning model and the error sources of MLBL are derived, respectively. It is assumed that the position measurement of the mobile buoy and the distance measurement between the mobile buoy and the target are corrupted by white Gaussian noises, and the variance of the distance measurement is distance-dependent. Using tools from estimation theory, the Positioning Accuracy Metric (PAM) is designed with the distance error and the position errors are considered. Based on the PAM, the optimal distance between the mobile buoy and target is deduced when the mobile buoys are in optimal geometry. Simulation examples illustrate the results.

This paper presents a simple identification method of the actual kinematic parameters for a robot with parallel joints. It is known that Denavit–Hartenberg's coordinate System is not useful for nearly parallel joints. In this paper, the coordinate frames are reassigned to model the kinematic parameter between nearly parallel joints by four parameters. The proposed identification method uses a straight ruler about 1 m long. A robot hand is placed by using a teaching pendant at the prescribed points on the ruler, and the corresponding error function is defined. The identified kinematic parameters, which make the error function zero, are obtained by the iterative least square method based on the singular value decomposition. In the compensation of joint angles, only the position is considered because the usual applications of robot do not require a precise orientation control.

A good practice to ensure high-positioning accuracy in industrial robots is to use joint error maximum mutual compensation (JEMMC). This paper presents an application of JEMMC for positioning of hexapod robots to improve end-effector positioning accuracy. We developed an algorithm and simulation framework in MatLab to find optimal hexapod configurations with JEMMC. Based on a real hexapod model, simulation results of the proposed approach are presented. Optimal hexapod configurations were found using the local minimum of the infinity norm of hexapod Jacobian inverse. JEMMC usage in hexapod robots can improve hexapod end-effector positioning accuracy by two times and more.