Unknown Bias Research Articles

Multipath Mitigation via Synthetic Aperture Beamforming for Indoor and Deep Urban Navigation

A synthetic aperture navigation (SAN) system that exploits downlink cellular long-term evolution (LTE) signals and an inertial measurement unit (IMU) is developed. The system is suitable for multipath-rich environments, such as indoors and deep urban canyons. The proposed SAN system mitigates multipath via a spatial discriminator, which utilizes the motion of a single antenna element to synthesize a geometrically separated antenna array from time-separated snapshots, alleviating the need for a physical antenna array. Signals from the synthesized antenna array are used to beamform towards the line-of-sight (LOS) LTE direction, while suppressing multipath components. Different stages of the beamforming process are discussed, and the computational complexity of the proposed system is analyzed. To deal with the unknown clock biases of the LTE eNodeBs, two navigation frameworks are developed: (1) base/rover and (2) standalone rover. The proposed SAN system is validated experimentally, and the navigation solutions achieved from the following systems are compared: (i) IMU only, (ii) LTE only, (iii) feedforward LTE-SAN, (iv) feedback LTE-SAN, (v) LTE-IMU, and (vi) feedback LTE-SAN-IMU. In the performed experiment, a pedestrian-mounted receiver navigated indoors for 109 m in 50 seconds, while receiving LTE signals from 5 LTE eNodeBs. The proposed LTE-SAN-IMU system exhibited a two-dimensional position root mean-squared error (RMSE) of 1.44 m with a standard deviation of 1.85 m.

Optimal design of experiments for optimization-based model calibration using Fisher information matrix

Statistical model calibration to infer unknown model parameters and model bias has been widely developed through comparison between simulation response and experimental data. Bayesian-based model calibration typically represented as Kennedy and O'Hagan (KOH) framework and optimization-based model calibration have been proposed, but efforts on optimization of experimental design to reduce the epistemic uncertainty minimizing experimental resources are still limited. Furthermore, when an unknown model parameter has natural and uncontrollable variability, the estimation may be much more difficult since both aleatory and epistemic uncertainties exist. In this paper, we have developed a framework to find the optimal design of experiments (DoE) satisfying the target information gain for inference of unknown model parameters based on optimization-based model calibration. The expected Fisher information matrix is approximated to quantify the expected information gain for the maximum likelihood estimation (MLE). Namely, the necessary number of experiments at each experimental design can be obtained to attain desired precision on estimators while minimizing the overall experimental cost. The numerical study verifies the feasibility of the proposed framework, which means that there is certainly a dominant DoE that gives more information to the inference on specific model parameters.

Pediatric basal cell carcinoma burden and management preferences in Gorlin syndrome: A survey study

