Real-time Loop Research Articles

2DLIW-SLAM:2D LiDAR-inertial-wheel odometry with real-time loop closure

Due to budgetary constraints, indoor navigation typically employs two-dimensional (2D) LiDAR rather than 3D LiDAR. However, the utilization of 2D LiDAR in simultaneous localization and mapping (SLAM) frequently encounters challenges related to motion degeneracy, particularly in geometrically similar environments. To address this problem, this paper proposes a robust, accurate, and multi-sensor-fused 2D LiDAR SLAM system specifically designed for indoor mobile robots. To commence, the original LiDAR data undergoes meticulous processing through point and line extraction. Leveraging the distinctive characteristics of indoor environments, line–line constraints are established to complement other sensor data effectively, thereby augmenting the overall robustness and precision of the system. Concurrently, a tightly-coupled front-end is created, integrating data from the 2D LiDAR, inertial measurement unit, and wheel odometry, thus enabling real-time state estimation. Building upon this solid foundation, a novel global feature point matching-based loop closure detection algorithm is proposed. This algorithm proves highly effective in mitigating front-end accumulated errors and ultimately constructs a globally consistent map. The experimental results indicate that our system fully meets real-time requirements. When compared to cartographer, our system not only exhibits lower trajectory errors but also demonstrates stronger robustness, particularly in degeneracy problem. We open source our methods here: https://github.com/LittleDang/2DLIW-SLAM.

Cross-pathogenicity of Phytophthora palmivora associated with bud rot disease of oil palm and development of biomarkers for detection.

Phytophthora palmivora has caused disease in many crops including oil palm in the South America region. The pathogen has had a significant economic impact on oil palm cultivation in Colombia, and therefore poses a threat to oil palm cultivation in other regions of the World, especially in Southeast Asia, the largest producer of the crop. This study aimed to look at the ability of isolates from Malaysia, Colombia, and other regions to cross-infect Malaysian oil palm, durian, and cocoa and to develop specific biomarkers and assays for identification, detection, and diagnosis of P. palmivora as a key component for the oil palm biosecurity continuum in order to contain the disease especially at the ports of entry. We have developed specific molecular biomarkers to identify and detect Phytophthora palmivora using polymerase chain reaction (PCR) and real-time loop mediated isothermal amplification (rt-LAMP) in various sample types such as soil and plants. The limit of detection (DNA template, pure culture assay) for the PCR assay is 5.94 × 10-2 ng µl-1 and for rt-LAMP is 9.28 × 10-4 ng µl-1. Diagnosis using rt-LAMP can be achieved within 30min of incubation. In addition, PCR primer pair AV3F/AV3R developed successfully distinguished the Colombian and Malaysian P. palmivora isolates.

BoW3D: Bag of Words for Real-Time Loop Closing in 3D LiDAR SLAM

Loop closing is a fundamental part of simultaneous localization and mapping (SLAM) for autonomous mobile systems. In the field of visual SLAM, bag of words (BoW) has achieved great success in loop closure. The BoW features for loop searching can also be used in the subsequent 6-DoF loop correction. However, for 3D LiDAR SLAM, the state-of-the-art methods may fail to effectively recognize the loop in real time, and usually cannot correct the full 6-DoF loop pose. To address this limitation, we present a novel Bag of Words for real-time loop closing in 3D LiDAR SLAM, called BoW3D. Our method not only efficiently recognizes the revisited loop places, but also corrects the full 6-DoF loop pose in real time. BoW3D builds the bag of words based on the 3D LiDAR feature LinK3D, which is efficient, pose-invariant and can be used for accurate point-to-point matching. We furthermore embed our proposed method into 3D LiDAR odometry system to evaluate loop closing performance. We test our method on public dataset, and compare it against other state-of-the-art algorithms. BoW3D shows better performance in terms of F1 max and extended precision scores on most scenarios. It is noticeable that BoW3D takes an average of 48 ms to recognize and correct the loops on KITTI 00 (includes 4K+ 64-ray LiDAR scans), when executed on a notebook with an Intel Core i7 @2.2 GHz processor. We release the implementation of our method here: https://github.com/YungeCui/BoW3D.

