关键词： Emotional state detection   Cluster analysis   Pleasure   Physiological signals   Social robotics  

摘要： Future social robots should have personalized behaviors based on user emotional state to fit more in ordinary users activities and to improve the human-robot interaction. Several, literature works use cameras to record emotions. However, these approaches may not be effective in everyday life, due to camera obstructions and different types of stimulation, which can be related also with the interaction with other human beings. Therefore, in this work, it is investigated the electrocardiogram, the electrodermal activity, and the electric brain activity physiological signals as main informative channels. The aforementioned signals have been acquired through the use of a wireless wearable sensor network. An experimental methodology was proposed to induce three different emotional states by means of social interaction. Two different combinations of sensors were analyzed using three different time-window frames (180s, 150s, and 120s) and classified with three unsupervised machine learning approaches (K-Means, K-medoids and Self-organizing maps). Finally, their classification performances were compared to the ones obtained by four commonly used supervised techniques (i.e. Support Vector Machine, Decision Tree and k-nearest neighbor) to discuss the optimal combination of sensors, time-window length, and unsupervised classifier. Fifteen healthy young participants were recruited in the study and more than 100 instances were analyzed. The proposed approaches achieve an accuracy of 77% in the best-unsupervised case and 85% with the best-supervised ones. (C) 2019 Elsevier B.V. All rights reserved.

关键词： biarticular muscles   leg morphology   locomotor subfunctions   biomechanical template models   legged robotics   assistive devices  

摘要： Leg morphology is an important outcome of evolution. A remarkable morphological leg feature is the existence of biarticular muscles that span adjacent joints. Diverse studies from different fields of research suggest a less coherent understanding of the muscles' functionality in cyclic, sagittal plane locomotion. We structured this review of biarticular muscle function by reflecting biomechanical template models, human experiments and robotic system designs. Within these approaches, we surveyed the contribution of biarticular muscles to the locomotor subfunctions (stance, balance and swing). While mono- and biarticular muscles do not show physiological differences, the reviewed studies provide evidence for complementary and locomotor subfunction-specific contributions of mono- and biarticular muscles. In stance, biarticular muscles coordinate joint movements, improve economy (e.g. by transferring energy) and secure the zig-zag configuration of the leg against joint overextension. These commonly known functions are extended by an explicit role of biarticular muscles in controlling the angular momentum for balance and swing. Human-like leg arrangement and intrinsic (compliant) properties of biarticular structures improve the controllability and energy efficiency of legged robots and assistive devices. Future interdisciplinary research on biarticular muscles should address their role for sensing and control as well as non-cyclic and/or non-sagittal motions, and non-static moment arms.

关键词： Robotics  

摘要： High-throughput fluidic technologies have increased the speed and accuracy of fluid processing to the extent that unlocking further gains will require replacing the human operator with a robotic counterpart. Recent advances in chemistry and biology, such as gene editing, have further exacerbated the need for smart, high-throughput experimentation. A growing number of innovations at the intersection of robotics and fluidics illustrate the tremendous opportunity in achieving fully self-driving fluid systems. We envision that the fields of synthetic chemistry and synthetic biology will be the first beneficiaries of AI-directed robotic and fluidic systems, and largely fall within two modalities: complex integrated centralized facilities that produce data, and distributed systems that synthesize products and conduct disease surveillance.

关键词： Deep reinforcement learning   End-to-end DRL strategy   Hybrid DRL strategy   Deep deterministic policy gradient   Cable-driven parallel robot  

摘要： Deep reinforcement learning (DRL) has been proven effective in learning policies of high-dimensional states and actions. Recently, a variety of robot manipulation tasks have been accomplished using end-to-end DRL strategies. An end-to-end DRL strategy accomplishes a robot manipulation task as a black box. On the other hand, a robot manipulation task can be divided into multiple subtasks and accomplished by non-learning-based approaches. A hybrid DRL strategy integrates DRL with non-learning-based approaches. The hybrid DRL strategy accomplishes some subtasks of a robot manipulation task by DRL and the rest subtasks by non-learning-based approaches. However, the effects of integrating DRL with non-learning-based approaches on the learning speed and the robustness of DRL to model uncertainties have not been discussed. In this study, an end-to-end DRL strategy and a hybrid DRL strategy are developed and compared in controlling a cable-driven parallel robot. This study shows that, by integrating DRL with non-learning-based approaches, the hybrid DRL strategy learns faster and is more robust to model uncertainties than the end-to-end DRL strategy. This study demonstrates that, by taking advantages of both learning and non-learning-based approaches, the hybrid DRL strategy provides an alternative to accomplish a robot manipulation task. (C) 2019 Elsevier B.V. All rights reserved.

