Shenyang Institute of Automation,Chinese Academy Of Sciences
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一种具有误差补偿功能的水下机器人电机组装装置
No full text本发明涉及水下机器人装配领域，具体地说是一种具有误差补偿功能的水下机器人电机组装装置，包括支撑架体和误差补偿器，其中所述支撑架体上设有可升降的滑座，且所述滑座上设有卡盘，所述支撑架体下端设有底座，且所述底座上设有误差补偿器，并且所述误差补偿器与所述卡盘同轴设置，所述误差补偿器包括依次相连的上连接法兰、波纹管和下连接法兰，且所述下连接法兰与所述底座固连，待组装电机的定子固定筒固设于所述上连接法兰上。本发明能够满足水下机器人电机组装的精度要求，且保证组装效率
一种大型水下机器人分段位姿检测对接装置及方法
No full text本发明涉及一种大型水下机器人分段位姿检测对接装置及方法，其中两个调整机构均包括前支座、后支座和四个X向移动的小车，小车内设有Y向移动的横移座，横移座上设有Z向升降的支撑轴，前支座两端分别通过前侧两个小车上的支撑轴支撑，后支座两端分别通过后侧两个小车上的支撑轴支撑，第一舱段两端通过第一调整机构中的后支座和前支座支撑，第二舱段两端通过第二调整机构中的后支座和前支座支撑，第一舱段和第二舱段对接端面法兰上均设有靶球，且各个靶球通过激光跟踪仪扫描，小车、横移座和支撑轴均通过控制系统控制移动，且控制系统根据激光跟踪仪扫描的靶球位置计算移动量。本发明能够准确反映舱段对接端面的位置姿态，并且自动调整对接
磁悬液自动搅拌输送机
No full text本实用新型属于机械自动化工程领域，具体地说是一种磁悬液自动搅拌输送机，包括超声波液位传感器、输送水泵、搅拌桶、搅拌机构及防水电机，防水电机安装于搅拌桶的底面，防水电机的输出端与搅拌机构相连，搅拌桶内盛装有磁悬液溶液，搅拌机构及防水电机均浸没在磁悬液溶液液面以下，防水电机驱动搅拌机构旋转，通过搅拌机构对磁悬液溶液进行搅拌；搅拌桶的侧壁顶部安装有用于监控磁悬液溶液液面高低的超声波液位传感器，输送水泵可拆卸地安装在搅拌桶的侧壁上，输送水泵的底部浸没在磁悬液溶液液面以下。本实用新型具有结构简单，功率高效，转速连续可调，可实现自主输送及自主预警等特点
一种基于加速度反馈增强的旋翼无人机抗风扰控制方法
No full text本发明涉及旋翼无人机控制领域，具体涉及一种基于加速度反馈增强的旋翼无人机抗风扰控制方法，所述的抗风扰控制方法包括常规高增益加速度反馈的设计，引入前置滤波器，采用基于几何控制理论的级联PID控制器作为模型的原始控制器，结合加速度反馈方法构成加速度反馈增强几何控制器，并对旋翼无人机模型进行解耦，对解耦后的系统设计级联H∞控制器，再与上述加速度反馈相结合，设计了加速度反馈增强的鲁棒H∞控制器。该控制方法解决了常规高增益加速度反馈在实际系统中难以实现的问题，加速度反馈与鲁棒H∞控制方法的结合，不仅保证了系统的稳定性，进一步提高了系统的抗扰动能力，将该方法应用于旋翼无人机保证了其在风扰环境下的稳定航行
Research on multi-AUV cooperative obstacle avoidance method in unknown environment
No full text针对多AUV（autonomous underwater vehicle）系统在未知环境中进行路径规划时，难以兼顾避障与编队的问题，提出了一种基于领航-跟随者与行为的多AUV协同避障方法。首先，通过构造碰撞危险度及偏离目标评价函数，设计了AUV局部路径规划方法；在此基础上，结合编队控制方法，分别为领航者和跟随者设计不同的行为以及行为选择模式。半物理仿真实验结果表明，该算法能够实现多AUV系统在未知环境中的协同避障，且队形偏离度与恢复队形时间优于传统多机器人避障算法。实验结果证明了该算法的可行性与有效性。</p
Proximal policy optimization with model-based methods
No full textModel-free reinforcement learning methods have successfully been applied to practical applications such as decision-making problems in Atari games. However, these methods have inherent shortcomings, such as a high variance and low sample efficiency. To improve the policy performance and sample efficiency of model-free reinforcement learning, we propose proximal policy optimization with model-based methods (PPOMM), a fusion method of both model-based and model-free reinforcement learning. PPOMM not only considers the information of past experience but also the prediction information of the future state. PPOMM adds the information of the next state to the objective function of the proximal policy optimization (PPO) algorithm through a model-based method. This method uses two components to optimize the policy: the error of PPO and the error of model-based reinforcement learning. We use the latter to optimize a latent transition model and predict the information of the next state. For most games, this method outperforms the state-of-the-art PPO algorithm when we evaluate across 49 Atari games in the Arcade Learning Environment (ALE). The experimental results show that PPOMM performs better or the same as the original algorithm in 33 games.</p
Electroactive Polymer-Based Soft Actuator with Integrated Functions of Multi-Degree-of-Freedom Motion and Perception
No full textSoft actuators have received extensive attention in the fields of soft robotics, biomedicine, and intelligence systems owing to their advantages of pliancy, silence, and essential safety. However, most existing soft actuators have only single actuation elements and lack sensing. Therefore, it is difficult for them to perform complex motions with multiple degrees of freedom (multi-DOFs) and high precision. This article reports a miniature columnar dielectric elastomer actuator (DEA) with multi-DOF actuation and sensing, which was fabricated with an electroactive polymer acrylic film (Very High Bond [VHB] acrylic film by 3M Company) and carbon black grease electrodes. The arrangement of the simulation electrodes on the VHB was optimized to realize multi-DOF actuation, and the sensing electrodes were configured on the outer part