动态双足机器人的控制与优化研究进展

对动态双足机器人的可控周期步态的稳定性、鲁棒性和优化控制策略的国内外研究现状与发展趋势进行了探讨.首先,介绍动态双足机器人的动力学数学模型,进一步,提出动态双足机器人运动步态和控制系统原理;其次,讨论动态双足机器人可控周期步态稳定性现有的研究方法,分析这些方法中存在的缺点与不足;再次,研究动态双足机器人的可控周期步态优化控制策略,阐明各种策略的优缺点;最后,给出动态双足机器人研究领域的难点问题和未来工作,展望动态双足机器人可控周期步态与鲁棒稳定性及其应用的研究思路.     

灵长类仿生机器人悬臂运动仿生控制综述

灵长类仿生机器人是通过智能机械手段模仿灵长类运动的一类机器人,针对其悬臂运动仿生的控制研究是该领域的热点.综述了目前灵长类仿生机器人悬臂运动仿生控制的研究方法,给出了悬臂运动仿生控制的一般方法与基于"动态伺服"理论的悬臂运动仿生控制策略,提出了悬臂运动仿生控制中亟待解决的若干问题,并对今后灵长类仿生机器人悬臂运动仿生控...     

基于组合测量的机器人运动误差特性分析及定位补偿技术

研究了机器人各轴运动角度误差的测量与控制补偿技术.讨论了各因素对运动角度误差影响的显著性,独立分析了电机运动控制误差和关节连杆变形误差模型.设计了双轴正交惯性测量方案,通过预先测量机器人各轴运动范围回转角度误差,得到机器人运动空间几何误差分布,基于多元统计学分析确立了不同因素对运动角度误差的影响系数,基于正交多项式拟合建立了各轴定位误差分布模型,在机器人运行前利用该模型计算误差补偿量,控制机器人进行定位补偿.同时,对所提出的机器人各轴运动误差分布规律和正交多项式拟合方法进行了分析,并使用激光跟踪仪测量验证了机器人末端定位精度的补偿效果.研究结果表明,通过对机器人自身性能的研究和补偿可以提高机器人控制精度.     

欠驱动冗余度空间机器人优化控制

欠驱动控制是空间技术中容错技术的重要方面.本文研究了被动关节中有制动器的欠驱动冗余度空间机器人系统的运动优化控制问题.从系统动力学方程出发,分析了欠驱动冗余度空间机器人的优化能力和控制方法;给出了主、被动关节间的耦合度指标;提出了欠驱动冗余度空间机器人系统的“虚拟模型引导控制”方法,在这种方法中采用与欠驱动机器人机构等价的全驱动机器人作为模型来规划机器人的运动,使欠驱动系统在关节空间中逼近给出的规划轨迹,实现了机器人末端运动的连续轨迹运动优化控制;通过末关节为被动关节的平面三连杆机器人进行了仿真,仿真的结果证明了提出算法的有效性.     

可视语音中虚拟机器人的运动学分析

针对肢体语言在传递非语言信息的过程中控制的复杂性,利用普通关节型机器人的运动学研究方法,对可视语音研究中的虚拟机器人进行了运动学分析,并为解决二者之间的差异引入了权值运算,从而推导出了虚拟机器人以肢体语言表达非语言信息的运动学方程.研究该虚拟机器人的运动学方法共分为三大步:第一步,利用D-H参数法求出各连杆机构的D-H参数表;第二步,根据参数表建立各个运动系统的运动学方程;第三步,利用权值选择适当强度级别的运动方程.实验表明,该分析方法在研究虚拟机器人随情感强弱变化而做出不同肢体反应的可视语音系统时,能够大大简化分析难度,优化控制.该方法不但适用于虚拟机器人,也同样适用于物理机器人的肢体语言控制,具有很强的实用性.     

康复辅助机器人及其物理人机交互方法

面对中国社会快速老龄化现状和庞大的残疾人群,康复辅助机器人研究具有重要学术价值和广阔的应用前景.康复辅助机器人研究涉及神经科学、生物力学、机器人自动控制等领域知识,是机器人最具挑战性和最受关注的研究领域之一.与其他机器人不同,康复辅助机器人的作用对象是人,存在人与机器人的信息交流和能量交换,物理人机交互控制方法是其研究核心和关键技术.本文以神经康复机器人、穿戴式外骨骼、智能假肢等应用为例,介绍当前的研究现状,并重点介绍人体运动意图识别方法和交互控制方法等研究重点和难点.最后展望该领域的未来技术发展方向.     

机器人机构学基础

1.前言机器人机构学在于研究机器人的构成、运动传递方法以及机器人关节运动与手爪抓取物体运动之间的关系。此外,还包括手爪机构和移动机器人的机构研究。下面以比较的方法就大家熟悉的机器人手臂做一简单的介绍。     

六足机器人亮相冰雪 足式仿生机器人未来可期

<正>北京冬奥会加速了冰雪运动的普及,同时也推动机器人在冰雪场景落地应用。六足滑雪机器人、六足冰壶机器人的亮相,向世界展示了中国足式机器人的风采。冰雪之外,足式机器人在安防、巡检等场景实现了测试应用,商业化探索步伐不断推进,价值前景广阔。前不久,上海交通大学研发的六足滑雪机器人亮相沈阳,顺利完成初级道、中级道,以及与人共同滑雪实验。广阔的雪地上,一台红色机器人踩着双板,灵活地穿梭于人群之中,引得游客纷纷驻足观看。     

自由飘浮空间机器人运动规划研究综述

本文介绍了自由飘浮空间机器人的运动学特性;从避奇异点规划、姿态调整规划和协同控制规划三个方面总结了自由飘浮空间机器人的运动规划研究现状,并对现有方法的局限性进行了分析;最后给出了自由飘浮空间机器人运动规划下一步需要研究的问题与解决思路。     

柔性蠕动管道机器人的牵引力及软轴结构稳定性分析

为解决柔性蠕动管道机器人的运动控制问题,提高机器人管内行走效率,对一种具有导向头和刹车轮结构的柔性蠕动管道机器人进行了深入分析和研究.通过对机器人进行管内受力分析,建立起机器人的牵引力模型;为提高机器人在不同管道环境中的运动性能,对软轴结构的运动稳定性进行了分析,提出了机器人蠕动运动失稳的概念,并采用长柱体的稳定性理论进行分析,推导出机器人在直管和L型管道中的临界失稳条件,为柔性蠕动管道机器人步距规划提供了理论依据.搭建管道实验环境进行机器人的牵引力和行走实验,测试值与理论分析基本一致,说明柔性蠕动管道机器人具有优良的牵引能力,行走过程中的运动失稳现象也验证了软轴临界失稳理论的正确性.     

互联网时代背景下吉林红色文化融入冰雪旅游发展策略

互联网的快速发展为吉林红色文化的开发创造了良好的条件,吉林省又是冰雪旅游的重要区域,冰雪旅游已成为吉林旅游业的排头兵,在这种情况下应将吉林红色文化融入冰雪旅游发展中,在两者深入结合的情况,弘扬红色文化,推动冰雪旅游发展。本文根据现有研究资料,结合自身在冰雪旅游发展中的一些经验,针对吉林红色文化融入冰雪旅游发展战略进行分析,提出以抗联英雄和东北抗联烽火道为核心的红色文化融入冰雪旅游的方案,提出吉林省旅游管理部门应与党建管理部门等共同制订红色文化融入冰雪旅游的方案,在此基础上打造多个主题旅游项目,实现红色文化与旅游业发展的深度融合。     

A methodology for design and analysis of cooperative behaviors with mobile robots

New methodologies are needed for modeling of physically cooperating mobile robots to be able to systematically design and analyze such systems. In this context, we present a method called the ‘P-robot Method’ under which we introduce entities called the p-robots at the environmental contact points and treat the linked mobile robots as a multiple degree-of-freedom object, comprising an articulated open kinematic chain, which is manipulated by the p-robots. The method is suitable to address three critical aspects of physical cooperation: a) analysis of environmental contacts, b) utilization of redundancy, and c) exploitation of system dynamics. Dynamics of the open chain are computed independent of the constraints, thus allowing the same set of equations to be used as the constraint conditions change, and simplifying the addition of multiple robots to the chain. The decoupling achieved through constraining the p-robots facilitates the analysis of kinematic as well as force constraints. We introduce the idea of a ‘tipping cone’, similar to a standard friction cone, to test whether forces on the robots cause undesired tipping. We have employed the P-robot Method for the static as well as dynamic analysis for a cooperative behavior involving two robots. The method is generalizable to analyze cooperative behaviors with any number of robots. We demonstrate that redundant actuation achieved by an adding a third robot to cooperation can help in satisfying the contact constraints. The P-robot Method can be useful to analyze other interesting multi-body robotic systems as well.     

Highly Precise Dynamic Simulation Environment for Humanoid Robots

In this paper we present a simulation environment for humanoid robots with a precise and efficient method of handling ground contact, and experiments empirically validating the simulator. Highly accurate dynamic simulation is an essential tool for research and development in humanoid robotics, and a simulator should ideally provide a transparent interface with pathways for control and sensing information identical to those of the actual robot(s) it models. We identified ground contact as the chief source of divergence from reality in work to date and have tackled this problem by developing an algorithm for resolving ground contact for humanoid robots. Our objective was to produce an algorithm that is accurate, efficient and easy to implement. The algorithm is general with respect to the complexity of the foot model; is based on empirically measurable characteristics of the foot–ground interaction, i.e., friction, which we have obtained using experiments described; provides an exact implementation of the Coulomb friction model (avoiding polyhedral approximation of the friction cone); runs in real-time; is also amenable to a straightforward accuracy–speed trade-off; and is relatively easy to implement as a constraint selection method. The simulation environment embodies generality, and we have applied it to two different humanoid robots, Hoap-2 and CB. We present experiments comparing the results of simulation with identical motions performed by real robots, and comparing the full contact resolution algorithm, the modification trading accuracy for computational speed and a penalty-based method.     

服务机器人技术研究现状与发展趋势

服务机器人技术经过近30年的发展,在机械、信息、材料、控制、医学等多学科交叉方面取得了重要的成果,本文结合作者在机器人领域的相关工作,在分析国内外关于服务机器人发展研究现状的基础上,就服务机器人目前涉及的仿生材料与结构、自重构机器人、复杂环境下机器人动力学问题、智能认知与感知、网络化交互及微纳系统等关键技术的研究进展做简要的综述,并概要展望了其发展趋势.希望能够在把握国际服务机器人前沿技术发展动态的同时,为培育我国服务机器人产业提供相关理论、方法及技术.     

Classification and snow line detection for glacial areas using the polarimetric SAR image

Snow cover and glaciers are sensitive indicators of the environment. The vast spatial coverage of remote sensing data, coupled with the tough conditions in areas of interest has made remote sensing a particularly useful tool in the field of glaciology. Compared to optical images, synthetic aperture radar (SAR) data are hardly influenced by clouds. This is important because glacial areas are usually under cloud cover.The Dongkemadi glacier in the Qinghai-Tibetan plateau was selected as the study area for this paper. We use polarimetric SAR (PolSAR) image for classification on and around the glacier. The contrast between ice and wet snow is remarkable, but it is difficult to distinguish the ice from the ground on SAR images due to similar backscatter characteristics in former research. In our study, we found that this distinction can be achieved by target decomposition. Support Vector Machines (SVMs) are performed to classify the glacier areas using the selected features. The glacial areas are classified into six parts: wet snow, ice, river outwash, soil land, rocky land and others. The PolSAR-Target decomposition-SVMs (PTS) method is proven to be efficient, with an overall classification accuracy of 91.1% and a kappa coefficient of 0.875. Moreover, 86.63% of the bare ice and 96.76% of the wet snow are correctly classified. The classification map acquired using the PTS method also helps to determine the snow line, which is an important concept in glaciology.     