To the Editor: Gorlin syndrome (GS) is a risk factor for early basal cell carcinomas (BCCs),1Moustafa D. Neale H. Hawryluk E.B. Trends in pediatric skin cancer.Curr Opin Pediatr. 2020; 32: 516-523Crossref PubMed Scopus (2) Google Scholar although its prevalence of fewer than 1 in 30,000 individuals2Evans D.G. Howard E. Giblin C. et al.Birth incidence and prevalence of tumor-prone syndromes: estimates from a UK family genetic register service.Am J Med Genet A. 2010; 152A: 327-332Crossref PubMed Scopus (491) Google Scholar limits existing literature. There are sparse pediatric GS studies beyond case reports, creating a knowledge gap regarding childhood cutaneous findings and sequelae, including BCC age at onset, quantity, treatments, and impact. Herein, we describe a global survey to illustrate the clinical presentation, childhood perspectives, and BCC management trends for pediatric GS to improve the understanding and inform patient care. Institutional review board approval was obtained from Massachusetts General Hospital to study survey data collected by the GS Alliance and GS Group. Inclusion criteria for analyses were respondents with GS who were physician-diagnosed in childhood (at ages, ≤18 years), of whom, 122 qualified. The majority were female (n = 93, 76.2%), aged 5 to 14 years at diagnosis (n = 66, 54.1%), White (n = 108, 88.5%), and born in the United States (n = 76, 62.3%). Of known mutation status, PTCH1 was reported in 65 of 66 individuals (98.5%) and SUFU was reported in 1 individual (1.5%). The most common presenting characteristics (Fig 1) were keratocysts (n = 68, 55.7%), large/abnormal skull (n = 55, 45.1%), palmar/plantar pits (n = 39, 32.0%), and BCC (n = 37, 30.3%). At the time of survey completion, 42 respondents represented children (aged ≤18 years), of whom 32 (76.2%) had a history of BCC. The 32 children with BCC (65.6% aged ≤13 years; range, 6-18 years) had notable BCC burden: their cumulative number of tumors was 1 to 30 in 17 patients (53.1%), 31 to 100 in 5 (15.6%), and > 100 BCCs in 10 children (31.3%). Excision was the most commonly pursued treatment for pediatric BCC (n = 21) and preferred by 12 patients who experienced it (57.1%). However, a higher percentage expressed preference for Mohs micrographic surgery (3 of 5), electrodessication and curettage (4 of 6), and laser modalities (2 of 3) (Fig 2). The top 10 burdensome aspects of treatments were as follows: time spent off work/school to recover (n = 22), time spent on appointments (n = 21), time spent traveling to appointments (n = 21), mental well-being (n = 21), scarring (n = 20), physical appearance (n = 20), healing time (n = 19), pain (n = 18), physical well-being (n = 18), and quality of life (n = 16). This childhood GS study identifies meaningful trends, demonstrating how patient voices may inform and improve the management of GS. Although literature estimates the cumulative incidence of BCC by the early 20s in patients with GS to be 12% to 50%,3Jones E.A. Sajid M.I. Shenton A. Evans D.G. Basal cell carcinomas in Gorlin syndrome: a review of 202 patients.J Skin Cancer. 2011; 2011: 217378Crossref PubMed Google Scholar,4Kimonis V.E. Goldstein A.M. Pastakia B. et al.Clinical manifestations in 105 persons with nevoid basal cell carcinoma syndrome.Am J Med Genet. 1997; 69: 299-308Crossref PubMed Scopus (687) Google Scholar our data reflect a considerably higher burden with over three-quarters of pediatric respondents (aged ≤18 years) reporting a history of BCC. Dermatologists, as well as dentists, oral surgeons, and other clinicians, have an important duty to recognize presenting features of GS for appropriate care. BCC management in children may create treatment challenges, thus a pediatric-centered approach and consideration of patient and caregiver preferences must be used to provide individualized care.5Fisher J. Moustafa D. Su K.A. et al.A pediatric approach to management of skin growths in basal cell nevus syndrome.Pediatr Dermatol. 2020; 37: 527-530Crossref PubMed Scopus (1) Google Scholar Further research is required to confirm patient-reported data. Results are limited by the unknown response rate and bias of participants who are engaged in patient advocacy organizations and may exhibit a more severe disease expression. Author Breneiser is the executive director and a board member for the Gorlin Syndrome Alliance. Dr Hawryluk is a board member for the Gorlin Syndrome Alliance (uncompensated). Author Neale has no conflicts of interest to declare.

P–413 The combination of endometrial injury and Freeze-All strategy in women with repeated implantation failures