of the DEA to realize real-time sensing. The results showed that the soft actuator can achieve all-round actuation through the selective power of the stimulation electrodes with a controllable voltage. The maximum bending angle and axial strain of the actuator reached 50 degrees and 13%, respectively. Moreover, the deformation modes, direction, and quantity could be precisely measured using the integrative sensing function. In addition, to demonstrate the advantages of the proposed actuator, a manipulator with multiple actuators was designed and controlled to realize different actions of screwing and grasping with sensing. This research is useful not only for the design of multifunctional soft actuators but also for the development of soft robots with flexible, complex, and precisely controllable motions.</p
SeNic: An Open Source Dataset for sEMG-Based Gesture Recognition in Non-ideal Conditions
No full textIn order to reduce the gap between the laboratory environment and actual use in daily life of human-machine interaction based on surface electromyogram (sEMG) intent recognition, this paper presents a benchmark dataset of sEMG in non-ideal conditions (SeNic). The dataset mainly consists of 8-channel sEMG signals, and electrode shifts from an 3D-printed annular ruler. A total of 36 subjects participate in our data acquisition experiments of 7 gestures in non-ideal conditions, where non-ideal factors of 1) electrode shifts, 2) individual difference, 3) muscle fatigue, 4) inter-day difference, and 5) arm postures are elaborately involved. Signals of sEMG are validated first in temporal and frequency domains. Results of recognizing gestures in ideal conditions indicate the high quality of the dataset. Adverse impacts in non-ideal conditions are further revealed in the amplitudes of these data and recognition accuracies. To be concluded, SeNic is a benchmark dataset that introduces several non-ideal factors which often degrade the robustness of sEMG-based systems. It could be used as a freely available dataset and a common platform for researchers in the sEMG-based recognition community. The benchmark dataset SeNic are available online via the website3.</p
Research and application of a multi-degree-of-freedom soft actuator
No full textABS T R A C T In recent years, soft pneumatic actuators with soft and flexible materials have been widely studied in the field of soft gripper and soft bionic robot. Up to present, the soft actuators studied usually have one motion manner such as extending, bending, twisting or rotation. In this paper, we propose a new type of multi-degree-of-freedom soft pneumatic actuator (MDoF SPA) that can extend or rotate in response to pressured air inputted in different chambers. A fabrication method was proposed. A mathematical model based on large deformation theory was presented to predict the elongation displacement and bending angle. Moreover, finite element analysis and experimental investigation were performed to verify the theoretical results. The output force during elongation and blocking force during bending were also tested. Finally, two MDoF SPAs were utilized to fabricate a crawling robot. The gait and hardware of crawling robot were shown. The average moving speed of linear motion, maximum bending angle were investigated as well. Experiments revealed the robot actuated by MDoF SPAs has a good comprehensive performance, which has great potential in search, detection, rescue and other operations in a narrow environment. This work can guide the design and application of MDoF SPAs in the future
Equivalent Ladder Cylinder Unfolding Method of Quasi-Cylinder Label
No full text目的针对半径不等的类圆柱标签的全表面展开问题,提出类圆柱标签等效阶梯柱面展开方法。方法提取4个视角下图像中的类圆柱标签最小外接矩形,根据提取结果建立位姿估计模型。基于微积分的化曲为直的思想,结合标签的位姿和各视角的轮廓,建立等效阶梯的类圆柱标签3D点云。利用双线性插值法对点云进行渲染,并通过NCC算法进行图像拼接,最终实现半径不等的类圆柱标签全表面展开。结果类圆柱棋盘格标签仿真模型与某品牌口香糖标签全表面展开实验表明,文中提出的算法较传统算法具有较高的精度,针对1号模型,在x轴、y轴方向上的方差分别为1.37像素和0.58像素。结论类圆柱标签等效阶梯柱面展开方法可以有效地实现类圆柱标签全表面展开,为后续的标签检测提供基础。</p