水下循迹航行器水动力学性能数值研究

为了研究低速水下循迹监测航行器的水动力学性能数值计算问题,采用FLUENT软件和SST剪切应力输运模型,通过雷诺时均N-S方程分析流速一定的情况下,取不同攻角、不同水平舵角作为来流条件,研究未安装推进器以及安装推进器且其安装位置不同时,航行器的升力系数、俯仰力矩系数、表面压力分布和流场速度的变化规律。结果表明:在未安装推进器以及推进器的安装位置不同时,随着攻角的变化,升力系数呈线性变化,俯仰力矩系数呈非线性变化;随着水平舵角的变化,升力系数和俯仰力矩系数呈线性变化。当推进器安装在航行器头部时,对航行器流场压力和流场速度变化影响最大;当安装在航行器尾部时,对二者影响最小。对于低速航行器,应尽量将推进器安装在中间靠后位置,以提高航行器的水动力性能。升力系数的试验结果与数值仿真结果之间最大相差7. 51%,阻力系数的试验结果与数值仿真结果最大相差5. 84%,均吻合较好。研究结果可以为低速水下循迹航行器的优化设计和发展提供理论参考。     

EmotionMap: Visual Analysis of Video Emotional Content on a Map

Journal of Computer Science and Technology - Emotion plays a crucial role in gratifying users’ needs during their experience of movies and TV series, and may be underutilized as a framework...     

Autonomous industrial assembly using force,torque, and RGB-D sensing

ABSTRACT

We present algorithms and results for a robotic manipulation system that was designed to be easily programable and adaptable to various tasks common to industrial setting, which is inspired by the Industrial Assembly Challenge at the 2018 World Robotics Summit in Tokyo. This challenge included assembly of standard, commercially available industrial parts into 2D and 3D assemblies. We demonstrate three tasks that can be classified into ‘peg-in-hole’ and ‘hole-on-peg’ tasks and identify two canonical algorithms: spiral-based search and tilting insertion. Both algorithms use hand-coded thresholds in the force and torque domains to detect critical points in the assembly. After briefly summarizing the state of the art in research, we describe the strategy and approach utilized by the tested system, how it's design bears on its performance, statistics on 20 experimental trials for each task, lessons learned during the development of the system, and open research challenges that still remain.     

Rolling Kanban: a new visual tool to schedule family batch manufacturing processes with kanban

Rolling Kanban is the name of a kanban management methodology for batch processes manufacturing environment. Proposed in the early 2000s by FESTO Consulting, for two decades we have lost knowledge both from operative and scientific point of view. Basically, Rolling Kanban means a visual planning methodology based on the production of product-families and variants where: (i) set-up times are reduced between the products of the same family, and (ii) relevant times (dozens of minutes if not even hours) must be considered for changeover between products of different families. In addition, the cyclic production sequence between different product families cannot be maintained. Considering that very few technical information and documents are available about this approach, the main objective of this paper is to retrieve and present, for the first time to the scientific community, the Rolling Kanban methodology. Besides, a real industrial implementation concerning a manufacturer of domestic fittings is discussed as a case study. More specifically, two novel versions of the original Rolling Kanban technique are fully presented to effectively overcome certain limits and criticalities found during its operative use, such as the difficulty to realise a pull production, considering increased set-up time for changeover between products of different families.     

卫星激光通信粗跟踪系统复合控制策略

针对卫星激光通信粗跟踪系统的跟踪稳定精度指标要求高的特点,建立了基于永磁同步电机直接驱动的粗跟踪系统模型并进行了跟踪稳定误差分析。在采用传统PID控制策略存在跟踪误差较大、动态性能较差等不足的基础上,提出了一种基于粗跟踪系统的改进型前馈复合控制策略。从理论上分析了前馈复合控制策略提高了粗跟踪系统的动态性能,为降低跟踪稳定误差提供了改善方案。地面实验验证结果表明,与传统控制策略相比,改进型复合控制策略极大地降低了系统的动态跟踪误差,动态跟踪误差由606μrad降低至13μrad(1δ)。进一步的在轨实验也验证了改进型复合控制策略的合理性和先进性,总体指标满足了卫星激光通信终端的极高精度要求。本文所提出的控制策略对其他高性能跟踪伺服系统设计也具有较大的借鉴意义。     

Exploratory factor analysis and validity of the virtual reality symptom questionnaire and computer use survey