Rapid and precise detection of cryptic tea pathogen Exobasidium vexans: RealAmp validation of LAMP approach.

This work embodies the development of a real time loop mediated isothermal amplification (RealAmp) assay for the rapid detection of the cryptic tea phytopathogen, Exobasidium vexans, the causal organism of blister blight disease. Due to the widespread popularity of tea as a beverage and the associated agro-economy, the rapid detection and management of the fast-spreading blister blight disease have been a longstanding necessity. Loop-mediated isothermal amplification (LAMP) primers were designed targeting the E. vexans ITS rDNA region and the reaction temperature was optimized at 62°C with a 60min reaction time. Amplification of the E. vexans isolates in the initial LAMP reactions was confirmed by both agarose gel electrophoresis and SYBR Green I dye based colour change visualization. The specificity of the LAMP primers for E. vexans was validated by negative testing of seven different phytopathogenic test fungi using LAMP and RealAmp assay. The positive findings in RealAmp assay for E. vexans strain were corroborated via detecting fluorescence signals in real-time. Further, the LAMP assays performed with gDNA isolated from infected tea leaves revealed positive amplification for the presence of E. vexans. The results demonstrate that this rapid and precise RealAmp assay has the potential to be applied for field-based detection of E. vexans in real-time.

Conductive Heat Transfer in Thermal Bridges

A thermal bridge is a component of a building that is characterized by a higher thermal loss compared with its surroundings. Their accurate modeling is a key step in energy performance analysis due to the increased awareness of the importance of sustainable design. Thermal modeling in architecture and engineering is often not carried out volumetrically, thereby sacrificing accuracy for complex geometries, whereas numerical textbooks often give the finite element method in much higher generality than required, or only treat the case of uniform materials. Despite thermal modeling traditionally belonging exclusively to the engineer’s toolbox, computational and parametric design can often benefit from understanding the key steps of finite element thermal modeling, in order to inform a real-time design feedback loop. In this entry, these gaps are filled and the reader is introduced to all relevant physical and computational notions and methods necessary to understand and compute the stationary energy dissipation and thermal conductance of thermal bridges composed of materials in complex geometries. The overview is a self-contained and coherent expository, and both physically and mathematically as correct as possible, but intuitive and accessible to all audiences. Details for a typical example of an insulated I-beam thermal bridge are provided.

Diagnostic utility and validation of a newly developed real time loop mediated isothermal amplification method for the detection of SARS CoV-2 infection

BackgroundDetecting SARS-CoV-2 using a simple real time molecular assay will be helpful for the mitigation efforts in low / middle income countries during the pandemic. We have developed and validated a rapid and simple real time loop mediated isothermal amplification assay (LAMP) for screening of SARS-CoV-2 infection in known infected and non-infected individuals. MethodsSix sets of primers were designed targeting the N-gene of the SARS-CoV-2 (Accession ID MN994468). LAMP reactions were performed using Warm Start 2X Master Mix and real-time PCR machine at 65 °C for 60 cycles with 15 s for each cycle. Results were read by visualizing turbidity under ultraviolet light and real time fluorescence detection through FAM channel of the real time PCR machine. We tested a total of 320 including 240 SARS CoV-2 positive (Ct values <40) and 80 SARS CoV-2 negative samples as tested by a real time RT-PCR using the newly developed LAMP assay. ResultsA total of 206 out of 240 SARS CoV-2 positive samples were tested positive by the newly developed LAMP assay with a sensitivity of 86%. All 80 SARS CoV-2 negative samples were tested negative by the newly developed LAMP assay with a specificity of 100%. ConclusionThe newly developed real time LAMP assay has a sensitivity of 86% and specificity of 100% compared to the real time RT-PCR for the detection of SARS CoV-2. The new assay will be useful to screen large number of samples if adopted to minimize the time and cost.

