ABSTRACT
In recent years, with the widespread application of indoor inspection robots, high-precision, robust environmental perception has become essential for robotic mapping. Addressing the issues of visual-inertial estimation inaccuracies due to redundant pose degrees of freedom and accelerometer drift during the planar motion of mobile robots in indoor environments, we propose a visual SLAM perception method that integrates wheel odometry information. First, the robot's body pose is parameterized in SE(2) and the corresponding camera pose is parameterized in SE(3). On this basis, we derive the visual constraint residuals and their Jacobian matrices for reprojection observations using the camera projection model. We employ the concept of pre-integration to derive pose-constraint residuals and their Jacobian matrices and utilize marginalization theory to derive the relative pose residuals and their Jacobians for loop closure constraints. This approach solves the nonlinear optimization problem to obtain the optimal pose and landmark points of the ground-moving robot. A comparison with the ORBSLAM3 algorithm reveals that, in the recorded indoor environment datasets, the proposed algorithm demonstrates significantly higher perception accuracy, with root mean square error (RMSE) improvements of 89.2% in translation and 98.5% in rotation for absolute trajectory error (ATE). The overall trajectory localization accuracy ranges between 5 and 17 cm, validating the effectiveness of the proposed algorithm. These findings can be applied to preliminary mapping for the autonomous navigation of indoor mobile robots and serve as a basis for path planning based on the mapping results.
ABSTRACT
Objective: Diabetic hepatocellular carcinoma (HCC) patients have high mortality and metastasis rates. Diabetic conditions promote neutrophil extracellular traps (NETs) generation, which mediates HCC metastasis and invasion. However, whether and how diabetes-induced NETs trigger HCC invasion is largely unknown. Here, we aimed to observe the effects of diabetes-induced NETs on HCC invasion and investigate mechanisms relevant to a DNA sensor cyclic GMP-AMP synthase (cGAS). Methods: Serum from diabetic patients and healthy individuals was collected. Human neutrophil-derived NETs were isolated for stimulating HCC cell invasion. Data from the SEER and TCGA databases were used for bioinformatics analysis. In HCC cells and allograft models, NETs-triggered invasion was observed. Results: Diabetic HCC patients had poorer survival than non-diabetic ones. Either diabetic serum or extracted NETs caused HCC invasion. Induction of diabetes or NETosis elicited HCC allograft invasion in nude mice. HCC cell invasion was attenuated by the treatment with DNase1. In TCGA_LIHC, an extracellular DNase DNASE1L3 was downregulated in tumor tissues, while function terms (the endocytic vesicle membrane, the NF-κB pathway and extracellular matrix disassembly) were enriched. DNASE1L3 knockdown in LO2 hepatocytes or H22 cell-derived allografts facilitated HCC invasion in NETotic or diabetic nude mice. Moreover, exposure of HCC cells to NETs upregulated cGAS and the non-canonical NF-κB pathway and induced expression of metastasis genes (MMP9 and SPP1). Both cGAS inhibitor and NF-κB RELB knockdown diminished HCC invasion caused by NETs DNA. Also, cGAS inhibitor was able to retard translocation of NF-κB RELB. Conclusion: Defective DNASE1L3 aggravates NETs DNA-triggered HCC invasion on diabetic conditions via cGAS and the non-canonical NF-κB pathway.