Abstract Study question Can the combination of hysteroscopic endometrial injury (EI) and freeze-all strategy improve pregnancy parameters, mainly live birth, in women with repeated implantation failures (RIF)? Summary answer The combination of Endometrial Injury and freeze-all strategy has no significant effect on live birth, clinical and miscarriage rates in RIF patients undergoing ART. What is known already A variety of strategies and approaches for RIF patients undergoing ART have been used and proposed. Currently there is insufficient evidence in the literature concerning the effect of either EI or freeze-all strategy in IVF cycles and very limited on the combination of these two approaches in RIF patients. Study design, size, duration This is a two-center two-arm cohort study conducted at both University and Private Assisted Reproductive Units in Greece, encompassing 60 cycles with vitrification as the cryopreservation method from 60 participants during the last three years. Participants/materials, setting, methods The study group comprised of 30 patients with RIF and underwent a hysteroscopic endometrial injury in the menstrual cycle prior that to the embryo transfer. The control group comprised of patients with RIF and underwent a standard cycle with no adjuvant treatment. Our primary analysis was performed to provide a direct comparison between groups. Logistic and Poisson Regression models were further employed to examine possible confounding effects. Main results and the role of chance Live birth did not differ between groups (p = 0.0953); similarly, clinical pregnancy and miscarriage rates were comparable among them (p = 0.3472 and p = 0.2542, respectively). The number of retrieved oocytes was the only significant confounder for biochemical pregnancy (p = 0.0481, 95% CI: (0.0014, 0.3223)]. Limitations, reasons for caution Limitations of the study include the lack of randomization that is linked with known and unknown biases and the small cohort size. Wider implications of the findings: The combination of both endometrial injury and freeze-all strategy does not appear to improve pregnancy rates, including live birth, in patients with RIF undergoing ART. The number of retrieved oocytes was the only significant confounder for biochemical pregnancy. Trial registration number NCT04597463

Finite-time stable estimator for attitude motion in the presence of bias in angular velocity measurements

This article presents a nonlinear finite-time stable attitude estimation scheme for a rigid body with unknown dynamics and with unknown bias in angular velocity measurements. The attitude and angular velocity are estimated from a minimum of two linearly independent known vectors measured in the body-fixed frame, and the measured angular velocity vector is assumed to have a constant bias in addition to measurement errors. The estimated attitude evolves directly on the special orthogonal group SO(3) of rigid body rotations, avoiding any ambiguities and singularities. The constant bias in angular velocity measurements is also estimated. The estimation scheme is proven to be almost globally finite time stable in the absence of measurement errors using a Lyapunov analysis. The robustness of the scheme in the presence of bounded measurement errors is analytically shown. The estimation scheme is discretized as a geometric integrator for digital implementation. Numerical simulations demonstrate the finite time stability properties of the estimation scheme. Robustness of this estimation scheme is also demonstrated through a numerical comparison against some state-of-the-art nonlinear attitude estimation schemes.

Designing experiments informed by observational studies

AbstractThe increasing availability of passively observed data has yielded a growing interest in “data fusion” methods, which involve merging data from observational and experimental sources to draw causal conclusions. Such methods often require a precarious tradeoff between the unknown bias in the observational dataset and the often-large variance in the experimental dataset. We propose an alternative approach, which avoids this tradeoff: rather than using observational data for inference, we use it to design a more efficient experiment. We consider the case of a stratified experiment with a binary outcome and suppose pilot estimates for the stratum potential outcome variances can be obtained from the observational study. We extend existing results to generate confidence sets for these variances, while accounting for the possibility of unmeasured confounding. Then, we pose the experimental design problem as a regret minimization problem subject to the constraints imposed by our confidence sets. We show that this problem can be converted into a concave maximization and solved using conventional methods. Finally, we demonstrate the practical utility of our methods using data from the Women’s Health Initiative.

Step length estimation with wearable sensors using a switched-gain nonlinear observer

This paper focuses on step length estimation using inertial measurement sensors. Accurate step length estimation has a number of useful health applications, including its use in characterizing the postural instability of Parkinson’s disease patients. Three different sensor configurations are studied using sensors on the shank and/or thigh of a human subject. The estimation problem has several challenges due to unknown measurement bias, misalignment of the sensors on the body and the desire to use a minimum number of sensors. A nonlinear estimation problem is formulated that aims to estimate shank angle, thigh angle, bias parameters of the inertial sensors and step lengths. A nonlinear observer is designed using Lyapunov analysis and requires solving an LMI to find a stabilizing observer gain. It turns out that global stability over the entire operating region can only be obtained by using switched gains, one gain for each piecewise monotonic region of the nonlinear output function. Experimental results are presented on the performance of the nonlinear observer and compared with gold standard reference measurements from an infrared camera capture system. An innovative technique that utilizes three sensors is shown to provide a step length accuracy nearly equal to that of the four-sensor configuration.

Promoting Diversity, Equity, and Inclusion in the Selection of Obstetrician-Gynecologists.