Application of the MiL and HiL Simulation Techniques in Stewart Platform Control Development

During the integration phase of a system development, we are often concerned as to whether the designed control algorithm could be performed on the selected controller in real-time. One of the tools to test and validate the control scheme is the Hardware-in-the-Loop (HiL) simulation technique, which is a part of a model-based design methodology. This approach requires a simulation model of a controlled system running in a real-time loop with an intended controller and a control algorithm, which are objects of interest in this method. To perform the test, the control algorithm must be deployed to the controller such as a PLC. This paper presents a use case of the HiL technique in the design of the Stewart platform control, where the controller is PLCnext from Phoenix Contact. The control algorithm was first verified in the Model-in-the-Loop simulation (MiL) and then generated as a code from the Matlab/Simulink environment and deployed to the PLCnext, which resulted in a smoother transition from the design to the integration and testing phase. The presented method is also applicable to other controllers that support code generation.

A Field Deployable Real-Time Loop Mediated Isothermal Amplification (LAMP) Targeting Five Copy nrdB Gene for the Detection of ‘Candidatus Liberibacter Asiaticus’ in Citrus

A Field Deployable Real-Time Loop Mediated Isothermal Amplification (LAMP) Targeting Five Copy nrdB Gene for the Detection of ‘Candidatus Liberibacter Asiaticus’ in Citrus

Abstract 13419: Novel Methods to Quantify Limitation of Right Ventricular Exercise Reserve in Pulmonary Hypertension: Afterload vs Ventricular Interdependency

Introduction: In this study, we report novel methods to investigate impact of pulmonary arterial (PA) afterload with impedance and ventricular interdependency with myocardial strain on right ventricular (RV) reserve with exercise and RV:PA coupling. Hypothesis: In pre-capillary pulmonary hypertension (PH), RV is conditioned to a higher contractility (end-systolic elastance: Ees) due to increased impedance and RV reserve is independent of left ventricle. However, in isolated post-capillary PH (Ipc-PH), RV is not conditioned due to lower impedance, yet contractility reserve is poor due to lower interventricular septal strain. Methods: In 4 subjects (Table 1), we performed invasive cardiopulmonary exercise tests with simultaneous echocardiogram for impedance quantification with spectral analysis, followed by real-time RV pressure volume loops (Figure 1A: data recorded at rest and every 25 watts till peak-exercise). Cardiac MRI was performed within 24-hours to assess myocardial function, strain, and 4D flow at rest and exercise in the bore. Results: The augmentation of RV contractility (Ees) with exercise is poor in Ipc-PH, despite an afterload (Ea) similar to the normal subject. The left ventricular septal strain is reduced in Ipc-PH which may indicate enhanced interventricular dependency. Due to increased afterload in pre-capillary PH, RV is conditioned to higher contractility (Ees), and RV reserve is possibly independent of the left ventricle. Conclusion: Our novel methods provide an opportunity to investigate mechanisms of poor RV reserve with exercise in different phenotypes of PH. We will further validate these preliminary findings in our ongoing studies.

Publico – A Digital Tool for Pandemic Crisis Communication and Management

"COVID-19 vividly demonstrates the global challenges of crisis communication. A flood of pandemic-related information from various sources and highly variable quality is inundating media platforms. To counter this “infodemic”, providing high-quality information is not sufficient. Real-time feedback loops from the public to policy-makers are urgently needed to better align communication strategies, actions taken, and public perception. To achieve this, the PubliCo online platform was launched in November 2020 in Switzerland. It follows a transdisciplinary multi-stakeholder approach rooted in participatory citizen science. PubliCo (https://publico.community/en/) includes three parts: 1. PubliCo Survey, collecting quantitative data, e.g. on moral preferences, while feeding back contextualized, tailored information to users; 2. PubliCo Diaries, collecting in-depth qualitative data, which also informs efforts to adapt PubliCo Survey to the evolving situation; and 3. PubliCo Analytics, which allows policymakers and other platform users to continuously analyse the collected data. We will present the PubliCo concept, considering the following key points: 1. Ethical considerations in the development of PubliCo concerning citizen science and crisis management. 2. PubliCo as a practical tool to implement the procedural ethics concepts such as Accountability for Reasonableness. 3. Lessons learned challenges, and opportunities for the transferability of PubliCo to better manage future crises in different global contexts. With our contribution, we aim to simulate a discussion on the ethical aspects of crisis communication and the strengths and limitations of citizen participation. "

Learning whole-image descriptors for real-time loop detection and kidnap recovery under large viewpoint difference

We present a real-time stereo visual-inertial-SLAM system which is able to recover from complicated kidnap scenarios and failures online in realtime. We propose to learn the whole-image-descriptor in a weakly supervised manner based on NetVLAD and decoupled convolutions. We analyze the training difficulties in using standard loss formulations and propose an allpairloss and show its effect through extensive experiments. Compared to standard NetVLAD, our network takes an order of magnitude fewer computations and model parameters, as a result runs about three times faster. We evaluate the representation power of our descriptor on standard datasets with precision–recall. Unlike previous loop detection methods which have been evaluated only on fronto-parallel revisits, we evaluate the performance of our method with competing methods on scenarios involving large viewpoint difference. Finally, we present the fully functional system with relative computation and handling of multiple world co-ordinate system which is able to reduce odometry drift, recover from complicated kidnap scenarios and random odometry failures. We open source our fully functional system as an add-on for the popular VINS-Fusion.

Real-time data assimilation and control on mechanical systems under uncertainties

This research work deals with the implementation of so-called Dynamic Data-Driven Application Systems (DDDAS) in structural mechanics activities. It aims at designing a real-time numerical feedback loop between a physical system of interest and its numerical simulator, so that (i) the simulation model is dynamically updated from sequential and in situ observations on the system; (ii) the system is appropriately driven and controlled in service using predictions given by the simulator. In order to build such a feedback loop and take various uncertainties into account, a suitable stochastic framework is considered for both data assimilation and control, with the propagation of these uncertainties from model updating up to command synthesis by using a specific and attractive sampling technique. Furthermore, reduced order modeling based on the Proper Generalized Decomposition (PGD) technique is used all along the process in order to reach the real-time constraint. This permits fast multi-query evaluations and predictions, by means of the parametrized physics-based model, in the online phase of the feedback loop. The control of a fusion welding process under various scenarios is considered to illustrate the proposed methodology and to assess the performance of the associated numerical architecture.

Development of a pair of real-time loop mediated isothermal amplification assays for detection of Yersinia pestis, the causative agent of plague

Yersinia pestis, the causative agent of plague mainly infects rodents, while humans are the accidental host. The conventional diagnostic methods available for Y. pestis exhibit cross-reactivity with other enteropathogenic bacteria which makes its detection difficult. Rapid and reliable point-of-care detection of Y. pestis is essential for timely initiation of medical treatment. In the present study, a pair of loop mediated isothermal amplification (LAMP) assays has been developed for rapid detection of Y. pestis. Two sets of LAMP primers, each containing 6 primers were specifically designed targeting caf1 and 3a genes located on pFra plasmid and chromosome of Y. pestis, respectively. Isothermal amplification was accomplished at 65 °C for 40 min for caf1 target, and at 63 °C for 50 min for 3a choromosomal target. The analytical sensitivity of the assay for the caf1 and 3a targets was found to be 500 fg and 100 fg genomic DNA of Y. pestis, respectively. The caf1 and 3a LAMP assays detected as few as 100 copies of caf1 and 10 copies of 3a gene targets harboured in the respective recombinant plasmids. The amplified products were detected visually under visible and UV light using SYBR Green 1 dye. The assay pair was found to be highly specific as it did not cross-react with closely related and other bacterial species.

