能效型步行机的计算机辅助研究

本学位论文根据移动耗能率的定义,推导了步行机移动耗能率的计算公式.用计算机模拟计算方法,研究了步行机的9个基本参数所决定的移动耗能率的曲线,得到了有关步行机的运动姿态以及腿足数目等对于步行机能量效率的影响问题的几个重要结论;首次提出了用机体自由度概念来评价步行机机能水平的观点,并     

基于群论的六足机器人运动空间研究

针对六足机器人相对复杂的机械结构,提出一个简化模型结构,利用等条件约束把腿支链转化为滑动连杆.其次,针对简化后的模型,依据其运动约束方程,分析研究六足机器人可达空间以及姿态空间.在群论基础上,结合六足机器人的运动约束模型,着重分析机器人初始状态的对称性与其运动空间对称性的关系,并通过分层搜索算法,求解六足机器人运动空间.最后通过仿真数据分析六足机器人运动空间随不同参数调整的变化情况,对比分析机器人不同初始状态与其运动空间的关系,同时对运动平台的姿态空间及其截面进行分析.分析与仿真结果表明,利用群约束模型可以对复杂并联机器人运动空间进行更详尽的分析,得到包括空间对称性、姿态空间以及空间截面的详细信息.     

四足机器人腿型配置的仿真分析与性能评价

对于四足机器人,腿型和关节姿态的布置形式极为重要,决定着机器人的运动学和动力学性能;四足机器人的腿型配置形式多样,为了在有效行走的前提下分析不同腿型配置的四足机器人的性能优劣和效率高低,采用基于CPG的仿生步态算法进行运动控制,通过Matlab/Simulink与Adams联合仿真,从速度、能耗和地形适应性三方面对不同腿型配置的四足机器人进行仿真分析和性能评价;通过对比仿真结果得知,前肘后膝型机器人前进速度更快,运动更平稳,横向偏移更小,能耗更低,具有更好的地形适应性,运动性能更优越,为物理样机调试与优化提供了理论依据。     

四足仿生机器人单腿系统

为实现四足仿生机器人动步态行走,设计一款基于液压驱动方式的机器人仿生单腿系统.首先,在四足哺乳动物肌肉-骨骼结构分析的基础上,确定了机器人单腿的自由度配置;其次,通过机器人在平坦路面上的行走运动仿真,获得关节输出特性;随后,在仿真研究的基础上,完成了关节驱动机构设计、液压驱动器选型、4自由度单腿设计以及控制系统设计;最后,搭建单腿子系统性能测试平台,并完成了单腿纵向弹跳实验.弹跳实验验证了机械结构和控制系统设计的正确性和相关控制算法的有效性.     

远程雷达与目标仿真的相对方位计算方法

在雷达探测飞行器目标的仿真过程中,需要计算目标被电磁波照射的方位,并且判断目标是否在雷达的探测范围内,还要根据距离计算检测概率,故需要求出雷达和目标的相对方位以及两者的距离.建立地球坐标系,计算雷达和目标的位置、姿态在这个坐标系下的分量表示.再根据这些分量求出距离.计算相对方位时,先计算目标在雷达坐标系下的分量表示和雷达在目标坐标系下的分量表示.再根据这些分量来计算相对方位角和仰角.     

基于单目显微视觉的微球姿态测量方法

微零件的姿态测量对微装配具有重要的作用.但对于微球零件,其姿态的精确测量存在困难,影响了装配精度.针对带有微孔的微球,本文提出了一种基于单目显微视觉的微球姿态高精度测量方法.设计了一种由粗到精的微孔检测算法,实现了高精度的微孔定位.通过对相机光轴方向的标定,在相机运动后对微球图像坐标进行补偿,提高了在相机坐标系下的微球定位精度.通过对微球和微孔的精确定位,计算出微球球心与微孔圆心的空间相对位置,实现了相机坐标系下高精度的微球姿态测量.同时,根据标定出的相机坐标系与调整平台坐标系之间的旋转关系,将微球姿态转换到调整平台坐标系.实验结果表明,最大姿态测量误差0.3度,验证了本文方法的有效性.     

