A 6-DOF humanoid wall-climbing robot with flexible adsorption feet based on negative pressure suction

A wide range of dangerous and special tasks have witnessed the applications of wall-climbing robots, but they still cannot adapt well torough or sloping walls. This paper proposes a 6-DOF (degree of freedom) humanoid wall-climbing robot (HWCR) based on the principle of negative pressure suction. HWCR has the advantages of flexible adsorption feet, strong adaptability, strong anti-subversion performance, and high friction to the wall. We deduce mechanics formulas and carry out a parametric design of the foot structure so that it can meet the requirement of robot wall climbing. We use Fluent to analyze the flow field of the adsorption foot and determine the motor speed that can provide a reliable adsorption force. Using the D-H matrix to plan gait, we also design a compound cycloid-based foot trajectory to reduce the impact between the HWCR and the wall. Experiments on the uneven wall and sloping wall show that the vehicle can walk with an ideal gait, and the resistance value of the servo on each joint is much lower than the critical value, which ensures the smooth movement of the HWCR.     

Quality assessment for color correction-based stitched images via bi-directional matching

With the deepening of social information, the panoramic image has drawn a significant interest of viewers and researchers as it can provide a very wide field of view (FoV). Since panoramic images are usually obtained by capturing images with the overlapping regions and then stitching them together, image stitching plays an important role in generating panoramic images. In order to effectively evaluate the quality of stitched images, a novel quality assessment method based on bi-directional matching is proposed for stitched images. Specifically, dense correspondences between the testing and benchmark stitched images are first established by bi-directional SIFT-flow matching. Then, color-aware, geometric-aware and structure-aware features are respectively extracted and fused via support vector regression (SVR) to obtain the final quality score. Experiments on our newly constructed database and ISIQA database demonstrate that the proposed method can achieve comparable performance compared with the conventional blind quality metrics and the quality metrics specially designed for stitched images.     

2种侧围加强内框总成检具结构对比分析

概述了侧围加强内框总成与周边零件的匹配关系,从检具操作的人机工程出发,描述了侧围加强内框总成检具的2种定位方式和结构设计,对比了2种定位方式对于检测结果的影响,总结了其优点和弊端,结果表明侧围加强内框总成检具采用车内方向朝下的定位方式效果更好。     

SOINN-Based Abnormal Trajectory Detection for Efficient Video Condensation

With the evolution of video surveillance systems, the requirement of video storage grows rapidly; in addition, safe guards and forensic officers spend a great deal of time observing surveillance videos to find abnormal events. As most of the scene in the surveillance video are redundant and contains no information needs attention, we propose a video condensation method to summarize the abnormal events in the video by rearranging the moving trajectory and sort them by the degree of anomaly. Our goal is to improve the condensation rate to reduce more storage size, and increase the accuracy in abnormal detection. As the trajectory feature is the key to both goals, in this paper, a new method for feature extraction of moving object trajectory is proposed, and we use the SOINN (Self-Organizing Incremental Neural Network) method to accomplish a high accuracy abnormal detection. In the results, our method is able to shirk the video size to 10% storage size of the original video, and achieves 95% accuracy of abnormal event detection, which shows our method is useful and applicable to the surveillance industry.     

结合预训练模型和语言知识库的文本匹配方法

针对文本匹配任务,该文提出一种大规模预训练模型融合外部语言知识库的方法。该方法在大规模预训练模型的基础上,通过生成基于WordNet的同义—反义词汇知识学习任务和词组—搭配知识学习任务引入外部语言学知识。进而,与MT-DNN多任务学习模型进行联合训练,以进一步提高模型性能。最后利用文本匹配标注数据进行微调。在MRPC和QQP两个公开数据集的实验结果显示,该方法可以在大规模预训练模型和微调的框架基础上,通过引入外部语言知识进行联合训练有效提升文本匹配性能。     