In the setting of long-standing structural racism in health care, it is imperative to highlight inequities in the medical school-to-residency transition. In obstetrics and gynecology, the percentage of Black residents has decreased in the past decade. The etiology for this troubling decrease is unknown, but racial and ethnic biases inherent in key residency application metrics are finally being recognized, while the use of these metrics to filter applicants is increasing. Now is the time for action and for transformational change to rectify the factors that are detrimentally affecting the racial diversity of our residents. This will benefit our patients and learners with equitable health care and better outcomes.

Security correction control of stochastic cyber–physical systems subject to false data injection attacks with heterogeneous effects

In this paper, the interconnected observer intervention-based security correction control idea is proposed for stochastic cyber–physical systems (CPSs) subjected to false data injection attacks (FDIAs). The FDIAs are injected into the controller-to-actuator channel by the adversary via wireless transmission. In particular, the FDIAs with heterogeneous effects are constructed, which consist of periodic attacks with unknown parameters and bias injection attacks with asymptotic convergence property. A novel interconnected adaptive observer structure is designed to online estimate the heterogeneous attack effects. The security correction control scheme with resilience is presented by integrating interconnected adaptive observer and robust technology. It is demonstrated that the impaired state signals can be corrected and desired security performance can be guaranteed for stochastic CPSs under FDIAs with heterogeneous effects. Finally, two simulation verifications, including a F-16 longitudinal dynamics system controlled by network, are established to verify the validity and feasibility for the presented strategy.

The importance of size ranges in aerosol instrument intercomparisons: a case study for the Atmospheric Tomography Mission

Abstract. Aerosol intercomparisons are inherently complex as they convolve instrument-dependent detection efficiencies vs. size (which often change with pressure, temperature, or humidity) and variations in the sampled aerosol population, in addition to differences in chemical detection principles (e.g., inorganic-only nitrate vs. inorganic plus organic nitrate for two instruments). The NASA Atmospheric Tomography Mission (ATom) spanned four separate aircraft deployments which sampled the remote marine troposphere from 86∘ S to 82∘ N over different seasons with a wide range of aerosol concentrations and compositions. Aerosols were quantified with a set of carefully characterized and calibrated instruments, some based on particle sizing and some on composition measurements. This study aims to provide a critical evaluation of inlet transmissions impacting aerosol intercomparisons, and of aerosol quantification during ATom, with a focus on the aerosol mass spectrometer (AMS). The volume determined from physical sizing instruments (aerosol microphysical properties, AMP, 2.7 nm to 4.8 µm optical diameter) is compared in detail with that derived from the chemical measurements of the AMS and the single particle soot photometer (SP2). Special attention was paid to characterize the upper end of the AMS size-dependent transmission with in-field calibrations, which we show to be critical for accurate comparisons across instruments with inevitably different size cuts. Observed differences between campaigns emphasize the importance of characterizing AMS transmission for each instrument and field study for meaningful interpretation of instrument comparisons. Good agreement (regression slope =0.949 and 1.083 for ATom-1 and ATom-2, respectively; SD =0.003) was found between the composition-based volume (including AMS-quantified sea salt) and that derived from AMP after applying the AMS inlet transmission. The AMS captured, on average, 95±15 % of the standard PM1 volume (referred to as the URG Corp. standard cut 1 µm cyclone operated at its nominal efficiency). These results support the absence of significant unknown biases and the appropriateness of the accuracy estimates for AMS total mass and volume for the mostly aged air masses encountered in ATom. The particle size ranges (and their altitude dependence) that are sampled by the AMS and complementary composition instruments (such as soluble acidic gases and aerosol, SAGA, and particle analysis by laser mass spectrometry, PALMS) are investigated to inform their use in future studies.

