髋关节康复机器人的运动学分析与仿真

康复机器人能够按照指定轨迹稳定运行是康复过程安全性和有效性的重要保证,因此机器人末端位姿与人体患肢位姿应保持高度重合,同时康复机器人应具备适应不同人体患肢长度的能力。为此提出了机器人与人体患肢运动学模型关联的计算方法。对所设计的平卧式五自由度髋关节康复串联机器人建立了运动学数学模型。将人体下肢简化为四自由度两关节连杆,建立人体的运动学模型,根据人体下肢参数计算患肢末端位姿,并将其作为输入条件代入机器人运动学模型求解,得到机器人的关节变量对关节转动进行控制。以屈髋和内旋动作为例,应用SimMechanics进行仿真,得到的各关节角度与目标设定值一致,且机器人关节角度范围满足人体髋关节活动度的康复要求。分析了下肢长度测量误差对髋关节康复角度及位置的影响。结果表明当大腿长度占比测量偏差为0.5%,位置偏差小于6 mm时,关节角度偏差小于1°。     

安防与智能家居机器人

随着5G时代的到来,智能家居、家居机器人等逐渐成为现代家庭重要的电子设备。传统的安防系统,往往以远程监控为主,对于室内出现诸如有毒气体泄漏、温湿度不适等情况无法做出判断和警示。安防和智能家居机器人是利用履带式行驶机器人在移动中完成对室内温湿度、有毒气体和人体红外信号的监测功能。该系统包括一台履带车、温湿度建模模块、气体检测模块和人体红外信号检测模块。其中,电机转动为履带机器人提供动力,温湿度检测模块可以实现高温火灾和室内潮湿度监测,气体检测模块可以对室内诸如一氧化碳等有害气体进行监测报警,人体检测模块则可以实现白天或夜晚对非法入室人员的监测。安防和智能家居机器人为家庭提供安全保障,是现代家庭重要的电子产品。     

医用微型机器人的姿态可控性研究

建立了新型医用微型机器人的系统动力学模型.利用有向图理论分析了医用微型机器 人的姿态可控性,得到微型机器人的姿态可控的结论.同时,对机器人和环境参数的摄动对机器 人的姿态的影响进行了研究,实验研究结果证明了上述理论.姿态可控性与微型机器人进入人 体时人体的舒适性和安全性紧密相关.通过控制微型机器人的运行姿态,可以使人体得到良好 的舒适程度.     

人体下肢外骨骼机器人的发展及关键技术分析

下肢外骨骼机器人具有增强人体机能和辅助下肢康复训练的功能,在军事和医疗领域具有很好的发展前景,逐渐成为机器人领域的研究热点。本文分别介绍了增强人体机能的下肢外骨骼机器人和医疗下肢外骨骼机器人的国内外最新研究现状,概括并分析了与之相关的关键技术,探讨了下肢外骨骼机器人的今后发展方向。     

基于体感的仿人机器人步态学习与控制

针对现有理想化步态动力学模型规划方法复杂、人为指定参数过多、计算量大的问题,提出一种基于体感数据学习人体步态的仿人机器人步态生成方法。首先,用体感设备收集人体骨骼信息,基于最小二乘拟合方法建立人体关节局部坐标系;其次,搭建人体与机器人映射的运动学模型,根据两者间主要关节映射关系,生成机器人关节转角轨迹,实现机器人对人类行走姿态的学习;然后,基于零力矩点(ZMP)稳定性原则,对机器人脚踝关节转角采用梯度下降算法进行优化控制;最后,在步态稳定性分析上,提出使用安全系数来评价机器人行走稳定程度的方法。实验结果表明,步行过程中安全系数保持在0~0.85,期望为0.4825,ZMP接近于稳定区域中心,机器人实现了仿人姿态的稳定行走,证明了该方法的有效性。     