Abstract

The widespread use of virtual reality head-mounted-displays (HMDs) calls for a re-examination of the impact of prolonged exposure to fixed visual displays at close ocular proximity. The purpose of this study is to validate the Virtual Reality Symptoms Questionnaire (VRSQ), created to understand symptoms of prolonged HMDs use, and Computer Use Survey (CUS), created to assess general physical and visual discomfort symptoms. Participants (N?=?100) recorded their general discomfort symptoms using the CUS, performed an interactive task using a HMD for thirty minutes, and then answered the CUS again along with the VRSQ. VRSQ, analysed using an exploratory factor analysis, indicated a clear two-factor solution, and demonstrated very good internal consistency (α?=?0.873). The CUS, also analysed using an exploratory factor analysis, indicated a four-factor solution, and demonstrated good internal consistency (α?=?0.838).

Practitioner Summary: A quantitative-experimental study was conducted to explore the factor structure and validate both the Virtual Reality Symptoms Questionnaire (VRSQ), and the Computer Use Survey (CUS). Findings indicate the VRSQ and CUS are precise and accurate survey instruments for evaluating discomfort after VR-HMD use and the latter for computer use.

Abbreviations: VRSQ: virtual reality symptom questionnaire; CUS: computer use survey; OLED: organic light-emitting diode; MSQ: pensacola motion symptom questionnaire; SSQ: simulator sickness questionnaire; 3?D: three-dimensional computer generated space; VR: virtual reality; VR-HMD: virtual reality head-mounted-display; HMDs: head-mounted-displays; EFA: exploratory factor analysis     

Adaptive compensation of persistent actuator failures of nonlinear systems

In this article, adaptive compensation designs are developed for nonlinear systems with uncertainties from the system functions and persistent actuator failures of characterizations that (i) some unknown system inputs are stuck at some unknown fixed or varying values at unknown time instants and (ii) the failure pattern always switches from one to another and the switching does not stop. Such a controlled plant is described by an uncertain time-varying nonlinear system, and some robust adaptive feedback linearization based failure compensation results are studied for closed-loop system stabilization and bounded output tracking for some specific conditions. To improve the tracking performance in the presence of persistent actuator failures, a new adaptive control scheme is developed, using the failure indicator function which contains the failure pattern and failure time in the formulation. Detailed stability and tracking performance are shown. Simulation results are shown to verify the effectiveness of the proposed adaptive actuator failure compensation method.     

Adaptive actuator failure compensation for cooperative robotic manipulators with parameter uncertainties

This article develops a new framework of adaptive actuator failure compensation control for cooperative manipulator systems with parameter uncertainties in addition to actuator failures, and designs and analyzes effective actuator failure compensation schemes for such robotic systems. The new adaptive control design uses an integration of multiple individual failure compensators and direct adaptation to handle various types of uncertainties in such robotic systems. The design can also be used for concurrent actuator failure cases, to expand the capability of adaptive actuator failure compensation. With a complete proof and performance analysis, it is shown that the proposed control scheme guarantees the desired closed-loop stability and asymptotic output tracking, despite actuator failures whose patterns, time instants and values are all unknown. Simulation results of a benchmark cooperative manipulator system are presented to verify the desired control performance of the system with both typical constant and square-wave actuator failure signals.     

Looking ahead: Joint small group detection and tracking in crowd scenes

Small group detection and tracking in crowd scenes are basis for high level crowd analysis tasks. However, it suffers from the ambiguities in generating proper groups and in handling dynamic changes of group configurations. In this paper, we propose a novel delay decision-making based method for addressing the above problems, motivated by the idea that these ambiguities can be solved using rich temporal context. Specifically, given individual detections, small group hypotheses are generated. Then candidate group hypotheses across consecutive frames and their potential associations are built in a tree. By seeking for the best non-conflicting subset from the hypothesis tree, small groups are determined and simultaneously their trajectories are got. So this framework is called joint detection and tracking. This joint framework reduces the ambiguities in small group decision and tracking by looking ahead for several frames. However, it results in the unmanageable solution space because the number of track hypotheses grows exponentially over time. To solve this problem, effective pruning strategies are developed, which can keep the solution space manageable and also improve the credibility of small groups. Experiments on public datasets demonstrate the effectiveness of our method. The method achieves the state-of-the-art performance even in noisy crowd scenes.