Firn Evolution at Camp Century, Greenland: 1966–2100

Camp Century is an American military base built in 1959 under the surface of the Greenland ice sheet and decommissioned in 1967. Here, we use outputs from RACMO2.3p2 and CanESM2 climate models, adjusted to meteorological observations, and a firn model to simulate the firn density and temperature at Camp Century between 1966 and 2100. The model output is evaluated against an extensive set of firn 3observations and three Representative Concentration Pathways (RCP2.6, 4.5 and 8.5) are considered as future scenarios. Our model suggests that the upper horizon of the Camp Century debris field – observed at a depth of 32 m in 2017 – will continue to be buried by persistent net accumulation over the next eighty years under all RCP scenarios. This horizon depth will be between 58 and 64 m in 2100, depending on the RCP scenario. We estimate a maximum meltwater percolation depth of 1.1 m under all RCP scenarios. We therefore find it extremely unlikely that surface meltwater interacts with the subsurface debris field at Camp Century before 2100 under all RCP scenarios. Camp Century’s future is representative of the firn area in northwestern Greenland, bound to shift from dry snow to a percolation regime. Our model suggests that 10 m firn temperatures at Camp Century will increase from −24.0°C in 1966 to −21.3, −20.0 and −18.6°C in 2100 under the RCP2.6, 4.5 and 8.5 scenarios, respectively. We reveal a previously unknown warm bias in air temperatures simulated at Camp Century by both RACMO2.3p2 and CanESM2 climate models which needs to be accounted for when using these models to predict melt, firn evolution and sea-level contribution of the Greenland ice sheet. We also present novelin situmeasurements of firn compaction rates, which indicate that about 25% of firn compaction of the top 62 m of firn occurs below 20 m depth. This highlights the importance of deep-firn compaction measurements for model evaluation and correction of altimetry products.

Integrated species distribution models: A comparison of approaches under different data quality scenarios

AbstractAimIntegrated species distribution modelling has emerged as a useful tool for ecologists to exploit the range of information available on where species occur. In particular, the ability to combine large numbers of ad hoc or presence‐only (PO) records with more structured presence–absence (PA) data can allow ecologists to account for biases in PO data which often confound modelling efforts. A range of modelling techniques have been suggested to implement integrated species distribution models (IDMs) including joint likelihood models, including one dataset as a covariate or informative prior, and fitting a correlation structure between datasets. We aim to investigate the performance of different types of integrated models under realistic ecological data scenarios.InnovationWe use a virtual ecologist approach to investigate which integrated model is most advantageous under varying levels of spatial bias in PO data, sample size of PA data and spatial overlap between datasets.Main conclusionsJoint likelihood models were the best performing models when spatial bias in PO data was low, or could be modelled, but gave poor estimates when there were unknown biases in the data. Correlation models provided good model estimates even when there were unknown biases and when good quality PA data were spatially limited. Including PO data via an informative prior provided little improvement over modelling PA data alone and was inferior to using either the joint likelihood or correlation approach. Our results suggest that correlation models provide a robust alternative to joint likelihood models when covariates related to effort or detection in PO data are not available. Ecologists should be aware of the limitations of each approach and consider how well biases in the data can be modelled when deciding which type of IDM to use.

Technological and informational frames: explaining age-related variation in the use of patient accessible electronic health records as technology and information

PurposeData from a national patient survey (N = 1,155) of the Swedish PAEHR “Journalen” users were analysed, and an extended version of the theory of technological frames was developed to explain the variation in the technological and informational framing of information technologies found in the data.Design/methodology/approachPatient Accessible Electronic Health Records (PAEHRs) are implemented globally to address challenges with an ageing population. However, firstly, little is known about age-related variation in PAEHR use, and secondly, user perceptions of the PAEHR technology and the health record information and how the technology and information–related perceptions are linked to each other. The purpose of this study is to investigate these two under-studied aspects of PAEHRs and propose a framework based on the theory of technological frames to support studying the second aspect, i.e. the interplay of information and technology–related perceptions.FindingsThe results suggest that younger respondents were more likely to be interested in PAEHR contents for general interest. However, they did not value online access to the information as high as older ones. Older respondents were instead inclined to use medical records information to understand their health condition, prepare for visits, become involved in their own healthcare and think that technology has a much potential. Moreover, the oldest respondents were more likely to consider the information in PAEHRs useful and aimed for them but to experience the technology as inherently difficult to use.Research limitations/implicationsThe sample excludes non-users and is not a representative sample of the population of Sweden. However, although the data contain an unknown bias, there are no specific reasons to believe that it would differently affect the survey's age groups.Practical implicationsAge should be taken into account as a key factor that influences perceptions of the usefulness of PAEHRs. It is also crucial to consider separately patients' views of PAEHRs as a technology and of the information contained in the EHR when developing and evaluating existing and future systems and information provision for patients.Social implicationsThis study contributes to bridging the gap between information behaviour and systems design research by showing how the theory of technological frames complemented with parallel informational frames to provide a potentially powerful framework for elucidating distinct conceptualisations of (information) technologies and the information they mediate. The empirical findings show how information and information technology needs relating to PAEHRs vary according to age. In contrast to the assumptions in much of the earlier work, they need to be addressed separately.Originality/valueFew earlier studies focus on (1) age-related variation in PAEHR use and (2) user perceptions of the PAEHR technology and the health record information and how the technology and information–related perceptions are linked to each other.