仿人机器人步态平衡泛化模型的建立与仿真

通过人体示教计算零力矩点(zero moment point, ZMP),并通过补偿关节角度对其矫正的方法可以解决机器人步行不稳定的问题,但仍存在算法复杂度过高等问题。本文提出一种人体示教与机器学习相结合的方法,基于支持向量回归算法建立机器人的步态平衡泛化模型,通过该模型可以实现对模型输入人体示教的关节角度和ZMP信息后直接得到经稳定性补偿的关节角度,并以此驱动机器人完成步行动作。引入鲸鱼优化算法(whale optimization algorithm, WOA)优化模型的参数以使模型得到最优的泛化效果,完善步态平衡模型的性能。WEBOTS仿真平台下,使用模型输出的补偿后的关节角度驱动NAO机器人,其动作自然、稳定且算法复杂度较低,验证了本文方法的可行性。     

基于蚯蚓运动原理的肠道检查微小机器人内窥镜系统

本文比较了传统的内窥镜系统和机器人内窥镜系统的差别，又对机器人内窥镜系统 的工作环境——人体肠道内部的状况作了详细讨论，由此提出了机器人内窥镜系统的设计要 求．介绍了一种基于蚯蚓运动原理的微小机器人内窥镜系统，对微小机器人机体的构造及其 驱动原理作了分析，选择了一种适合的驱动方式，确定了单一构件磁感应强度的标定方法． 实验证明，微小机器人的运行是平稳的．下一步的研究集中于对机器人在肠道内表面行走机 理的研究和机器人的发热问题上．     

基于仿生原理的节能减振类人机器人膝关节的设计

通过对人体膝关节结构的研究,设计了一种基于仿生原理的类人机器人膝关节.仿效人体膝关节处的ACL、PCL(前、后十字韧带)及半月板结构,为机器人膝关节设计了节能和减振结构,降低了机器人在迈步期膝关节的峰值驱动力矩,减小了机器人脚着地阶段膝关节受到的冲击,并增加了膝关节的刚度,提高了机器人行走的稳定性.采用NDI公司的Optotrak Certus三维动态测量系统测得人体各关节运动角度与时间的离散点序列,用最小二乘法拟合成机器人行走步态曲线.在ADAMS软件环境下建立虚拟样机模型,对机器人进行了平地行走仿真分析,仿真结果验证了设计的有效性与可行性.     

基于深度学习的配电高压操作机器人运动控制技术研究

随着人工智能的快速发展,体感控制成为机器人人机交互的热点方向,如何快速且准确地识别人体姿态是完成体感控制的一大难点。此次研究将通过改进后的YOLOv4模型检测人体框架,改进后的堆叠沙漏网络模型识别关节点,以提高人体姿态识别的速度和准确率;并针对机器人上半身手臂运动和下半身步态控制的特点,开发关节点映射算法来对机器人进行体感控制,解决配电高压操作机器人进行人机交互时容易摔倒的问题。结果表明,改进后YOLOv4网络检测人体目标的最好结果为84.37%,改进堆叠沙漏网络模型的收敛损失函数为0.096,PCK值为88.3%;研究模型的识别速度均值较CPN模型提高了21.5 s,表明研究模型在提高人体姿态识别准确率的同时,提高了体感控制的效率,在体感控制领域有一定的研究价值。     

装有复合燃料电池系统的双足步行机器人"Speecys-FC"

日本从事机器人开发的Speecys公司在6月28日宣布他们发明了装有复合燃料电池的机器人,这个机器人最大的特点是采用了备受瞩目的作为下一代清洁能源燃料电池系统“Speecys Composite Fuel Cell System”。“Speecys-FC”机器人高约50cm,重4．2kg。头部装有16L的氢气瓶,双肩和背部装有燃料电池,工作时间大约为1小时。“Speecys-FC”机器人主要用于研究和展览,7月份开始销售,价格约为23,000美元（含税）。     

