基于ADAMS和MATLAB的双足机器人运动轨迹规划和控制的联合仿真

相比ADAMS仿真的不稳定性,利用ADAMS和MATLAB联合仿真对双足机器人运动轨迹规划和控制设计的可靠性及高效性进行了研究。首先绘制双足机器人三维参数模型进行逆运动学分析,验证其合理性后导入ADAMS中添加约束,进行动力学仿真。基于此,在MATLAB中使用多项式插值法完成模型的步态规划。最后利用Simulink试验台建立控制系统的框图,由ADAMS输入关节角之后控制台输出关节的驱动力矩,完成双足机器人ADAMS和MATLAB的联合仿真。仿真结果显示,联合仿真相较于ADAMS仿真的波动性所获得的数据更加稳定,此法高效可行,可作为下一步设计双足机器人的控制系统电机选型的重要理论依据。     

准经典轨线法在反应动力学中的应用

"反应"是如何发生的是分子反应动力学研究的一个基本问题。但是要想精确地研究反应发生的本质始终是一个挑战。准经典轨线法在经典轨线方法的基础上进行了改进,既缩短了计算所需要的时间,又人为的引入了一些量子效应。所以该方法被广泛用于研究一些典型的小分子反应。     

Self-consistent kinetic theory with nonlinear wave-particle resonances

We have developed, based on the oscillating-center transformation, a general theoretical approach for self-consistent plasma dynamics including, explicitly, effects of nonlinear(higherorder) wave-particle resonances. A specific example is then given for low-frequency responses of trapped particles in axisymmetric tokamaks. Possible applications to transport as well as nonlinear wave growth/damping are also briefly discussed.     

电磁场作用下球形磁极辅助研磨弯管内表面研究

弯管弯曲成形后,在弯折处易产生微裂纹、褶皱等表面质量缺陷问题。本文通过采用六自由度机械手拖动电磁场发生装置沿加工轨迹往复运动,电磁场发生装置驱动球形辅助磁极绕管件内壁转动,实现了对弯管内表面的光整加工。在此基础上,通过对弯管轮廓采集及曲线拟合,重新构建了弯管中心线并转换为新的研磨加工轨迹。采用超景深3D电子显微镜和触针式表面粗糙度测量仪对研磨试验前后弯管内表面的形貌和粗糙度进行了对比分析。结果表明,通过重新构建研磨加工轨迹,试验装置有效解决了研磨弯折处的干涉与研磨不均匀等问题。研磨55 min后,表面粗糙度由原始的0.713μm降低到0.194μm,铜合金弯管内表面原始质量缺陷基本去除,表面纹理较为致密均匀。该方法有效避免了未规划研磨轨迹时出现的犁耕等纹理缺陷,提高了弯管的服役可靠性。     

高瓦斯矿井U型通风工作面瓦斯治理技术

针对李雅庄煤矿U型通风工作面上隅角及回风流瓦斯浓度高、瓦斯治理难度大的问题，根据工作面瓦斯来源及在采空区三带的运移储存规律，李雅庄煤矿开展了本煤层抽采工艺优化和裂隙带抽采技术研究。对本煤层钻孔封孔深度、联孔工艺、管路连接方式等进行优化，钻孔抽采浓度由抽采4个月后降低到9%提高到抽采10个月后维持在19%；通过调整裂隙带钻孔布置方式、优化钻孔布孔层位、采取下筛管护孔等技术措施，裂隙带钻场最高瓦斯抽采纯流量达13.6 m³/min，平均瓦斯抽采纯流量达8 m³/min，2个钻场联合抽采瓦斯纯流量在13 m³/min以上；取消了瓦斯措施巷、井下移动泵和上隅角风帘，上隅角和回风流平均瓦斯浓度分别控制在0.5%和0.4%以下，对高瓦斯矿井U型通风工作面瓦斯治理有借鉴意义。     

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。     

基于粒子群优化算法的五自由度机械臂轨迹规划

为了让机械臂的工作时间达到最优,以自主研发的抛光机器人样机为研究对象,针对手表表壳表耳部分的抛光过程,提出PSO算法对五自由度机械臂轨迹规划进行优化,并通过MATLAB软件进行机械臂的仿真与分析。仿真结果表明,基于PSO算法的轨迹规划使机械臂在工作过程中加加速度不会产生突变,运动轨迹精度高,机械臂工作时间达到最优。     

A hand gesture recognition technique for human–computer interaction

We propose an approach to recognize trajectory-based dynamic hand gestures in real time for human–computer interaction (HCI). We also introduce a fast learning mechanism that does not require extensive training data to teach gestures to the system. We use a six-degrees-of-freedom position tracker to collect trajectory data and represent gestures as an ordered sequence of directional movements in 2D. In the learning phase, sample gesture data is filtered and processed to create gesture recognizers, which are basically finite-state machine sequence recognizers. We achieve online gesture recognition by these recognizers without needing to specify gesture start and end positions. The results of the conducted user study show that the proposed method is very promising in terms of gesture detection and recognition performance (73% accuracy) in a stream of motion. Additionally, the assessment of the user attitude survey denotes that the gestural interface is very useful and satisfactory. One of the novel parts of the proposed approach is that it gives users the freedom to create gesture commands according to their preferences for selected tasks. Thus, the presented gesture recognition approach makes the HCI process more intuitive and user specific.     

共享交通的时空轨迹检索与群体发现

为解决共享交通下的共乘用户群体发现效率低、准确率不高问题，依据R-树原理建立GeoOD-Tree索引，并在此基础上提出以最大化共乘率为目标的群体发现策略。首先，对原始时空轨迹数据进行特征提取与标定处理，挖掘有效出行起讫点（OD）轨迹；其次，针对用户起讫点轨迹的特征，建立GeoOD-Tree索引进行有效的存储管理；最后，给出以最大化共乘行程为目标的群体发现模型，并运用K最近邻（KNN）查询对搜索空间剪枝压缩，提高群体发现效率。采用西安市近12000辆出租车营运轨迹数据，选取动态时间规整（DTW）等典型算法与所提算法在查询效率与准确率上进行性能对比分析。与DTW算法相比，所提算法的准确率提高了10.12%，查询效率提高了约15倍。实验结果表明提出的群体发现策略能有效提高共乘用户群体发现的准确率和效率，可有效提升共乘出行方式的出行率。     

A Global Maximum Error Controller Based Nonlinearity Aware TPWL Method for Reducing Nonlinear Systems

Abstract

Model order reduction is a common practice to reduce large order systems so that their simulation and control become easy. Nonlinearity aware trajectory piecewise linear is a variation of trajectory piecewise linearization technique of order reduction that is used to reduce nonlinear systems. With this scheme, the reduced approximation of the system is generated by weighted sum of the linearized and reduced sub-models obtained at certain linearization points on the system trajectory. This scheme uses dynamically inspired weight assignment that makes the approximation nonlinearity aware. Just as weight assignment, the process of linearization points selection is also important for generating faithful approximations. This article uses a global maximum error controller based linearization points selection scheme according to which a state is chosen as a linearization point if the error between a current reduced model and the full order nonlinear system reaches a maximum value. A combination that not only selects linearization points based on an error controller but also assigns dynamic inspired weights is shown in this article. The proposed scheme generates approximations with higher accuracies. This is demonstrated by applying the proposed method to some benchmark nonlinear circuits including RC ladder network and inverter chain circuit and comparing the results with the conventional schemes.