A geometric nonlinear stochastic filter for simultaneous localization and mapping

Simultaneous Localization and Mapping (SLAM) is one of the key robotics tasks as it tackles simultaneous mapping of the unknown environment defined by multiple landmark positions and localization of the unknown pose (i.e., attitude and position) of the robot in three-dimensional (3D) space. The true SLAM problem is modeled on the Lie group of SLAMn(3), and its true dynamics rely on angular and translational velocities. This paper proposes a novel geometric nonlinear stochastic estimator algorithm for SLAM on SLAMn(3) that precisely mimics the nonlinear motion dynamics of the true SLAM problem. Unlike existing solutions, the proposed stochastic filter takes into account unknown constant bias and noise attached to the velocity measurements. The proposed nonlinear stochastic estimator on manifold is guaranteed to produce good results provided with the measurements of angular velocities, translational velocities, landmarks, and inertial measurement unit (IMU). Simulation and experimental results reflect the ability of the proposed filter to successfully estimate the six-degrees-of-freedom (6 DoF) robot's pose and landmark positions.

The use of personal weather station observations to improve precipitation estimation and interpolation

Abstract. The number of personal weather stations (PWSs) with data available through the internet is increasing gradually in many parts of the world. The purpose of this study is to investigate the applicability of these data for the spatial interpolation of precipitation using a novel approach based on indicator correlations and rank statistics. Due to unknown errors and biases of the observations, rainfall amounts from the PWS network are not considered directly. Instead, it is assumed that the temporal order of the ranking of these data is correct. The crucial step is to find the stations which fulfil this condition. This is done in two steps – first, by selecting the locations using the time series of indicators of high precipitation amounts. Then, the remaining stations are then checked for whether they fit into the spatial pattern of the other stations. Thus, it is assumed that the quantiles of the empirical distribution functions are accurate. These quantiles are then transformed to precipitation amounts by a quantile mapping using the distribution functions which were interpolated from the information from the German National Weather Service (Deutscher Wetterdienst – DWD) data only. The suggested procedure was tested for the state of Baden-Württemberg in Germany. A detailed cross validation of the interpolation was carried out for aggregated precipitation amount of 1, 3, 6, 12 and 24 h. For each of these temporal aggregations, nearly 200 intense events were evaluated, and the improvement of the interpolation was quantified. The results show that the filtering of observations from PWSs is necessary as the interpolation error after the filtering and data transformation decreases significantly. The biggest improvement is achieved for the shortest temporal aggregations.

On extended state based Kalman filter for nonlinear time-varying uncertain systems with measurement bias

This paper addresses the state estimation for a class of nonlinear time-varying stochastic systems with both uncertain dynamics and unknown measurement bias. A novel extended state based Kalman filter (ESKF) algorithm is developed to estimate the original state, the uncertain dynamics and the measurement bias. It is shown that the estimation error of the proposed algorithm is bounded in the mean square sense. Also, the estimation of the measurement bias asymptotically converges to its true value, such that the influence of measurement bias is eliminated. Furthermore, the asymptotic optimality of the estimation result is proved while the uncertain dynamics approaches to a constant vector. Finally, a simulation study for harmonic oscillator system model is provided to illustrate the effectiveness of proposed method.