Analysis of ERS-1 Synthetic Aperture Radar data from Nordaustlandet,Svalbard

Study of the Earth's terrestrial ice masses (glaciers, ice caps and ice sheets), especially the seasonal variation of different surface conditions such as dry snow, wet snow and bare ice, is of particular importance in relation to possible climatic change. Synoptic monitoring techniques using visible and near-infrared satellite imagery are severely limited by the prevalence of cloud cover in the polar regions, and winter observations are impossible as a result of the absence of solar radiation. Consequently, considerable attention is now being focused on the use of imaging radar in the study of large ice masses. In this paper, we present and interpret a time-series of C-band synthetic aperture radar images acquired using the ERS-1 satellite from the Austfonna ice cap in eastern Svalbard. Winter imagery shows little variability, most of the ice cap having a uniform and high (approximately – 3dB) backscatter attributed to ice lenses or to a large effective grain size. Summer imagery shows considerable topographically-related detail, and backscatter values typically 5 to l0 dB less than in winter, which can be explained on the basis of surface scattering from wet snow. However, the marginal areas of the ice cap show a clearly defined zone of high ( –5dB) backscatter in mid- to late-August. It is proposed that this corresponds to the bare ice zone, the high backscatter values being due to scattering from crevasses and meltwater channels, and that the inner boundary of the zone of enhanced backscatter indicates the position of the transient snow line.     

路面除雪融冰智能控制与远程监控系统

针对传统路面除雪融冰的弊端,设计了一种路面除雪融冰智能控制与远程监控系统.采用ARM嵌入式主机对环境温湿度进行实时监测,并通过3G网络实现与远程监控系统之间数据的接收和发送.远程监控系统实时显示环境温湿度信息,并自动或手动触发嵌入式主机启动加热控制器,实现路面除雪融冰智能化管理.整个系统性能稳定、操作简单,经实际应用表明:该系统能够很好地完成路面除雪融冰工作,在城市高架、高速公路、机场等关键路段具有良好的应用前景.     

Investigation of C- and X-band backscattering signatures of Baltic Sea ice

Backscattering signatures of various Baltic Sea ice types and open water leads were measured with the helicopter-borne C- and X-band Helsinki University of Technology scatterometer (HUTSCAT) during six ice research campaigns in 1992–1997. The measurements were conducted at incidence angles of 23° and 45°. The HUTSCAT data were assigned by video imagery into various surface type categories. The ground data provided further classification of the HUTSCAT data into different snow wetness categories (dry, moist and wet snow). Various basic statistical parameters of backscattering signature data were used to study discrimination of open water leads and various ice types. The effect of various physical parameters (e.g. polarization, frequency, snow condition) on the surface type discrimination was investigated. The results from the data analysis can be used to help the development of sea ice classification algorithms for space-borne SAR data (e.g. Radarsat and Envisat). According to the results from the maximum likelihood classification it is not possible to reliably distinguish various surface types in the SAR images only by their backscatter intensity. In general, the best ice type discrimination accuracy is achieved with C-band VH-polarization σ° at an incidence angle of 45°.     

Using big data techniques for measuring productive friction in mass collaboration online environments

The advent of the social web brought with it challenges and opportunities for research on learning and knowledge construction. Using the online-encyclopedia Wikipedia as an example, we discuss several methods that can be applied to analyze the dynamic nature of knowledge-related processes in mass collaboration environments. These methods can help in the analysis of the interactions between the two levels that are relevant in computer-supported collaborative learning (CSCL) research: The individual level of learners and the collective level of the group or community. In line with constructivist theories of learning, we argue that the development of knowledge on both levels is triggered by productive friction, that is, the prolific resolution of socio-cognitive conflicts. By describing three prototypical methods that have been used in previous Wikipedia research, we review how these techniques can be used to examine the dynamics on both levels and analyze how these dynamics can be predicted by the amount of productive friction. We illustrate how these studies make use of text classifiers, social network analysis, and cluster analysis in order to operationalize the theoretical concepts. We conclude by discussing implications for the analysis of dynamic knowledge processes from a learning sciences perspective.