关键词： Robotics-assisted tilt table   Treadmill   Cycle ergometer   Submaximal exercise   Anaerobic threshold   Respiratory compensation point   Cardiopulmonary exercise testing  

摘要： Background: The robotics-assisted tilt table (RATT), including actuators for tilting and cyclical leg movement, is used for rehabilitation of severely disabled neurological patients. Following further engineering development of the system, i.e. the addition of force sensors and visual bio-feedback, patients can actively participate in exercise testing and training on the device. Peak cardiopulmonary performance parameters were previously investigated, but it also important to compare submaximal parameters with standard devices. The aim of this study was to evaluate the feasibility of the RATT for estimation of submaximal exercise thresholds by comparison with a cycle ergometer and a treadmill. Methods: 17 healthy subjects randomly performed six maximal individualized incremental exercise tests, with two tests on each of the three exercise modalities. The ventilatory anaerobic threshold (VAT) and respiratory compensation point (RCP) were determined from breath-by-breath data. Results: VAT and RCP on the RATT were lower than the cycle ergometer and the treadmill: oxygen uptake (V'O-2) at VAT was [mean (SD)] 1.2 (0.3), 1.5 (0.4) and 1.6 (0.5) L/min, respectively (p < 0.001);V'O-2 at RCP was 1.7 (0.4), 2.3 (0.8) and 2.6 (0.9) L/min, respectively (p = 0.001). High correlations for VAT and RCP were found between the RATT vs the cycle ergometer and RATT vs the treadmill (R on the range 0.69-0.80). VAT and RCP demonstrated excellent test-retest reliability for all three devices (ICC from 0.81 to 0.98). Mean differences between the test and retest values on each device were close to zero. The ventilatory equivalent for O-2 at VAT for the RATT and cycle ergometer were similar and both were higher than the treadmill. The ventilatory equivalent for CO2 at RCP was similar for all devices. Ventilatory equivalent parameters demonstrated fair-to-excellent reliability and repeatability. Conclusions: It is feasible to use the RATT for estimation of submaximal exercise thresholds: VAT

关键词： 3D ToF Camera   PMD Camera   Pioneer Mobile Robots   Path-planning  

摘要： The aim of this paper is to deploy a time-of-flight (ToF) based photonic mixer device (PMD) camera on an Autonomous Ground Vehicle (AGV) whose overall target is to traverse from one point to another in hazardous and hostile environments employing obstacle avoidance without human intervention. The hypothesized approach of applying a ToF Camera for an AGV is a suitable approach to autonomous robotics because, as the ToF camera can provide three-dimensional (3D) information at a low computational cost, it is utilized to extract information about obstacles after their calibration and ground testing, and is mounted and integrated with the Pioneer mobile robot. The workspace is a two-dimensional (2D) world map which has been divided into a grid/cells, where the collision-free path defined by the graph search algorithm is a sequence of cells the AGV can traverse to reach the target. PMD depth data is used to populate traversable areas and obstacles by representing a grid/cells of suitable size. These camera data are converted into Cartesian coordinates for entry into a workspace grid map. A more optimal camera mounting angle is needed and adopted by analysing the camera's performance discrepancy, such as pixel detection, the detection rate and the maximum perceived distances, and infrared (IR) scattering with respect to the ground surface. This mounting angle is recommended to be half the vertical field-of-view (FoV) of the PMD camera. A series of still and moving tests are conducted on the AGV to verify correct sensor operations, which show that the postulated application of the ToF camera in the AGV is not straightforward. Later, to stabilize the moving PMD camera and to detect obstacles, a tracking feature detection algorithm and the scene flow technique are implemented to perform a real-time experiment.

关键词： 智能机器人   蔡自兴   智能科学   信息科学   颁奖词   学术带头人   成就奖   智能移动机器人   吴文俊   工业机器人  

摘要： 蔡自兴,中南大学信息科学与工程学院教授,国际导航与运动控制科学院院士、纽约科学院院士,2014年吴文俊人工智能科技奖＂成就奖＂获得者。中国人工智能、智能控制、智能机器人学的学术带头人之一,被誉为＂中国智能科学的开拓者＂＂中国智能控制的奠基者＂＂智能机器人学科的创始人＂和＂中国人工智能教育第一人＂。2014年,蔡自兴获得中国人工智能领域的最高奖项——吴文俊人工智能科技奖＂成就奖＂。颁奖词写道,＂他是一位敢为人先的开拓者,首先在我国人工智能、智能控制、机器人学的3个学科群构建理论体系和基础课程,