Nonlinear Filter for Simultaneous Localization and Mapping on a Matrix Lie Group Using IMU and Feature Measurements

Simultaneous localization and mapping (SLAM) is a process of concurrent estimation of the vehicle&#x2019;s pose and feature locations with respect to a frame of reference. This article proposes a computationally cheap geometric nonlinear SLAM filter algorithm structured to mimic the nonlinear motion dynamics of the true SLAM problem posed on the matrix Lie group of <inline-formula> <tex-math notation="LaTeX">$\mathbb {SLAM}_{n}(3)$ </tex-math></inline-formula>. The nonlinear filter on manifold is proposed in continuous form and it utilizes available measurements obtained from group velocity vectors, feature measurements, and an inertial measurement unit (IMU). The unknown bias attached to velocity measurements is successfully handled by the proposed estimator. Simulation results illustrate the robustness of the proposed filter in discrete form, demonstrating its utility for the six-degrees-of-freedom (6 DoF) pose estimation as well as feature estimation in three-dimensional (3-D) space. In addition, the quaternion representation of the nonlinear filter for SLAM is provided.

Two‐Stage Cubature Kalman Filtering Based on T‐Transform and Its Application

According to the actual application system model which has bias, this paper analyzes the shortage of the conventional augmented algorithm, the two‐stage cubature Kalman filtering algorithm, which is presented on the basis of a two‐stage nonlinear transformation. The core ideas of the algorithm are to obtain the block diagonalization of the covariance matrix using the matrix transformation and avoid calculating the covariance of the state and bias to reduce the amount of calculation and ensure a smooth filtering process. Then, the equivalence of the two‐stage cubature Kalman filtering algorithm and the cubature Kalman filtering algorithm is proved by updating equivalent transformation. Through the experiment of trajectory tracking of a wheeled robot, it is verified that the two‐stage cubature Kalman filtering algorithm can obtain good tracking accuracy and stability with the presence of unknown random bias. Simultaneously, the equivalence of the two‐stage cubature Kalman filtering algorithm and cubature Kalman filtering algorithm is verified again using the contrast experiment.

Algorithms of Machines and Law

Pattern recognition, machine learning and artificial intelligence offer tremendous opportunities for efficient operations, management and governance. They can optimise processes for object, text, graphics, speech and pattern recognition. In doing so the algorithmic processing may be subject to unknown biases that do harm rather than good. We examine how this may happen, what damage may occur and the resulting ethical/legal impact and newly manifest obligations to avoid harm to others from these systems. But what are the risks, given the Human Condition?

Landmark and IMU Data Fusion: Systematic Convergence Geometric Nonlinear Observer for SLAM and Velocity Bias

Navigation solutions suitable for cases when both autonomous robot's pose (\textit{i.e}., attitude and position) and its environment are unknown are in great demand. Simultaneous Localization and Mapping (SLAM) fulfills this need by concurrently mapping the environment and observing robot's pose with respect to the map. This work proposes a nonlinear observer for SLAM posed on the manifold of the Lie group of $\mathbb{SLAM}_{n}\left(3\right)$, characterized by systematic convergence, and designed to mimic the nonlinear motion dynamics of the true SLAM problem. The system error is constrained to start within a known large set and decay systematically to settle within a known small set. The proposed estimator is guaranteed to achieve predefined transient and steady-state performance and eliminate the unknown bias inevitably present in velocity measurements by directly using measurements of angular and translational velocity, landmarks, and information collected by an inertial measurement unit (IMU). Experimental results obtained by testing the proposed solution on a real-world dataset collected by a quadrotor demonstrate the observer's ability to estimate the six-degrees-of-freedom (6 DoF) robot pose and to position unknown landmarks in three-dimensional (3D) space. Keywords: Simultaneous Localization and Mapping, Nonlinear filter for SLAM, Nonlinear filter for SLAM on Matrix Lie group, pose, asymptotic stability, prescribed performance, adaptive estimate, feature, inertial measurement unit, inertial vision unit, IMU, SE(3), SO(3), noise.