搜救型重組式機器人

[[abstract]]災難後的救援一直為世界各國所重視的議題，特別是要在極短時間內快速進行的救援工作，影響受難人員生存的關鍵，以及救難人員的風險。 主要目的是建立災難救援型機器人，其中所需要的移動設計概念與相關控制技術，期望可早日結合日益成熟且多樣化的技術，同時兼顧偵查、感測等功能。 本次的研究作品，設計上以單模組機器人為核心，運用運動模擬架構為出發點，再透過模組間的組成，達到各式理想運行的機器人，接著利用程式撰寫及編譯，使能夠控制模組移動的正常流暢，且透過程式的改變，轉彎能達到我們理想的旋轉方向，及旋轉至特定角度的需求，完成設計出單一模組，就能透過重組的思想，加以複製，就能組裝成許多形狀，完成理想指定的動作目標。 搜救型機器人的研發，在災難發生後的第一時間內，在危險和複雜的災難環境下，快速且自動的進行受難人員的偵查搜救，降低救難人員的危險，提高受難人員的生存機率

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