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黄强

机电学院

职称:教授

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发明人:ZHANG, Liancun;HUANG, Qiang

申请日期:2017.01.16

摘要:A self-driven and adaptive-gait wearable knee-joint walking assistance device, comprising: a left-foot power output component (1); a right-foot power ...

作者:Li, Xin;Wang, Huaping;Dong, Xinyi;Shi, Qing;Sun, Tao;Shimoda, Shingo;Huang, Qiang;Fukuda, Toshio (1Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing; 100081, China;2The Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology), Ministry of Education, Beijing; 100081, China;3School of Medical Technology, Beijing Institute of Technology, Beijing; 100081, China;4Intelligent Behavior Control Collaboration Unit, RIKEN Center of Brain Science, Nagoya; 463-0003, Japan)

出处:Microsystems and Nanoengineering 2022

关键词:FABRICATION;CONSTRUCTS

摘要:Engineered extracellular matrices (ECMs) that replicate complex in-vivo features have shown great potential in tissue engineering. Biocompatible hydro ...

作者:Huang, Qiang1;Dong, Chencheng2;Yu, Zhangguo3;Chen, Xuechao4;Li, Qingqing5;Chen, Huanzhong6;Liu, Huaxin7; (1School of Mechatronic Engineering, Beijing Institute of Technology, Beijing 100081 China, with the Beijing Advanced Innovation Center for Intelligent Robotics and System, Beijing Institute of Technology, Beijing 100081 China, with the Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081 China, with the International Joint Research Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081 China, and also with the State Key Laboratory of Intelligent Control and Decision of Complex System, Beijing 100081 China (e-mail: qhuang@bit.edu.cn).;2School of Mechatronic Engineering, Beijing Institute of Technology, Beijing 100081 China, with the Beijing Advanced Innovation Center for Intelligent Robotics and System, Beijing Institute of Technology, Beijing 100081 China, and also with the Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081 China (e-mail: 3120195094@bit.edu.cn).;3School of Mechatronic Engineering, Beijing Institute of Technology, Beijing 100081 China, with the Beijing Advanced Innovation Center for Intelligent Robotics and System, Beijing Institute of Technology, Beijing 100081 China, with the Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081 China, with the International Joint Research Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081 China, and also with the State Key Laboratory of Intelligent Control and Decision of Complex System, Beijing 100081 China (e-mail: yuzg@bit.edu.cn).;4School of Mechatronic Engineering, Beijing Institute of Technology, Beijing 100081 China, with the Beijing Advanced Innovation Center for Intelligent Robotics and System, Beijing Institute of Technology, Beijing 100081 China, with the Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081 China, with the International Joint Research Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081 China, and also with the State Key Laboratory of Intelligent Control and Decision of Complex System, Beijing 100081 China (e-mail: chenxuechao@bit.edu.cn).;5School of Mechatronic Engineering, Beijing Institute of Technology, Beijing 100081 China, with the Beijing Advanced Innovation Center for Intelligent Robotics and System, Beijing Institute of Technology, Beijing 100081 China, and also with the Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081 China (e-mail: hexb66@bit.edu.cn).;6School of Mechatronic Engineering, Beijing Institute of Technology, Beijing 100081 China, with the Beijing Advanced Innovation Center for Intelligent Robotics and System, Beijing Institute of Technology, Beijing 100081 China, and also with the Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081 China (e-mail: 3120195092@bit.edu.cn).;7School of Mechatronic Engineering, Beijing Institute of Technology, Beijing 100081 China, with the Beijing Advanced Innovation Center for Intelligent Robotics and System, Beijing Institute of Technology, Beijing 100081 China, and also with the Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing 100081 China (e-mail: 0077@bit.edu.cn).)

出处:IEEE/ASME Transactions on Mechatronics 2022

关键词:CAPTURABILITY-BASED ANALYSIS;IMPEDANCE CONTROL;LEGGED LOCOMOTION;WALKING;UNEVEN;JOINT;MANIPULATION;MODEL

摘要:Compliance control is important for the realization of disturbance absorption in biped robots. However, under a sustained disturbance, compliance cont ...