步行机器人的研究

1.首先介绍了步行机步态的定义及四足步行机的对称规则步态,在此基础上,对四足步行机稳定性问题进行了深入的研究,提出了基于能量考虑(计入运动速度影响)稳定性分析计算的能量法.2.详细讨论了运动主平面与垂直旋转轴具有偏距的圆柱型空间缩放式腿机构运动学,对四足步行机进行了与运动学控制有关的运动分析,给出了步行机运动速度与步态之间的关系,机体速度加速度与足端速度加     

面向复杂地形的四足机器人步态生成方法

为实现四足机器人在凹凸地形上稳定运动并能选择最大步长的目的,提出了基于稳定裕度的步态规划方法;基于研究对象,建立四足机器人的运动学方程及逆运动学方程,将机器人足端的位置映射为各关节的关节变量;提出工作空间矩阵的概念,将所需克服的地形高度反映到工作空间矩阵中,并选择最优步态区域;依据四足机器人的立足点在质心坐标系下的空间坐标,以纵向稳定裕度为约束条件,在工作空间矩阵中计算机器人摆动腿的最大步长并规划机械腿的运动轨迹;针对所提出的方法,分别利用MATLAB和ADAMS进行仿真验证;在MATLAB环境中计算并验证质心的水平投影是否在立足点形成支撑多变形内,而ADAMS平台分析机器人在复杂地形上的位移变化及姿态变化。仿真结果表明机器人的质心始终在支撑多边形内,机器人的躯干姿态基本保持不变且运动速度匀速,所提出的方法能够保证机器人稳定行走,为四足机器人的稳定运动提出依据。     

基于重心动力学及虚拟模型的负载型四足步行平台对角步态控制方法

为提高负载型四足步行平台对角步态行走的稳定性,减小较大的腿部质量及偏心质量对稳定行走的影响,提出融合重心动力学及虚拟模型的控制方法．应用虚拟模型控制方法对机身及摆动腿加速度进行求解．结合平台重心动力学模型得到其所受合外力,而后应用二次规划将平台合外力分配到支撑腿足端．接着运用逆向动力学和关节空间PD控制得到步行平台关节力矩．通过Adams和Simulink对负载型四足步行平台对角步态行走进行仿真,并将该方法与虚拟模型控制算法进行对比．结果表明重心动力学及虚拟模型控制方法能够使平台姿态角稳定在目标值附近,在平台受到侧向冲击情况下横滚角、俯仰角分别减小约42%、21.8%,在机身偏心全向行走过程中减小50%、89%．证明了所提控制方法能够有效应对较大的腿部质量及偏心质量的影响,提高负载型四足步行平台对角步态行走的稳定性和鲁棒性．     

具有悬挂系统的轮腿式机器人设计与分析

设计了一种具有独立悬挂系统和足端缓冲机构的六足轮腿式机器人.该机器人结合了轮式机器人和腿式机器人的优点,同时将汽车的独立悬挂系统的设计思想应用在机器人上,降低了不平整地面对机器人的冲击,并减轻了由此引起的振动,保证了机器人在不同的复杂环境下机身内部环境的稳定.本文对该机器人的机构与结构进行阐述,建立了其运动学模型以及其悬挂系统机构和足端缓冲机构的单自由度振动模型,并对其缓冲机理进行分析对比.通过ADAMS仿真软件在不同地形环境下对其进行动力学仿真分析,验证了在机器人的运动过程中,与足端缓冲机构相比,悬挂系统的缓冲减震效果受地形影响较小,且悬挂系统和足端缓冲机构相结合会比单一缓冲机构具有更好的缓冲减震作用.     

Acceptable loads and locomotor patterns selected in different carriage methods

The purpose of this study was twofold: (1) to assess the reliability of both the psychophysical method in determining maximum acceptable loads (MAL) and the use of selected gait parameters in describing locomotor patterns; and (2) to describe and compare the locomotor patterns associated with a number of common load carriage strategies involving the hands and arms. A test-retest experimental design was utilized. Ten males performed five tasks comprising four load carriage conditions and one normal walking condition over a 10m walking distance. The MAL for each carriage task was determined using procedures modified from those described by Snook et al. (1970). Preferred walking speed was calculated from the time taken to cover a standardized portion of the walking distance. The other gait parameters-stride length, cadence and total and double support periods-were obtained using a footswitch technology as described by Wall et al. (1981). The results demonstrated that the procedures used in this study were reliable, in that no significant test-retest differences were found for any of the dependent variables (MAL and gait parameters). No significant differences in MAL were found between the carriage strategies involving two hands, but significantly less mass was chosen in the one-hand carriage condition. Only the two-handed arms-straight carriage condition resulted in significantly different preferred walking speeds. All load carriage conditions except the one-hand carriage condition resulted in significant changes in stride length and/or cadence when compared with normal walking. Only one condition, involving the heaviest MAL, resulting in significantly different total and double support periods when compared with normal walking. There appear to be discrepancies in the literature regarding the effects of load carriage on the various gait parameters. Specific task characteristics, such as the method of carriage, load mass, speed and walking medium, were discussed as potential contributors to the seemingly contradictory results. Subject characteristics, such as gender, age and occupation, may also be confounding factors.     

Information-Theoretic Distance Measures for Clustering Validation: Generalization and Normalization

This paper studies the generalization and normalization issues of information-theoretic distance measures for clustering validation. Along this line, we first introduce a uniform representation of distance measures, defined as quasi-distance, which is induced based on a general form of conditional entropy. The quasi-distance possesses three properties: symmetry, the triangle law, and the minimum reachable. These properties ensure that the quasi-distance naturally lends itself as the external measure for clustering validation. In addition, we observe that the ranges of the distance measures are different when they apply for clustering validation on different data sets. Therefore, when comparing the performances of clustering algorithms on different data sets, distance normalization is required to equalize ranges of the distance measures. A critical challenge for distance normalization is to obtain the ranges of a distance measure when a data set is provided. To that end, we theoretically analyze the computation of the maximum value of a distance measure for a data set. Finally, we compare the performances of the partition clustering algorithm K-means on various real-world data sets. The experiments show that the normalized distance measures have better performance than the original distance measures when comparing clusterings of different data sets. Also, the normalized Shannon distance has the best performance among four distance measures under study.     

Clustering based on median and closest string via rank distance with applications on DNA

This paper aims to present several clustering methods based on rank distance. Rank distance has applications in many different fields such as computational linguistics, biology and computer science. The K-means algorithm represents each cluster by a single mean vector. The mean vector is computed with respect to a distance measure. Two K-means algorithms based on rank distance are described in this paper. Hierarchical clustering builds models based on distance connectivity. This paper describes two hierarchical clustering techniques that use rank distance. Experiments using mitochondrial DNA sequences extracted from several mammals are performed to compare the results of the clustering methods. Results demonstrate the clustering performance and the utility of the proposed algorithms.     

Phase and transition based batch process modeling and online monitoring

Multiple phases/stages with transitions from phase to phase are important characteristics of many batch processes. In order to model and monitor batch processes more accurately and efficiently, such process features are needed to be considered carefully. In this work, an index based on the angles between different principal component analysis (PCA) score spaces is developed to quantify the similarities between PCA models. Phase division algorithm is designed based on this new PCA similarity index, following by a statistical transition identification step. The steady phase ranges and transition ranges are then modeled separately. The transition models can be calculated by solving the optimization problems. Application examples show the advantages of the proposed method on both batch process modeling and online monitoring.     

Precise Agriculture: Effective Deep Learning Strategies to Detect Pest Insects

Pest insect monitoring and control is crucial to ensure a safe and profitable crop growth in all plantation types,as well as guarantee food quality and limited use of pesticides.We aim at extending traditional monitoring by means of traps,by involving the general public in reporting the presence of insects by using smartphones.This includes the largely unexplored problem of detecting insects in images that are taken in noncontrolled conditions.Furthermore,pest insects are,in many cases,extremely similar to other species that are harmless.Therefore,computer vision algorithms must not be fooled by these similar insects,not to raise unmotivated alarms.In this work,we study the capabilities of state-of-the-art(SoA)object detection models based on convolutional neural networks(CNN)for the task of detecting beetle-like pest insects on nonhomogeneous images taken outdoors by different sources.Moreover,we focus on disambiguating a pest insect from similar harmless species.We consider not only detection performance of different models,but also required computational resources.This study aims at providing a baseline model for this kind of tasks.Our results show the suitability of current SoA models for this application,highlighting how FasterRCNN with a MobileNetV3 backbone is a particularly good starting point for accuracy and inference execution latency.This combination provided a mean average precision score of 92.66%that can be considered qualitatively at least as good as the score obtained by other authors that adopted more specific models.     

Effects of prolonged load carriage on ground reaction forces, lower limb kinematics and spatio-temporal parameters in female recreational hikers

The effect of load carriage on female recreational hikers has received little attention. This study collected lower limb sagittal plane kinematic, spatio-temporal and ground reaction force (GRF) data from 15 female hikers carrying four loads (0%, 20%, 30% and 40% body weight (BW)) over 8 km. Increasing load resulted in a proportional increase in GRF up to 30% BW, increased stance time, and greater mediolateral impulse with 30% and 40% BW. Also seen were decreased velocity and cadence and increased double support and knee flexion when carrying load compared to no load. Increased distance resulted in increased knee flexion and ankle plantar flexion at initial foot-ground contact. It was concluded that, as load mass and distance increased, female hikers modified their gait to attenuate the lower limb impact forces. When carrying 30% and 40% BW loads, however, the changes aimed at attenuating the higher GRF may result in a less stable gait. PRACTITIONER SUMMARY: Limited research has investigated the biomechanical responses of female recreational hikers to prolonged load carriage. This study provides a better understanding of the effects of increasing load on lower limb kinematics, spatio-temporal parameters and the GRF generated by female hikers during prolonged load carriage. The results have implications for the development of load carriage guidelines to minimise the risk of injury to females who carry backpacks and to improve performance for this population.     

