Centroid Distance Keypoint Detector for Colored Point Clouds

Keypoint detection serves as the basis for many computer vision and robotics applications. Despite the fact that colored point clouds can be readily obtained, most existing keypoint detectors extract only geometry-salient keypoints, which can impede the overall performance of systems that intend to (or have the potential to) leverage color information. To promote advances in such systems, we propose an efficient multi-modal keypoint detector that can extract both geometry-salient and color-salient keypoints in colored point clouds. The proposed CEntroid Distance (CED) keypoint detector comprises an intuitive and effective saliency measure, the centroid distance, that can be used in both 3D space and color space, and a multi-modal non-maximum suppression algorithm that can select keypoints with high saliency in two or more modalities. The proposed saliency measure leverages directly the distribution of points in a local neighborhood and does not require normal estimation or eigenvalue decomposition. We evaluate the proposed method in terms of repeatability and computational efficiency (i.e. running time) against state-of-the-art keypoint detectors on both synthetic and real-world datasets. Results demonstrate that our proposed CED keypoint detector requires minimal computational time while attaining high repeatability. To showcase one of the potential applications of the proposed method, we further investigate the task of colored point cloud registration. Results suggest that our proposed CED detector outperforms state-of-the-art handcrafted and learning-based keypoint detectors in the evaluated scenes. The C++ implementation of the proposed method is made publicly available at https://github.com/UCR-Robotics/CED_Detector.Comment: Accepted to IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023; copyright will be transferred to IEEE upon publicatio

Development and Testing of a Novel Automated Insect Capture Module for Sample Collection and Transfer

There exists an urgent need for efficient tools in disease surveillance to help model and predict the spread of disease. The transmission of insect-borne diseases poses a serious concern to public health officials and the medical and research community at large. In the modeling of this spread, we face bottlenecks in (1) the frequency at which we are able to sample insect vectors in environments that are prone to propagating disease, (2) manual labor needed to set up and retrieve surveillance devices like traps, and (3) the return time in analyzing insect samples and determining if an infectious disease is spreading in a region. To help address these bottlenecks, we present in this paper the design, fabrication, and testing of a novel automated insect capture module (ICM) or trap that aims to improve the rate of transferring samples collected from the environment via aerial robots. The ICM features an ultraviolet light attractant, passive capture mechanism, panels which can open and close for access to insects, and a small onboard computer for automated operation and data logging. At the same time, the ICM is designed to be accessible; it is small-scale, lightweight and low-cost, and can be integrated with commercially available aerial robots. Indoor and outdoor experimentation validates ICM's feasibility in insect capturing and safe transportation. The device can help bring us one step closer toward achieving fully autonomous and scalable epidemiology by leveraging autonomous robots technology to aid the medical and research community.Comment: Accepted to IEEE International Conference on Automation Science and Engineering (CASE) 202

Analysis of Damage of Typical Composite/Metal Connecting Structure in Aircraft under the Influences of High-Velocity Fragments

A two-stage light gas gun was used to conduct a high-velocity impact test on the aircraft’s typical composite/metal connecting structure (CFRP/AL). The battle damage simulations used for the CFRP/AL connecting structure were carried out under different intersection conditions. Then, the damage morphology and mechanism of high-velocity prefabricated spherical fragments on typical structures, the dynamic process of hyper-velocity impact, and the formation of debris clouds on the secondary damage morphology of different component structures were investigated. Next, based on the X-ray computerized tomography (CT), the typical mode of different damage areas and evolution trends of CFRP under high-velocity impacts were explored. Finally, a simulation model was established for battle damages of typical structures by combining FEM methods, and structural components’ energy dissipation capabilities for fragments under different velocities were analyzed. The study results provide a reference and model support for the rapid repair of battle-damaged aircraft and aircraft survivability design

WDR73 Depletion Destabilizes PIP4K2C Activity and Impairs Focal Adhesion Formation in Galloway–Mowat Syndrome

(1) Background: Galloway–Mowat syndrome (GAMOS) is a rare genetic disease, classically characterized by a combination of various neurological symptoms and nephrotic syndrome. WDR73 is the pathogenic gene responsible for GAMOS1. However, the pathological and molecular mechanisms of GAMOS1, especially nephrotic syndrome caused by WDR73 deficiency, remain unknown. (2) Methods and Results: In this study, we first observed remarkable cellular morphological changes including impaired cell adhesion, decreased pseudopodia, and G2/M phase arrest in WDR73 knockout (KO) HEK 293 cells. The differentially expressed genes in WDR73 KO cells were enriched in the focal adhesion (FA) pathway. Additionally, PIP4K2C, a phospholipid kinase also involved in the FA pathway, was subsequently validated to interact with WDR73 via protein microarray and GST pulldown. WDR73 regulates PIP4K2C protein stability through the autophagy–lysosomal pathway. The stability of PIP4K2C was significantly disrupted by WDR73 KO, leading to a remarkable reduction in PIP2 and thus weakening the FA formation. In addition, we found that podocyte-specific conditional knockout (Wdr73 CKO) mice showed high levels of albuminuria and podocyte foot process injury in the ADR-induced model. FA formation was impaired in primary podocytes derived from Wdr73 CKO mice. (3) Conclusions: Since FA has been well known for its critical roles in maintaining podocyte structures and function, our study indicated that nephrotic syndrome in GAMOS1 is associated with disruption of FA caused by WDR73 deficiency