Loop detection for 3D LiDAR SLAM using segment-group matching

Three-dimensional (3D) maps are indispensable for autonomous robot navigation in outdoor environments. Loop closure, which is a key technology in robotic mapping, is essential for creating consistent maps. This paper proposes an efficient method of loop detection for 3D-mapping. The proposed method detects loop constraints by estimating robot poses in revisited places using point-cloud registration. A difficulty in the registration is a large set of 3D points obtained by laser sensors, which requires a long processing time. To reduce the processing time, the proposed method employs a coarse-to-fine approach. Coarse estimation is performed using planes, lines, and balls instead of 3D points, and reduces the hypothesized loop constraints using geometric constraints between the segments. Subsequently, fine estimation is performed using the iterative closest points (ICP) algorithm and 3D points. Another difficulty is the precision of loop detection. To increase the precision, the proposed method employs robustification techniques such as outlier removal in the registration, combination of feature-based and pose-based methods, and robust pose adjustment. Experiments using large-scale datasets show that the proposed method realizes realtime loop detection in a variety of outdoor environments including cities, parks, and forest areas.

Range-Aided Pose-Graph-Based SLAM: Applications of Deployable Ranging Beacons for Unknown Environment Exploration

Simultaneous Localization and Mapping (SLAM) is a critical part of robotic exploration in unknown environments. SLAM over large scales typically presents challenges with limiting drift and requires loop closures to correct accumulated errors. However, real-time loop closure detection can be limited by high computational cost and susceptibility to outliers, especially in perceptually challenging, unknown, and large-scale environments. One solution to these challenges is to deploy ranging beacons from a robot and to utilize them for unambiguous place recognition. In this letter, we develop an architecture to take advantage of deployable ranging beacons in pose-graph SLAM. First, we highlight the inherent ambiguity in range measurements for sparsely deployed ranging beacons by analyzing the challenges in applying conventional methods of processing range measurements for localization. To both handle this ambiguity and address the challenges of loop closure for large-scale, perceptually challenging environments, we propose range-aided loop closure (RA-LC), an algorithm that combines beacon-based place recognition with geometric loop closures. We implement RA-LC in our hardware system and demonstrate the efficiency of RA-LC in field tests. Our results show that RA-LC can achieve equivalent accuracy of geometric-only lidar-based loop closure with significantly lower computational cost (95% reduction) and eight-times fewer outliers.

Real Time Loop Mediated Isothermal Amplification Assay of Urine for Diagnosis of Neurocysticercosis: A Preliminary Observation Study

Real Time Loop Mediated Isothermal Amplification Assay of Urine for Diagnosis of Neurocysticercosis: A Preliminary Observation Study

Development and application of an electronic treatment register: a system for enumerating populations and monitoring treatment during mass drug administration

ABSTRACT We developed an electronic treatment register for the DeWorm3 Project, a cluster-randomised, controlled trial in Benin, India, and Malawi testing the feasibility of interrupting transmission of soil-transmitted helminths through community-wide mass drug administration. The electronic treatment register was designed in xlsform, deployed via the SurveyCTO mobile data collection platform, and implemented on smartphones running the Android operating system. The versatile system enables collection of census and treatment status information, facilitates data aggregation and visualisation, and permits real-time feedback loops during implementation of mass drug administration. Here we describe the system’s design and use within the DeWorm3 Project and key features, and by sharing the register here, we hope our readers will further explore its use within their research and disease-control activities.

Validation of a Loop-Mediated Isothermal Amplification Assay for Rapid Diagnosis of Invasive Pneumococcal Disease.