面向智能客服系统的情感分析技术

该文以阿里小蜜为例,对智能客服系统中的情感分析技术进行比较全面的介绍,包括情感分析算法模型的原理及其在智能客服系统的多个应用场景中的实际落地使用方式和效果分析。智能客服在解决客户高频业务问题的同时,也需要给客户提供多维度的、具有类人能力的助理、导购、语聊和娱乐等服务,提高客户对智能客服机器人的整体满意度。在此过程中,情感分析技术在机器人类人能力建设中起到了至关重要的作用。该文围绕智能客服系统中人机结合的服务形式,从六个维度总结和介绍了情感分析技术在智能客服系统中的应用场景,包括用户情感检测、用户情感安抚、情感生成式语聊、客服服务质检、会话满意度预估和智能人工入口。     

地面微地震有源噪声自动识别与匹配压制方法

微地震监测技术通过对非常规储层压裂改造引发的震源点进行成像，实时提供压裂施工过程中产生的裂隙高度、长度、宽度和方位角等信息，为致密储层压裂提供指导，以提高油气采收率。在地面布设站点进行监测时，因微地震信号传播距离较远、近地表吸收衰减严重、地面有源噪声较多，微地震数据具有信号能量弱、噪声干扰强和信噪比低等特点，严重制约微地震事件的定位精度。噪声源多分布于地表，根据有源噪声与由储层向上传播的微地震事件在能量、频率、传播速度和源位置等方面的差异，本文提出微地震有源噪声自动识别与匹配方法。综合长短时窗能量比与微地震量板方法，自动识别有源噪声干扰，并进行噪声源位置和传播速度的三维最优并行搜索；利用同时确定的最优噪声源位置和传播速度对微地震数据进行动校正处理，得到噪声标准道，通过能量自适应匹配处理压制有源噪声。正演模拟数据和实际微地震数据去噪效果证明，本文方法能有效压制有源噪声，显著提高微地震数据品质，为后续微地震事件精确定位奠定了基础。     

高强度钢管道环焊缝隐患治理措施研究

针对国内管道建设过程中存在的很多问题,如建设过程中施工单位违规返修、检测单位对射线底片的漏评错评、监理单位监管缺失等,尤其是近年来突出的高强度钢管道环焊缝不能承受较大的外部载荷的问题,分析了高强度钢管道环焊缝与传统X65及以下钢级管道环焊缝失效特征的差异性,剖析了当前在役高强度钢管道焊接结构存在的问题,从系统工程的角度分析了高强钢管道焊接结构中焊缝与钢管管体抗拉强度匹配、变壁厚焊接结构应力集中、焊缝冲击韧性分散等方面存在的问题,并结合人力资源、配套资源和应用技术等因素提出了高强钢管道环焊缝隐患治理的建议,建立了高强度钢管道环焊缝关键风险控制的鱼骨图。     

基于近似测地线的分层次自动铺带轨迹规划方法

自动铺带技术是一种增量制造技术，适用于制造翼面、壁板等大尺寸、小曲率复合材料构件，具有加工成本低、效率高等特点。轨迹规划是自动铺带技术的关键环节，它直接关系到复合材料构件的成型精度与质量。现有的自动铺带轨迹规划方法难以便捷兼顾调控铺放间隙与防止铺放褶皱，保证铺带产品的最终质量。有鉴于此，提出了一种基于近似测地线的分层次铺放轨迹规划方法。主要目标是合理利用预浸带允许变形能力，在防止铺放褶皱产生的前提下，保证相邻带料不产生覆盖，且间隙不超过2.5 mm。首先，研究了铺放间隙的产生与演化规律，给出了几种典型曲面上初始铺放间隙的优化方法。接下来，提出了近似测地线的数学模型与求解格式。然后，基于铺放褶皱的产生机制与铺放间隙的演化规律，确定了近似测地线的测地曲率大小与符号。最后，在双曲面模具以及自由曲面模具上验证了所提出方法的有效性。