基于优化DRG的三维人体点云骨架提取方法

针对离散Reeb图（Discrete Reeb Graph,DRG）描述人体骨架时分支部位骨架线偏离中轴的问题,采用了能量函数最小化的方法对DRG曲线进行优化。将人体模型的DRG曲线作为初始骨架,定义其能量函数,在点云模型的距离场梯度的作用下,迭代地调整偏离中轴目标段的曲线位置使其逐渐逼近中轴,能量函数最小时得到优化的骨架。将该算法应用于同一模特四个不同姿势和四个不同模特同一姿势的人体点云模型,并与基于拉普拉斯算子的点云收缩的骨架提取方法进行了比较。结果表明,该算法能够很好地适应各种不同姿势和体型,模型分叉部位的特征得到更加完善的描述,得到的骨架曲线更接近模型的中轴。     

Effects of military load carriage on kinematics of gait

Manual load carriage is a universal activity and an inevitable part of the daily schedule of a soldier. Indian Infantry soldiers carry loads on the waist, back, shoulders and in the hands for a marching order. There is no reported study on the effects of load on gait in this population. It is important to evaluate their kinematic responses to existing load carriage operations and to provide guidelines towards the future design of heavy military backpacks (BPs) for optimising soldiers' performance. Kinematic changes of gait parameters in healthy male infantry soldiers whilst carrying no load (NL) and military loads of 4.2–17.5 kg (6.5–27.2% body weight) were investigated. All comparisons were conducted at a self-selected speed. Soldier characteristics were: mean (SD) age 23.3 (2.6) years; height 172.0 (3.8) cm; weight 64.3 (7.4) kg. Walk trials were collected using a 3-D Motion Analysis System. Results were subjected to one-way ANOVA followed by Dunnett post hoc test. There were increases in step length, stride length, cadence and midstance with the addition of a load compared to NL. These findings were resultant of an adaptive phenomenon within the individual to counterbalance load effect along with changes in speed. Ankle and hip ranges of motion (ROM) were significant. The ankle was more dorsiflexed, the knee and hip were more flexed during foot strike and helped in absorption of the load. The trunk showed more forward leaning with the addition of a load to adjust the centre of mass of the body and BP system back to the NL condition. Significant increases in ankle and hip ROM and trunk forward inclination (≥10°) with lighter loads, such as a BP (10.7 kg), BP with rifle (14.9 kg) and BP with a light machine gun (17.5 kg), may cause joint injuries. It is concluded that the existing BP needs design improvisation specifically for use in low intensity conflict environments.

Statement of Relevance:The present study evaluates spatial, temporal and angular changes at trunk and limb joints during military load carriage of relatively lighter magnitude. Studies on similar aspects on the specific population are limited. These data can be used for optimising load carriage and designing ensembles, especially a heavy BP, for military operations.     

Efficient algorithms for computing the best subset regression models for large-scale problems

Several strategies for computing the best subset regression models are proposed. Some of the algorithms are modified versions of existing regression-tree methods, while others are new. The first algorithm selects the best subset models within a given size range. It uses a reduced search space and is found to outperform computationally the existing branch-and-bound algorithm. The properties and computational aspects of the proposed algorithm are discussed in detail. The second new algorithm preorders the variables inside the regression tree. A radius is defined in order to measure the distance of a node from the root of the tree. The algorithm applies the preordering to all nodes which have a smaller distance than a certain radius that is given a priori. An efficient method of preordering the variables is employed. The experimental results indicate that the algorithm performs best when preordering is employed on a radius of between one quarter and one third of the number of variables. The algorithm has been applied with such a radius to tackle large-scale subset-selection problems that are considered to be computationally infeasible by conventional exhaustive-selection methods. A class of new heuristic strategies is also proposed. The most important of these is one that assigns a different tolerance value to each subset model size. This strategy with different kind of tolerances is equivalent to all exhaustive and heuristic subset-selection strategies. In addition the strategy can be used to investigate submodels having noncontiguous size ranges. Its implementation provides a flexible tool for tackling large scale models.     

Ranging-aided relative navigation of multi-platforms

This paper proposes a relative attitude and distance estimation algorithm based on pairwise range measurements between vehicles as well as inertial measurement of each platform. The solution of Wahba''s Problem is introduced to compute the relative attitude between multi-platforms with the sampled pairwise ranges, in which the relative distance estimation is derived and the estimation error distributions are analyzed. An extended Kalman filter is designed to fuse the estimated attitude and distance with the inertial measurement of each platform. The relative poses between platforms are determined without any external aided measurement. To show this novelty, a real testbed is constructed by our research lab. And the experiment results are positive.