共查询到19条相似文献,搜索用时 140 毫秒
1.
2.
3.
4.
提出了一种用于智能机器人仿生皮肤的电容式滑觉传感器,用以解决智能机器人软抓取过程中滑觉信息的感知问题.阐述了电容式滑觉传感器的结构设计、滑觉感知机理,并借助ANSYS有限元仿真软件进行滑觉感知机理验证.基于CC2530低功耗微处理器与AD7147-1型电容数字转换器构建便携式电容滑觉信息感知系统.根据差分电容式滑觉传感器的输出可实现全方向性滑觉力检测功能.实验结果表明:该电容式滑觉传感器具有结构简单、设计合理、加工制作方便、成本低且高灵敏度等优点. 相似文献
5.
6.
7.
机器人滑觉传感器的研究 总被引:1,自引:1,他引:0
本文介绍作者研制的机器人握力实现可控“软抓取”的简易又实用的滑觉传感器.1 工作原理、结构和安装1.1 工作原理与结构将滑动位移量转换成角位移量,得到光电脉冲信号,送入控制计算机,其结构见图1.当机械手夹持物体(5)移动时,如果物体下滑,就带动摩擦轮转动,并通过齿轮副增 相似文献
8.
基于柔性可穿戴传感器及多模态信息融合,研究人类的抓握特征学习及抓取物体识别,探索人类在抓取行为中所依赖的感知信息的使用.利用10个可拉伸传感器、14个温度传感器及78个压力传感器构建了数据手套并穿戴于人手,分别测量人类在抓取行为中手指关节的弯曲角度、抓取物体的温度及压力分布信息,并在时间及空间序列上建立了跨模态信息表征,同时使用深度卷积神经网络对此多模态信息进行融合,构建人类抓握特征学习模型,实现抓取物体的精准识别.分别针对关节角度特征、温度特征及压力信息特征进行了融合实验及有效性分析,结果表明了基于多传感器的多模态信息融合能够实现18种物品的精准识别. 相似文献
9.
设计了一款面向海珍品捕捞的水下智能识别与自主抓取机器人. 首先通过YOLOv4-tiny网络对海珍品图像
离线训练, 设计单双目自适应切换与多目标选择算法以实现海珍品在线识别与持续定位. 进一步, 采用声呐与深度
传感器融合策略获取水下机器人深度信息, 设计基于模糊比例–积分–微分控制的定深抓取控制器, 以确保目标定位
与抓取过程中深度信息的有效反馈. 所提目标识别算法, 具有实时性强、复杂度低优点; 同时, 定深与抓取控制器,
不依赖于系统复杂模型, 可适应不同海况下的精确抓取. 最后, 通过试验验证了方法的有效性. 相似文献
10.
11.
12.
M.T. Hussein 《Advanced Robotics》2013,27(24):1575-1585
In this review, recent developments in the field of flexible robot arm control using visual servoing are reviewed. In comparison to rigid robots, the end-effector position of flexible links cannot be obtained precisely enough with respect to position control using kinematic information and joint variables. To solve the task here the use of a vision sensor (camera) system, visual servoing is proposed to realize the task of control flexible manipulators with improved quality requirements. The paper is organized as follows: the visual servoing architectures will be reviewed for rigid robots first. The advantages, disadvantages, and comparisons between different approaches of visual servoing are carried out. The using of visual servoing to control flexible robot is addressed next. Open problems such as state variables estimation as well as the combination of different sensor properties as well as some application-oriented points related to flexible robot are discussed in detail. 相似文献
13.
范申民 《自动化与仪器仪表》2021,(2):57-60
为了提高柔性负载抓握机器人的故障检测能力,提出基于神经网络技术的机器人并发故障自动诊断方法。运用高分辨的智能传感器信息识别技术,结合刚度和强度等机械结构特征分析,构建柔性负载抓握机器人的故障信息采集模型,采用变刚度原理,提取柔性负载抓握机器人的振荡信息特征,通过谱特征检测和动态信息融合进行柔性负载抓握机器人的故障信息的多分辨融合和特征聚类处理。通过分析故障样本信息数据参数的估计值,对信息数据进行重组,根据采样信息的差异性对故障类别进行初步判断和识别。采用BP神经网络技术,通过特征分布函数进行故障特征提取,进行机器人并发故障的优化诊断和自适应学习,提高机器人并发故障的有效检测和识别能力。仿真结果表明,采用该方法进行机器人并发故障诊断的自适应性较好,特征辨识能力较强,具有很好的故障监测和模式识别能力。 相似文献
14.