作者:韩连强1;,陈学超1,2;,余张国1,2;,高志发1;,黄岩1,2;,黄强1,2; (1北京理工大学机电学院;2仿生机器人与系统教育部重点实验室)

出处:自动化学报 2022

关键词:欠驱动双足机器人;离散地形;平衡控制;虚拟约束;模型预测控制

摘要:欠驱动双足机器人在行走中为保持自身的平衡,双脚需要不间断运动.但在仅有特定立足点的离散地形上很难实现调整后的落脚点,从而导致欠驱动双足机器人在复杂环境中的适应能力下降.提出了基于虚拟约束(Virtual constraint,VC)的变步长调节与控制方法,根据欠驱动双足机器人当前状态与参考落脚点设计 ...

发明人:黄强,仪传库,陈学超,余张国,李龙,石青

申请日期:2022.05.07

摘要:本发明提供一种小型可调式大阻尼直线阻尼器,包括底部支架、阻尼器外壳、阻尼器活塞模块、阻尼器端盖模块、顶部支架和弹簧支撑模块,阻尼器活塞模块包括活塞杆、流速阀、单向阀和活塞片,活塞片固定在活塞杆上,且活塞片下方固定流速阀,流速阀上加工有孔径不同的流速孔;活塞片上加工有流量孔和单向孔,流量孔靠近活塞杆、 ...

发明人:余张国,赵凌萱,陈学超,邱雪健,张筱晨,黄强

申请日期:2022.06.09

摘要:本发明提供了一种轮足转换机构及其控制方法,包括横滚支架、外转子电机、横滚电机和直流电机,横滚支架一侧与横滚电机的外壳固连,横滚电机的输出轴与交叉轴支架的一端固连,交叉轴支架的另一端与横滚支架转动连接,交叉轴支架上固连外转子电机,外转子电机的外壳与丝杠/蜗轮蜗杆结构转动连接,丝杠/蜗轮蜗杆结构固连脚掌 ...

发明人:陈学超,张锦涛,余张国,韩连强,高志发,杜嘉恒,黄强

申请日期:2022.06.16

摘要:本发明公开了一种仿人机器人足部缓冲装置,趾跖关节部件的上部可转动连接足背板簧的一端;趾跖关节部件可转动连接跖骨连杆的一端;舟骨块固定连接足背板簧的另一端,舟骨块可转动连接跖骨连杆的另一端;足背板簧平行设置在跖骨连杆的上部;跟骨部件与舟骨块之间通过两组跟骨连杆可转动连接;足弓弹簧阻尼器两端分别与跟骨部 ...

发明人:余张国,赵凌萱,陈学超,邱雪健,张筱晨,黄强

申请日期:2022.06.09

摘要:本发明提供一种可变形轮履转换机构及其控制方法,包括同步带支架,同步带支架两端分别安装推动杆的顶端,推动杆底端通过丝杠结构/蜗轮蜗杆结构与直流电机的输出端连接,直流电机安装在电机固定支架;推动杆靠近同步带支架的一端转动连接滑动轴一端,滑动轴另一端转动连接同步带导向轮;电机固定支架与其上端电机连接支架固 ...

发明人:陈晓鹏,赵培渊,余明明,王启航,徐鹏,黄强

申请日期:2022.10.24

摘要:本发明公开了一种基于仿射变换的电动汽车充电孔像素坐标校正方法,当相机正对充电口时,将射影变换近似成仿射变换,通过目标检测方法得到充电孔中心点的原始坐标,根据仿射变换前后保持共线性和距离比的特性,参照充电孔间的几何尺寸对像素坐标进行校正;依次进行平行线拟合、垂直于平行线方向上校正、引入校正量在平行线方 ...

发明人:高峻峣,马晓帅,余张国,陈学超,孟非,黄强,于晗

申请日期:2022.09.30

摘要:本发明公开了一种基于机器学习前馈模型的自抗扰力矩控制方法,PD控制器输入参考力矩τd和扩张状态观测器的输出z1、z2,输出电流Ic;机器学习前馈模型输入参考力矩τd、电机转速nm< ...