Current molecular PCR-based techniques used for detecting Streptococcus pneumoniae, the causative pathogen of invasive pneumococcal disease (IPD), are accurate but have a run time of several hours. We aimed to develop and validate a novel real-time loop mediated amplification (LAMP) assay for rapid detection of pneumococcus in normally sterile samples with accuracy comparable to a gold standard real-time PCR. Conserved regions of lytA were used for the design of the LAMP test. Analytical validation included assessment of linearity, limit of detection (LOD), intra-assay and inter-assay precision and analytical specificity, which was evaluated by using reference strain S. pneumoniae R6 and a quality control panel. Clinical performance was assessed on all samples collected from children with suspicion of IPD attended in Hospital Sant Joan de Deu (Barcelona, Spain) during the period April-September 2015. Fresh samples were analyzed after DNA extraction. The following values of analytical parameters were determined: linearity within the range 108-104 copies/mL; limit of detection, 5·103 copies/mL; intra- and inter-assay precision measured by mean coefficient of variance, 3.61 and 6.59%; analytical specificity, 9/9 pathogens similar to S. pneumoniae and 14/14 strains of different S. pneumoniae serotypes correctly identified as negative and positive results, respectively. Diagnostic sensitivity and specificity values were 100.0 and 99.3%. Median time of DNA amplification was 15 min. The new LAMP assay showed to have similar accuracy as PCR while being 5-fold faster and could become a useful diagnostic tool for early diagnosis of IPD.

Active disturbance rejection consensus control of uncertain high-order nonlinear multi-agent systems

In this paper, we consider the consensus control problem for uncertain high-order nonlinear multi-agent systems in a leader-follower scheme. Each follower node is modeled by a high-order integrator incorporating with unmeasurable states and unknown nonlinear dynamics. First, the total uncertainty that lumps the unknown nonlinear dynamics and the mismatch of control is viewed as an extended state of the agent. By using local information from neighborhood set, a distributed extended state observer (ESO) is designed to estimate not only the unmeasurable agent states but also its total uncertainty. Then, based on the output of the ESO, a novel consensus control law is proposed, in which the total uncertainty is canceled out in the feedback loop in real time. We show that, with the application of the proposed approach, the ESO estimation errors and the disagreement error vectors between the leader and the followers can be made arbitrarily small. A simulation example is given to illustrate the effectiveness of the proposed consensus control method.

Sorting out difficulties in immunological diagnosis of neurocysticercosis: Development and assessment of real time loop mediated isothermal amplification of cysticercal DNA in blood

Purpose of the studyAmong various immunological tests available for diagnosis of neurocysticercosis (NCC), only EITB (Electroimmunotransfer blot for detection of anticysticercal antibodies) had gained widespread acceptance. However EITB is not available widely and is costly (Indian rupees 15,000/− approximately). We evaluated utility of Loop mediated isothermal amplification (LAMP) assay for detection of Taenia solium cox1 gene in blood of patients with NCC. Patients and methodsCurrent study included 100 consecutive patients of NCC at a tertiary teaching hospital in Northern India. All the patients underwent detailed history and examinations as well as gadolinium enhanced magnetic resonance imaging of brain. LAMP assay was performed in all the patients. The results were compared with 50 controls. ResultsLAMP detected Taenia Solium cox1 gene in 74% of all blood samples in patients of NCC.T he overall sensitivity of LAMP assay for detection of cox1 gene was 74% in all patients with NCC, 71.8% in patients with intraparenchymal brain cysts only and 86.7% of patients with extraparenchymal brain cysts with or without intraparenchymal brain cysts. The overall specificity of LAMP assay was 90% in all these three subgroups. The positive predictive value of real time LAMP assay was close to 93% for almost all forms of NCC- both solitary and multiple while negative predictive value ranged from 57 to 64%. ConclusionReal time LAMP assay of blood for detection of Taenia solium cox1 gene appears to be a promising toll for diagnosis of NCC.