13 research outputs found

    Depth Completion with Multiple Balanced Bases and Confidence for Dense Monocular SLAM

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    Dense SLAM based on monocular cameras does indeed have immense application value in the field of AR/VR, especially when it is performed on a mobile device. In this paper, we propose a novel method that integrates a light-weight depth completion network into a sparse SLAM system using a multi-basis depth representation, so that dense mapping can be performed online even on a mobile phone. Specifically, we present a specifically optimized multi-basis depth completion network, called BBC-Net, tailored to the characteristics of traditional sparse SLAM systems. BBC-Net can predict multiple balanced bases and a confidence map from a monocular image with sparse points generated by off-the-shelf keypoint-based SLAM systems. The final depth is a linear combination of predicted depth bases that can be optimized by tuning the corresponding weights. To seamlessly incorporate the weights into traditional SLAM optimization and ensure efficiency and robustness, we design a set of depth weight factors, which makes our network a versatile plug-in module, facilitating easy integration into various existing sparse SLAM systems and significantly enhancing global depth consistency through bundle adjustment. To verify the portability of our method, we integrate BBC-Net into two representative SLAM systems. The experimental results on various datasets show that the proposed method achieves better performance in monocular dense mapping than the state-of-the-art methods. We provide an online demo running on a mobile phone, which verifies the efficiency and mapping quality of the proposed method in real-world scenarios

    Mechanistic exploration of polytetrafluoroethylene thermal plasma gasification through multiscale simulation coupled with experimental validation

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    Abstract The ever-growing quantities of persistent Polytetrafluoroethylene (PTFE) wastes, along with consequential ecological and human health concerns, stimulate the need for alternative PTFE disposal method. The central research challenge lies in elucidating the decomposition mechanism of PTFE during high-temperature waste treatment. Here, we propose the PTFE microscopic thermal decomposition pathways by integrating plasma gasification experiments with multi-scale simulations strategies. Molecular dynamic simulations reveal a pyrolysis—oxidation & chain-shortening—deep defluorination (POCD) degradation pathway in an oxygen atmosphere, and an F abstraction—hydrolysis—deep defluorination (FHD) pathway in a steam atmosphere. Density functional theory computations demonstrate the vital roles of 1O2 and ·H radicals in the scission of PTFE carbon skeleton, validating the proposed pathways. Experimental results confirm the simulation results and show that up to 80.12% of gaseous fluorine can be recovered through plasma gasification within 5 min, under the optimized operating conditions determined through response surface methodology

    Multiscale Simulation of polytetrafluoroethylene gasification using thermal plasma: Mechanism investigation with experimental validation

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    This repository contains the source data that support the findings of "Multiscale Simulation of polytetrafluoroethylene gasification using thermal plasma: mechanism investigation with experimental validation"
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