关键词： 缆索检测   爬缆机器人   避障   动力学分析   实验样机  

摘要： 在对现有爬缆机器人分析研究的基础上,提出了一种新型四驱式爬缆机器人结构;该爬缆机器人设计有两组对边驱动装置,交替作业可使机器人避开缆索上一些小型元件。通过控制夹紧机构,机器人可利用重力实现匀速安全回收,节省了能源。通过对该爬缆机器人的动力学分析,得到了夹紧力条件和驱动力条件。研制出了样机并对其进行了多次实验,实验结果表明,该机构运行平稳可靠,越障性能较好,能够达到实验的预定目标。

关键词： 机器人大赛   学校基本情况   实验学校   青少年教育   合肥学院   产学研基地   培训中心   机器人竞赛   人形机器人   照片上传  

摘要： 学校基本情况 合肥市贝思特乐高科技中心成立于2014年3月,是一所以乐高教具为平台,从事儿童科技启蒙教育的培训中心,也是合肥学院产学研基地、全国青少年教育机器人等级考试考点、国际机器人奥林匹克培训（IROC）实验学校。一年来培训中心多次参加全国、省、市各级机器人大赛,还代表中国参加国际机器人大赛,均取得优异的成绩。

关键词： 并联机器人控制   动力学补偿   Lyapunov方法   鲁棒跟踪控制  

摘要： 针对6-DOF并联机器人系统存在动力学建模误差和外界不确定性因素干扰的问题,提出了一种基于动力学补偿的并联机器人鲁棒轨迹跟踪控制策略。在充分研究了机器人系统动力学模型特点的基础上,基于Lyapunov方法获得了并联机器人的鲁棒控制率,提出了一种鲁棒轨迹跟踪控制方法,采用逆动力学对内回路进行补偿,外回路采用PD控制,然后对并联机器人进行了鲁棒控制器的设计,最后通过MATLAB进行了系统的轨迹跟踪控制仿真分析。仿真结果表明:当系统存在外界周期干扰的状况时,系统轨迹跟踪误差仍然一致终值有界,在一定程度上提高了系统的鲁棒稳定性。

关键词： 独轮车机器人   实验平台   多体动力学   多信息融合  

摘要： 基于多体动力学理论、多信息融合技术,介绍了独轮车机器人实验平台的建设内容,给出了平台在教学与科研中的具体实施方案,以及该平台在教学与科研两方面的桥梁作用。

关键词： Delta机器人   有限元理论   弹性动力学模型   模态分析  

摘要： 目的建立Delta机器人弹性动力学模型,研究其动态特性。方法基于有限元理论和Lagrange方程,充分考虑主动臂与从动臂的空间动力学特性与运动协调关系,建立Delta机器人系统弹性动力学模型;根据系统结构参数,制造装配出Delta机器人物理样机,对所建立的弹性动力学模型进行验证分析;利用Ansys Workbench对Delta机器人进行模态分析。结果动平台中心点位移的数值解与试验得到的结果吻合度较好,结合Matlab,对比系统的前6阶固有频率,最大频率误差为3.912%;元件刚性假设前后系统的最大频率误差为1.693%;确定了机器人从动臂为系统的薄弱环节。结论验证了Delta机器人系统弹性动力学模型的正确性及建模过程中静、动平台与转动关节刚性假设的合理性,且改善从动臂的结构参数能提高机器人的整体动态性能,为Delta机器人的结构优化和减振控制提供了理论依据。

关键词： 并联机器人   运动学   逆解   工作空间  

摘要： 并联机器人由多个封闭的机构环组成。这些机构环通常是由连接基座和运动平台的两或多个机构链构成,其中一个关节被驱动,其它关节也跟着一起运动。本文介绍一种3自由度的并联机器人--DELTA机器人。DELTA机器人具有在短时间内搬运大量的轻巧物体的能力,这满足了工业的需求。本文根据DELTA机器人的机构结构,运用空间向量知识,建立机器人各连杆之间位置的向量关系,进行DELTA机器人的运动学逆解计算,以及工作空间的计算。

关键词： 巡线机器人   D-H法   Lagrange方法   动力学仿真  

摘要： 分析了跨越式高压输电线路巡线作业机器人的结构特征,采用D-H法构建巡线机器人空间坐标,用Lagrange方法建立了机器人机械臂的动力学模型。基于此动力学模型,对一种典型工况进行了机械臂各关节动力学逆问题仿真,通过给定已知运动轨迹对应的各关节位移、速度曲线,确定所需的关节力矩或关节力,为机器人的实时控制提供理论依据。