带主动腰关节的四足机器人平稳运动控制

针对四足机器人在对角小跑运动时出现的后腿“拖地”、机体振荡的现象,提出了一种基于偏航方向上主动腰关节摆动的解决方法。通过D-H法对机器人各关节进行运动学建模,获得其运动学方程,并采用Kuramoto振荡器模型作为扩展的CPG耦合网络振子,实现对腰、腿关节的统一控制。仿真实验表明,经过腰关节控制优化后的机器人在对角小跑时,相对于刚体躯干的机器人,姿态角变化幅度显著减小,抬腿高度明显增加,有效地提高了机器人的运动稳定性,证明了方法的可行性。     

助行机器人研究发展和展望

本文简单回顾助行机器人的发展历史及目前的助行机器人国内外的研究现状;综述助行机器人的机构设计及辅助导航策略,提出助行机器人面临的主要技术难题：移动灵活性、能源高效性、便携性以及多种路面适用性;展望助行机器人未来的发展趋势和研究重点——智能化。     

A humanoid robot that pretends to listen to route guidance from a human

This paper reports the findings for a humanoid robot that expresses its listening attitude and understanding to humans by effectively using its body properties in a route guidance situation. A human teaches a route to the robot, and the developed robot behaves similar to a human listener by utilizing both temporal and spatial cooperative behaviors to demonstrate that it is indeed listening to its human counterpart. The robot's software consists of many communicative units and rules for selecting appropriate communicative units. A communicative unit realizes a particular cooperative behavior such as eye-contact and nodding, found through previous research in HRI. The rules for selecting communicative units were retrieved through our preliminary experiments with a WOZ method. An experiment was conducted to verify the effectiveness of the robot, with the results revealing that a robot displaying cooperative behavior received the highest subjective evaluation, which is rather similar to a human listener. A detailed analysis showed that this evaluation was mainly due to body movements as well as utterances. On the other hand, subjects' utterance to the robot was encouraged by the robot's utterances but not by its body movements.     

Dynamic modeling and step-climbing analysis of a two-wheeled stair-climbing inverted pendulum robot

ABSTRACT

In this study, the control of a two-wheeled stair-climbing inverted pendulum robot and its climbing motion are analyzed and discussed. The robot adopts a state-feedback controller with a feed-forward constant to stabilize the body and achieve step-climbing motion. The control parameter is considered based on the dynamic model motion on a flat surface and the static model of motion on the step. For climbing stairs with a narrow step tread, a constant torque is applied to reduce the space required for recovering the body stability after climbing. The stability of the robot is numerically analyzed by analyzing the orbital stability of its limit cycle. The stability analysis shows that the control method can achieve a stable stair-climbing motion. The effectiveness of the control method is demonstrated through an experiment. The result indicates that the robot can climb the stairs, and the required time for climbing a single step is approximately 1.8?s.     

下肢康复机器人系统设计与协调控制算法

脑卒中、脊髓损伤、下肢退行性关节疾病等神经系统疾病会导致肢体功能障碍,需要进行有针对性和重复性的训练.本文设计了一款可以切换坐、立、躺三种模式的轮椅式下肢康复机器人,在机器人站立姿态的主动步行训练模式下,解算人体前进速度映射轮椅式底盘电机速度,实现了下肢功能障碍患者步态训练与机器人轮椅式车体的协调控制.实验结果表明,下肢外骨骼行走的速度曲线和轮椅式车体的速度曲线基本一致,实现人与机器人的协调控制.     

基于力反馈的脊柱外科机器人系统的设计与实现

本文针对脊柱椎管狭窄症减压手术中椎管壁磨削不安全这一问题，介绍一种基于力反馈控制策略的脊柱外科机器人系统，包括监控磨削过程的检测子系统、完成磨削手术操作的运动驱动子系统和再现磨削信息状况的控制显示子系统。利用脊柱磨削手术过程中磨削力的变化特点，提出基于力反馈的脊柱外科机器人控制策略，辅助医生实现安全的脊柱手术操作。最后通过仿真实验和模拟骨实验，验证了此基于力反馈控制策略的脊柱外科机器人系统的可行性。     

The development and control of a flexible-spine for a human-form robot

In this paper, the development of a robot which has a flexible spine is presented. By embedding a multi-d.o.f. soft structure into a robot body as a spine, the robot can increase its ability to absorb shock and to work in various environment such as narrow places. As a result of these abilities, the robot can expand its opportunity to work in the human environment. Moreover, its motion could be more natural. The developed full-body human-form robot has a five-jointed flexible spine. Each joint (vertebra) has 3 d.o.f. Between each vertebrae is a 'disk' made of silicone rubber. The spine is controlled by eight tendons, whose tensions can be controlled using tension sensors and locally distributed microcontrollers. This paper describes the development of the flexible spine and the control of the posture of the spine and body.     

