DRIVE: Data-driven Robot Input Vector Exploration

An accurate motion model is a fundamental component of most autonomous navigation systems. While much work has been done on improving model formulation, no standard protocol exists for gathering empirical data required to train models. In this work, we address this issue by proposing Data-driven Robot Input Vector Exploration (DRIVE), a protocol that enables characterizing uncrewed ground vehicles (UGVs) input limits and gathering empirical model training data. We also propose a novel learned slip approach outperforming similar acceleration learning approaches. Our contributions are validated through an extensive experimental evaluation, cumulating over 7 km and 1.8 h of driving data over three distinct UGVs and four terrain types. We show that our protocol offers increased predictive performance over common human-driven data-gathering protocols. Furthermore, our protocol converges with 46 s of training data, almost four times less than the shortest human dataset gathering protocol. We show that the operational limit for our model is reached in extreme slip conditions encountered on surfaced ice. DRIVE is an efficient way of characterizing UGV motion in its operational conditions. Our code and dataset are both available online at this link: https://github.com/norlab-ulaval/DRIVE.Comment: 6 pages, 7 figures, submitted to 2024 IEEE International Conference on Robotics and Automation (ICRA 2024

Present and Future of SLAM in Extreme Underground Environments

This paper reports on the state of the art in underground SLAM by discussing different SLAM strategies and results across six teams that participated in the three-year-long SubT competition. In particular, the paper has four main goals. First, we review the algorithms, architectures, and systems adopted by the teams; particular emphasis is put on lidar-centric SLAM solutions (the go-to approach for virtually all teams in the competition), heterogeneous multi-robot operation (including both aerial and ground robots), and real-world underground operation (from the presence of obscurants to the need to handle tight computational constraints). We do not shy away from discussing the dirty details behind the different SubT SLAM systems, which are often omitted from technical papers. Second, we discuss the maturity of the field by highlighting what is possible with the current SLAM systems and what we believe is within reach with some good systems engineering. Third, we outline what we believe are fundamental open problems, that are likely to require further research to break through. Finally, we provide a list of open-source SLAM implementations and datasets that have been produced during the SubT challenge and related efforts, and constitute a useful resource for researchers and practitioners.Comment: 21 pages including references. This survey paper is submitted to IEEE Transactions on Robotics for pre-approva

Transethnic, Genome-Wide Analysis Reveals Immune-Related Risk Alleles and Phenotypic Correlates in Pediatric Steroid-Sensitive Nephrotic Syndrome

International audienceBackground Steroid-sensitive nephrotic syndrome (SSNS) is a childhood disease with unclear pathophysiology and genetic architecture. We investigated the genomic basis of SSNS in children recruited in Europe and the biopsy-based North American NEPTUNE cohort.Methods We performed three ancestry-matched, genome-wide association studies (GWAS) in 273 children with NS (Children Cohort Nephrosis and Virus [NEPHROVIR] cohort: 132 European, 56 African, and 85 Maghrebian) followed by independent replication in 112 European children, transethnic meta-analysis, and conditional analysis. GWAS alleles were used to perform glomerular cis-expression quantitative trait loci studies in 39 children in the NEPTUNE cohort and epidemiologic studies in GWAS and NEPTUNE (97 children) cohorts.Results Transethnic meta-analysis identified one SSNS-associated single-nucleotide polymorphism (SNP) rs1063348 in the 3' untranslated region of HLA-DQB1 (P=9.3×10-23). Conditional analysis identified two additional independent risk alleles upstream of HLA-DRB1 (rs28366266, P=3.7×10-11) and in the 3' untranslated region of BTNL2 (rs9348883, P=9.4×10-7) within introns of HCG23 and LOC101929163 These three risk alleles were independent of the risk haplotype DRB1*07:01-DQA1*02:01-DQB1*02:02 identified in European patients. Increased burden of risk alleles across independent loci was associated with higher odds of SSNS. Increased burden of risk alleles across independent loci was associated with higher odds of SSNS, with younger age of onset across all cohorts, and with increased odds of complete remission across histologies in NEPTUNE children. rs1063348 associated with decreased glomerular expression of HLA-DRB1, HLA-DRB5, and HLA-DQB1.Conclusions Transethnic GWAS empowered discovery of three independent risk SNPs for pediatric SSNS. Characterization of these SNPs provide an entry for understanding immune dysregulation in NS and introducing a genomically defined classification

Outcome associated with prescription of cardiac rehabilitation according to predicted risk after acute myocardial infarction: Insights from the FAST-MI registries

International audienceCardiac rehabilitation is strongly recommended in patients after acute myocardial infarction

Ostéopathies fragilisantes, maladie rénale chronique, malabsorptions, anomalies biologiques du métabolisme phosphocalcique : les bonnes indications pour un remboursement raisonné du dosage de vitamine D [Weakening osteopathies, chronic kidney disease, malabsorption, biological anomalies of calium/phosphorus metabolism: appropriate indications for a reasoned reimbursment of serum vitamin D measurement]

National audienceEditoria

Value of biomarkers for predicting immunoglobulin A vasculitis nephritis outcome in an adult prospective cohort

International audienc