Mohammed Ibrahim Ahmed Al-mashhadani Theyazn H. H. Aldhyani Mosleh Hmoud Al-Adhaileh Alwi M. Bamhdi Mohammed Y. Alzahrani Fawaz Waselallah Alsaade Hasan Alkahtani 《计算机系统科学与工程》2021,38(1):25-37
Touch gesture recognition is an important aspect in human–robot interaction, as it makes such interaction effective and realistic. The novelty of this study is the development of a system that recognizes human–animal affective robot touch (HAART) using a deep learning algorithm. The proposed system was used for touch gesture recognition based on a dataset provided by the Recognition of the Touch Gestures Challenge 2015. The dataset was tested with numerous subjects performing different HAART gestures; each touch was performed on a robotic animal covered by a pressure sensor skin. A convolutional neural network algorithm is proposed to implement the touch recognition system from row inputs of the sensor devices. The leave-one-subject-out cross-validation method was used to validate and evaluate the proposed system. A comparative analysis between the results of the proposed system and the state-of-the-art performance is presented. Findings show that the proposed system could recognize the gestures in almost real time (after acquiring the minimum number of frames). According to the results of the leave-one-subject-out cross-validation method, the proposed algorithm could achieve a classification accuracy of 83.2%. It was also superior compared with existing systems in terms of classification ratio, touch recognition time, and data preprocessing on the same dataset. Therefore, the proposed system can be used in a wide range of real applications, such as image recognition, natural language recognition, and video clip classification. 相似文献
15.
16.
多传感器信息融合的服务机器人导航方法 总被引:1,自引:0,他引:1
在机器人中,计算机视觉与传感器开始交融.本文设计了以人脸识别为视觉导引的主体,传感器为辅的服务机器人系统,提出了一种基于视觉的图像处理算法,采用将形态学处理与自适应阈值分割相结合直接除掉阴影,使用多传感器与视觉融合的方法来解决视觉误判的问题.在小车避障中运用单目测距的原理,跳过了传统相机的标定问题,并将该算法与迷宫机器人路径规划中的左手法则相结合运用在设计的服务机器人中. 相似文献
17.
Menno de Graaf Ronald Aarts Ben Jonker Johan Meijer 《Control Engineering Practice》2010,18(8):944-953
In this paper a real-time seam tracking algorithm is proposed that can cope with the accuracy demands of robotic laser welding. A trajectory-based control architecture is presented, which had to be developed for this seam tracking algorithm. Cartesian locations (position and orientation) are added to the robot trajectory during the robot motion. In this way, sensor information obtained during the robot motion is used to generate the robot trajectory while moving. Experiments have been performed to prove the tracking capabilities of the seam tracking algorithm. 相似文献
18.
针对在Kinect平台利用人体动作进行人机交互的时效性问题,提出了一种基于时间序列相似性的快速人体动作识别方法。通过Kinect获取人体全身20个关节点,提取关键点的空间三维坐标,转化成特征向量,该特征向量模型能很好地对全身动作进行表示;在动作识别方面提出了一种快速动态时间弯曲距离(Fast Dynamic Time Warping,F-DTW)算法,解决了因动作速度不同导致的两时间序列在时间轴上不一致的问题,通过引入下界函数和提前终止技术对算法进行加速优化,解决动作识别的时延问题,从而能快速地控制机器人;定义20种动作进行识别,平均识别速度较传统算法大大提高,验证了方法的有效性,满足与机器人交互的要求。 相似文献
19.
介绍了一个应用滑觉传感器组成的握力自适应控制系统,并给出了一种新型滑觉传感器的设计及结构,实验证明,它能够满足自适应控制的需要。 相似文献