用于丝驱动连续体机器人的实用运动学研究

针对单段及多段连续体机器人运动学问题,提出分段常曲率与粒子群算法相结合的完整正逆运动学分析方法.以双段丝驱动连续体机器人为研究对象,首先设计含平移段的机器人样机;然后利用分段常曲率方法建立驱动空间与关节空间的相互映射,根据齐次变换得到关节空间至工作空间的正映射关系;最后利用线性递减权重粒子群算法实现工作空间至关节空间的逆映射.对双段连续体机器人的运动学进行仿真及逆运动学求解耗时测试,并在研制样机上进行了实验验证.仿真结果说明了所提运动学研究方法的合理性及逆运动学求解的快速性,实验结果显示位置平均误差小于双段连续体机器人本体长度的6.22％,验证了所提运动学的有效性.     

Mobile robot interception using human navigational principles: Comparison of active versus passive tracking algorithms

We examined human navigational principles for intercepting a projected object and tested their application in the design of navigational algorithms for mobile robots. These perceptual principles utilize a viewer-based geometry that allows the robot to approach the target without need of time-consuming calculations to determine the world coordinates of either itself or the target. Human research supports the use of an Optical Acceleration Cancellation (OAC) strategy to achieve interception. Here, the fielder selects a running path that nulls out the acceleration of the retinal image of an approaching ball, and maintains an image that rises at a constant rate throughout the task. We compare two robotic control algorithms for implementing the OAC strategy in cases in which the target remains in the sagittal plane headed directly toward the robot (which only moves forward or backward). In the “passive” algorithm, the robot keeps the orientation of the camera constant, and the image of the ball rises at a constant rate. In the “active” algorithm, the robot maintains a camera fixation that is centered on the image of the ball and keeps the tangent of the camera angle rising at a constant rate. Performance was superior with the active algorithm in both computer simulations and trials with actual mobile robots. The performance advantage is principally due to the higher gain and effectively wider viewing angle when the camera remains centered on the ball image. The findings confirm the viability and robustness of human perceptual principles in the design of mobile robot algorithms for tasks like interception. Thomas Sugar works in the areas of mobile robot navigation and wearable robotics assisting gait of stroke survivors. In mobile robot navigation, he is interested in combining human perceptual principles with mobile robotics. He majored in business and mechanical engineering for his Bachelors degrees and mechanical engineering for his Doctoral degree all from the University of Pennsylvania. In industry, he worked as a project engineer for W. L. Gore and Associates. He has been a faculty member in the Department of Mechanical and Aerospace Engineering and the Department of Engineering at Arizona State University. His research is currently funded by three grants from the National Sciences Foundation and the National Institutes of Health, and focuses on perception and action, and wearable robots using tunable springs. Michael McBeath works in the area combining Psychology and Engineering. He majored in both fields for his Bachelors degree from Brown University and again for his Doctoral degree from Stanford University. Parallel to his academic career, he worked as a research scientist at NASA—Ames Research Center, and at the Interval Corporation, a technology think tank funded by Microsoft co-founder, Paul Allen. He has been a faculty member in the Department of Psychology at Kent State University and at Arizona State University, where he is Program Director for the Cognition and Behavior area, and is on the Executive Committee for the interdisciplinary Arts, Media, and Engineering program. His research is currently funded by three grants from the National Sciences Foundation, and focuses on perception and action, particularly in sports. He is best known for his research on navigational strategies used by baseball players, animals, and robots.