关键词： 绳索牵引并联机器人   动力学   悬链线   带约束的非线性优化方法  

摘要： 针对6自由度大跨度绳索牵引并联机器人存在绳索悬链线效应的问题,分别建立了绳索的直线模型和绳索的悬链线模型,在此基础上推导了并联机器人的动力学模型,并对二者进行分析和比较.在绳索牵引并联机器人逆动力学的求解过程中,采用带约束的非线性优化方法作为求解工具来计算满足绳索单向力约束的绳索张力.仿真结果表明,考虑绳索的悬链线模型时,并联机器人逆动力学解得到的绳索末端张力与绳索的线性模型相比有很大的变化,故绳索悬链线效应不可忽略,动力学分析中必须加入绳索的悬链线模型.

关键词： 自主机动飞网机器人   动力学建模   网型保持   间隙函数  

摘要： 针对自主机动飞网机器人多系绳编织结构的动力学建模难题,首先提出利用无向图描述飞网机器人的结构,然后依据系绳杨氏模量极大的特点,设计间隙函数和约束反力,基于Hamilton原理建立飞网机器人数学模型,并设计一种基于Lemke算法和龙格库塔积分的解算方法;针对其网型保持问题,设计一种"双层优化伪动态逆内环+变结构控制外环"的控制方法。仿真结果表明,设计的控制器能够有效控制飞网机器人沿指令轨迹运动,并很好保持其网型,避免飞网机器人任务过程的变形和轨道径向移动。

关键词： 焊接机器人   动力学   仿真   Adams  

摘要： 本文先用拉格朗日法对一款六自由度焊接机器人进行动力学分析,得出该机器人各个关节的峰值力矩理论值。并运用Solid Works建立了该款机器人的三维装配模型,将其导入到Adams后进行动力学仿真分析,在Adams中仿真出焊接机器人在不同工况下各个运动情况,得出各个关节处的力矩图。并将仿真出的峰值力矩与所求的理论峰值力矩对比,验证仿真数据的正确性。将仿真结果与该机器人各个驱动关节处电机经减速器减速后的输出力矩对比,验证电机选型的合理性。

关键词： 机器人学   机构学   旋量理论   几何基础   李代数   李群   终身成就奖   研究成果  

摘要： 戴建生教授在机构学与机器人学领域取得了丰硕的研究成果，他是国际上享有盛誉的可重构机构与可重构机器人学领域的权威专家，并于今年（2015年）获得了ASME机构学与机器人学终身成就奖。藉二十余年的学术积淀，戴教授在耳顺之年（2014年）出版了两部新著。

关键词： 并联机器人   柔顺关节   动力学  

摘要： 首次采用初始弯曲梁的伪刚体模型建立了柔顺关节的双1R伪刚体模型,应用拉格朗日方程和虚拟切割法推导了柔顺关节并联机器人系统动力学方程。对方程进行了数值求解,结果显示在理想结果的基础上存在低幅高频振动,而简化模型结果却比较理想,这表明理论模型比简化模型更能反映柔顺关节并联机器人这种刚柔耦合系统的特征;同时理论轨迹与ADAMS-ANSYS联合仿真轨迹、实验轨迹进行对比,最大相对误差分别为2.41%和4.69%,验证了理论模型的正确性。

关键词： ROBOTICS   DIGITAL image processing   AGGREGATION (Robotics)  

摘要： An introduction is presented in which the editor discusses various reports within the issue on topics including molecular robotics, an image processing technology that can recognize DNA nanostructures, and swarm networks in Brownian environments.

关键词： exercise therapy   exercise tolerance   robotics   stroke   subacute care   treadmill training  

摘要： Background and Purpose: Cardiovascular fitness is greatly reduced after stroke. Although individuals with mild to moderate impairments benefit from conventional cardiovascular exercise interventions, there is a lack of effective approaches for persons with severely impaired physical function. This randomized controlled pilot trial investigated efficacy and feasibility of feedback-controlled robotics-assisted treadmill exercise (FC-RATE) for cardiovascular rehabilitation in persons with severe impairments early after stroke. Methods: Twenty individuals (age 61 +/- 11 years;52 +/- 31 days poststroke) with severe motor limitations (Functional Ambulation Classification 0-2) were recruited for FC-RATE or conventional robotics-assisted treadmill exercise (RATE) (4 weeks, 3 x 30-minute sessions/wk). Outcome measures focused on peak cardiopulmonary performance parameters, training intensity, and feasibility, with examiners blinded to allocation. Results: All 14 allocated participants (70% of recruited) completed the intervention (7/group, withdrawals unrelated to intervention), without serious adverse events occurring. Cardiovascular fitness increased significantly in both groups, with peak oxygen uptake increasing from 14.6 to 17.7 mL . kg (1) . min (1) (+17.8%) after 4 weeks (45.8%-55.7% of predicted maximal aerobic capacity;time effect P = 0.01;no group-time interaction). Training intensity (% heart rate reserve) was significantly higher for FC-RATE (40% +/- 3%) than for conventional RATE (14% +/- 2%) (P = 0.001). Discussion and Conclusions: Substantive overall increases in the main cardiopulmonary performance parameters were observed, but there were no significant between-group differences when comparing FC-RATE and conventional RATE. Feedback-controlled robotics-assisted treadmill exercise significantly increased exercise intensity, but recommended intensity levels for cardiovascular training were not consistently achieved. Future research should focus on appropriate a

关键词： Robotics  

摘要： The Three Laws of Robotics made their debut in a story by Isaac Asimov, entitled 'Runaround', first published in the March 1942 issue of Astounding Science Fiction magazine, edited by John W Campbell. Asimov was disenchanted with stock narratives about monstrous robots being destroyed when they turn on their makers.

关键词： MIMO system   Neural networks   Nonlinear control   Adaptive control  

摘要： In this work, original results, concerning the application of a discrete-time adaptive PID neural controller in mobile robots for trajectory tracking control, are reported. In this control strategy, the exact dynamical model of the robot does not need to be known, but a neural network is used to identify the dynamic model. To implement this strategy, two controllers are implemented separately: a kinematic controller and an adaptive neural PID controller. The uncertainty and variations in the robot dynamics are compensated by an adaptive neural PID controller. It is efficient and robust in order to achieve a good tracking performance. The stability of the proposed technique, based on the discrete-time Lyapunov's theory, is proven. Finally, experiments on the mobile robot have been developed to show the performance of the proposed technique, including the comparison with a classical PID.