The research of vision system for rechargeable docking robot

随着机器视觉技术的快速发展，使得机器人技术在生产和生活领域中的应用越来越多。本文开发的充电对接机器人的视觉系统就是基于机器视觉技术发展而来，其主要目的就是为充电对接机器人提供视觉引导，使其能够完成对电动汽车插座的检测及定位。 本文采用了FPGA的硬件处理平台，应用了NiosII嵌入式技术，将开发的以电动汽车插座为目标的检测定位算法进行了系统植入，最终实现了系统在对接区域内对目标的高精度检测及定位。 完成的主要工作有： 首先，对基于FPGA的双目视觉系统的硬件模块进行了设计，主要涉及硬件模块的选型和相应电路的功能设计。在搭建完系统的硬件平台后，我们通过NiosII系统的构建，完成了系统的图...In recent years, the application fields of robotics technology have become more and more extensive with the rapid development of machine vision technology. The vision system of rechargeable docking robot this paper aiming to develop is based on this machine vision technology, the main purpose of which is to provide a vision system for rechargeable docking robot, to enable it to identify and locate...学位：工学硕士院系专业：航空航天学院_车辆工程学号：1992013115290

Determination of the number of ψ(3686) events taken at BESIII

The number of ψ(3686) events collected by the BESIII detector during the 2021 run period is determined to be (2259.3±11.1)×106 by counting inclusive ψ(3686) hadronic events. The uncertainty is systematic and the statistical uncertainty is negligible. Meanwhile, the numbers of ψ(3686) events collected during the 2009 and 2012 run periods are updated to be (107.7±0.6)×106 and (345.4±2.6)×106, respectively. Both numbers are consistent with the previous measurements within one standard deviation. The total number of ψ(3686) events in the three data samples is (2712.4±14.3)×10^

Prediction of Energy Resolution in the JUNO Experiment

International audienceThis paper presents the energy resolution study in the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The study reveals an energy resolution of 2.95% at 1 MeV. Furthermore, the study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data taking. Moreover, it provides a guideline in comprehending the energy resolution characteristics of liquid scintillator-based detectors

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies