Swarming Microdroplets to a Dexterous Micromanipulator

Many astonishing biological collective behaviors exist in nature, and artificial microrobotic swarms have been developed by emulating these scenarios. However, these microswarms typically have single structures and lack the adaptability that many biological swarms exhibit to thrive in complex environments. Inspired by viscoelastic fire ant aggregations and using a combination of experiment and simulation, a strategy to trigger ferrofluid droplets into forming microswarms exhibiting both liquid-like and solid-like behaviors is reported. By spatiotemporally programming an applied magnetic field, microswarms can be liquefied to implement reversible elongation with a high aspect ratio and solidified into entireties to perform overturning and bending behaviors. It is demonstrated that reconfigurability enables the microswarm to be a mobile dexterous micromanipulator, acting not only as a soft “octopus arm” to explore a confined environment and grasp a targeted object but also adaptively navigate multiple terrains, such as uneven surfaces, curved grooves, complex mazes, high steps, narrow channels, and even wide gaps. This microrobotic swarm can reconfigure both shapes and tasks based on the demands of the environment, presenting novel solutions for a variety of applications.     

Adaptive constraint control for flexible manipulator systems modeled by partial differential equations with dead-zone input

In this article, based on partial differential equations (PDEs), the flexible manipulator system with both dead-zone input and state constraints is studied. The dynamic model of the flexible manipulator system is described by PDEs. The parameters of the dead-zone input are unknown, and the state constraint problem is also considered. An adaptive approach is proposed to offset the effects caused by dead-zone input. Thus, to guarantee that all states remain within their respective constraint regions, the boundary control law based on the barrier Lyapunov function is given, and an adaptive controller is designed. According to the Lyapunov analysis method, the control method is given to ensure that all signals of the closed-loop system are bounded and all states satisfy the constraint conditions. Finally, simulation results show the effectiveness of the proposed control method in this article.     

基于深度分离卷积的情绪识别机器人即时交互研究

情绪识别是人工智能领域的研究热点,人机交互系统若能感知人类的情感行为并能表达情感,将会使机器人与人类的交互更加自然。人类主要通过面部表情、语义语调、肢体语言等几个方面获取情感信息。以拥有高自由度的NAO机器人为应用平台,设计了机器人面部情绪识别和肢体情感表达的人机交互系统。首先,引入深度分离卷积算法对人脸表情(生气、恐惧、伤心、高兴、惊讶和中性)进行特征提取和分类,结果表明通过训练得到的网络模型对FER2013人脸表情测试集的预测正确率可以达到0.711;其次,设计NAO机器人的肢体动作,对6种面部情感做出了分类;最后,对机器人实时表达使用者的情绪状态进行了测试,反馈时间均在2 s内,并对连续10帧预测结果进行了统计分析。     

轻量级电驱水下机械臂设计与运动学分析

设计了一款四功能水下机械臂，并对驱动关节进行了模块化设计和密封测试。为了保证水下机械臂的可靠性，在水下机械臂水下测试前，进行了强度校核和模态分析。为了验证水下机械臂的性能，通过 Ｄ- Ｈ法建立了其运动学模型，在此基础上分别进行了正、逆运动学分析。此外还采用蒙特卡洛法，在正运动学分析的基础上研究了工作空间特点。研究结果将为进一步的运动控制提供有益的帮助。     

基于粒子群优化算法的五自由度机械臂轨迹规划

为了让机械臂的工作时间达到最优,以自主研发的抛光机器人样机为研究对象,针对手表表壳表耳部分的抛光过程,提出PSO算法对五自由度机械臂轨迹规划进行优化,并通过MATLAB软件进行机械臂的仿真与分析。仿真结果表明,基于PSO算法的轨迹规划使机械臂在工作过程中加加速度不会产生突变,运动轨迹精度高,机械臂工作时间达到最优。     

平面结构冗余并联机构的误差敏感度分析

针对一种含闭环支链的平面结构冗余并联机构进行误差敏感度分析。分析了该机构的逆运动学和正运动学。基于矩阵法建立了机构的误差模型，并通过反解、正解结合的方法对该误差模型进行了验证。基于误差模型，得到了评价机构误差敏感度的指标，绘制了各指标在工作空间内的等值线图。基于误差敏感度指标，定义了低误差敏感性工作空间，绘制了低误差敏感性工作空间在工作空间中的分布图。与平面3-RRR并联机构进行了误差敏感度对比分析。结果表明，该机构的低误差敏感性工作空间占比较大，同时可以通过调节其冗余支链不断扩大低误差敏感性工作空间，使机构在大范围空间中保持低误差敏感性。     

Creating the brain and interacting with the brain: an integrated approach to understanding the brain

In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the ‘understanding the brain by creating the brain’ approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain–machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop.     

仿人机器人的机械结构设计与控制系统构建

文章研发了一款适用于机器人教育教学的多功能、多用途、普适性的19自由度的小型仿人机器人,主要完成了该机器人的机械结构设计与控制系统构建工作[1]。所设计的机器人机械结构可靠性高、工艺性好、结构紧凑、样式新颖；所构建的机器人控制系统鲁棒性高、稳定性好、控制准确、反应迅速,圆满地实现了预期的设计任务。通过对优缺点的综合对比,得出组合式构型方案在功能性、实用性和稳定性等方面具有明显优势,有望通过后续软件系统的开发提高其运动效能,真正在青少年机器人教育中发挥重要作用[2]。     

Adaptive sliding mode disturbance rejection control with prescribed performance for robotic manipulators

This study proposes an adaptive sliding mode disturbance rejection control with prescribed performance for robotic manipulators. A transformation with respect to tracking error using certain performance functions is used to ensure the transient and steady-state performances of the trajectory tracking control for robotic manipulators. Using the transformed error, a nonsingular terminal sliding mode surface is proposed. A continuous terminal sliding mode control (SMC) is presented to stabilize the system. To compensate for the uncertainty and external disturbance, a novel sliding mode disturbance observer is proposed. Considering the unknown boundary of the derivative of a lumped disturbance, an adaptive law based on the idea of equivalent control is designed. Combining the adaptive law, continuous nonsingular terminal SMC, and sliding mode disturbance observer, the adaptive sliding mode disturbance rejection control with prescribed performance is developed. Simulations are carried out to demonstrate the effectiveness of the proposed approach.     

基于多自由度气动机械手位置伺服系统稳定性控制研究

基于传统易碎薄板机械手位置伺服控制系统稳定性低、自动化分拣效率低等不足,设计了一种基于笛卡尔坐标式的气动码垛机器手和位置伺服稳定性控制系统。首先,设计并介绍笛卡尔坐标式码垛机械手的基本组成结构,对机械手末端吸盘气动回路控制系统进行设计和分析;然后分别对机械手X、Y、Z三个方向的伺服电机控制原理进行分析并设计了一种位置伺服系统的前馈自适应控制算法;最后,将传统位置闭环PID算法和前馈自适应控制算法进行位置跟踪稳定性对比试验。实验结果表明该笛卡尔坐标式的气动码垛机器手和位置伺服稳定性控制系统设计合理,满足实际生产要求。