关键词： 码垛机器人   动力学模型   SolidWorks   ADAMS   仿真  

摘要： 目的工业码垛机器人因其负载大、自动化程度高等优点,被广泛应用于食品、药品、化肥等生产线中,但是机器人动力学模型的建立较为困难,为了得到码垛机器人设计参数,运用SolidWorks与Matlab联合仿真。方法通过SolidWorks建立码垛机器人实体模型,并将其导入到ADAMS中,在仿真软件中通过设置具体参数,得到机器人动力学仿真模型。结果通过SolidWorks与ADAMS的结合仿真,可以大大缩短设计周期,有效地获得码垛机器人的动力学特性参数。结论运用SolidWorks与Matlab联合仿真,可以形象直观地模拟机器人的三维运动情况,并获取其动力学特性参数。

关键词： 机器人竞赛   教学设计   设计型学习   FLL工程挑战赛  

摘要： 设计型学习强调通过分析、设计、开发和实施的反复循环来改进教育实践,其理念与机器人竞赛的备赛过程一致,因此,可采用DBL的理念开展机器人竞赛的教学过程。本文主要针对机器人竞赛的课堂教学设计,在深入了解众多中小学机器人教学方式的基础上,查阅了国内外相关文献,并结合笔者连续两年深入中小学指导学生参加FLL工程挑战赛的实践经验,不断改进教学策略,以期为一线教师机器人竞赛教学的开展提供参考。

关键词： 大数据   机器人   计算机科学与技术   课程建设   教育教学改革  

摘要： 本本以现今大数据应用环境为研究背景,面向计算机应用科学类专业学生为例,针对目前高校中高等教育教学存在的问题,提出如何建设《机器人学》课程的改革思路。通过对《机器人学》课程的发展情况、研究进展、课程目标以及探索进行剖析,并对教学内容、教学手段、考核方法等几个方面进行分析及总结《机器人学》课程的建设情况,并立足新的计算机应用与软件工程类专业学生的特点,基于大数据背景下特征特点建设新《机器人学》课程,实现与大数据、人工智能、机器人以及计算机应用等技术的交叉融合,对大学课程建设和改革提供引导作用。

关键词： 重载搬运机器人   动态性能   能量耗散   五次多项式插值算法   机电联合仿真  

摘要： 关节型重载搬运机器人各运动关节动态性能和能量耗散水平直接影响机器人以及运动规划的可达性。以ABB公司生产的IRB460型重载搬运机器人为研究对象,针对其机械本体结构特性,建立重载搬运机器人三维模型。若仅考虑回转轴、大臂和小臂组成的三个自由度,重载搬运机器人系统模型可简化成空间三关节机器人系统模型;依据拉格朗日力学方程建立重载搬运机器人系统动力学模型,利用机械臂逆运动学和五次多项式插值算法完成对多关节机械臂空间轨迹规划。通过动力学仿真分析可知,重载搬运机器人各运动关节的动态性能变化稳定且能量耗散较小,且能够沿着预定轨迹完成PTP模式的运动控制。最后,搭建控制系统仿真实验平台,提出一种重载搬运机器人控制系统模型,实验结果表明,所设计的重载搬运机器人控制系统能够准确、稳定的控制各运动关节运动,验证了各运动关节驱动电动机功率参数选择的合理性,为实际的工业生产应用奠定了理论基础。

关键词： 弹药装填机器人   旋量理论   动力学  

摘要： 针对弹药装填机器人动力学模型存在耦合性、非线性的特点,提出了基于旋量理论的弹药装填机器人动力学建模方法。通过构建弹药装填机器人的动能旋量、势能旋量和驱动力旋量,进而确定了弹药装填机器人惯性力、重力、哥氏力与离心力的数学模型,最后建立了基于旋量理论的弹药装填机器人拉格朗日动力学方程。通过动力学仿真分析验证了该方法的合理性,为下一步的控制策略打下坚实基础。

关键词： 绳系并联机器人   绳阻尼   动力学特性   风洞试验   模型支撑  

摘要： 针对应用于风洞试验模型支撑的绳系并联机器人的设计需求,采用实验和理论建模相结合的方法,研究绳阻尼对绳系并联机器人动力学特性的影响。首先,为了准确地定量描述绳阻尼,设计了一套测量绳阻尼的实验装置,通过实验得到了不同参数下的绳阻尼比;其次,考虑了绳阻尼,对绳张力进行建模,并提出了考虑绳阻尼的绳系并联机器人的动力学建模方法;最后,分析了绳阻尼对绳系并联机器人动力学特性的影响。结果表明:绳阻尼对绳系并联机器人动力学响应的影响主要体现在响应幅值上,绳直径越大,绳阻尼对绳系并联机器人动力学响应的减振作用越明显。当绳阻尼系数大于0.6 N·s/m时,不论绳直径粗细如何,绳阻尼对绳系并联机器人动力学特性的影响不能忽略。研究结果可为绳系并联机器人的设计提供理论指导。