【标题】Sales of industrial robots on the rise
【参考中译】工业机器人的销量在上升
【类型】 期刊
【作者】 Justin Burns
【摘要】 Sales of industrial robots have reached a strong recovery with a new record of 486,800 units were shipped globally-an increase of 27% compared to the previous year with Asia/Australia seeing the largest growth in demand and installations up 33% reaching 354,500 units, according to figures from the International Federation of Robotics (IFR).
【参考中译】 根据国际机器人联合会(IFR)的数据，工业机器人的销售已经强劲复苏，全球发货量达到48.68万台，创历史新高，与前一年相比增长了27%，其中亚洲/澳大利亚的需求增长最快，安装数量增长33%，达到35.45万台。
【来源】 Machinery 2022, vol.180
【入库时间】 2023/5/30
【标题】Evaluation of Robot Degradation on Human-Robot Collaborative Performance in Manufacturing
【参考中译】制造中机器人退化对人-机器人协同性能的影响评价
【关键词】 Manufacturing; Degradation; Industrial robot; Human-robot collaboration
【参考中译】 制造；退化；工业机器人；人-机器人协作
【作者】 Vinh Nguyen; Jeremy Marvel
【摘要】 Human-robot collaborative systems are highly sought candidates for smart manufacturing applications because of their adaptability and consistency in production tasks. However, manufacturers are still hesitant to adopt these systems because of the lack of metrics regarding the influence of the degradation of collaborative industrial robots on human-robot teaming performance. Hence, this paper defines teaming performance metrics with respect to robot degradation. In addition, the defined metrics are applied to a human-robot collaborative inverse peg-in-hole case study with respect to the degradation of the joint angular encoder and current sensor. Specifically, this case study compares pure insertion versus insertion with spatial scanning to solve the peg-in-hole problem, and manual intervention is implemented in the event of robotic failure. The metrics used in the case study showed that pure insertion more sensitive to robot degradation with manual intervention was required at 0.04° as opposed to 0.12° from insertion with scanning. Therefore, insertion with scanning was shown to be more robust to robot degradation at the cost of a slower insertion time of 9.48 s compared to 3.19 s. Thus, this paper provides knowledge and usable metrics regarding the influence of robot degradation on human-robot collaborative systems in manufacturing applications.
【参考中译】 人-机器人协作系统因其在生产任务中的适应性和一致性而成为智能制造应用的热门候选系统。然而，制造商仍然对采用这些系统犹豫不决，因为缺乏关于协作工业机器人的退化对人-机器人协作性能的影响的衡量标准。因此，本文定义了与机器人降级相关的团队绩效指标。此外，将所定义的度量应用于人-机器人协作的反向钉扎-孔案例研究，该案例涉及关节角度编码器和电流传感器的退化。具体地说，这个案例研究比较了纯插入和插入与空间扫描，以解决钉在洞中的问题，并在机器人发生故障时实施人工干预。案例研究中使用的衡量标准表明，在人工干预下，纯插入对机器人退化更敏感，在0.04°时需要纯插入，而在扫描时插入时需要0.12°。因此，扫描插入对机器人退化具有更强的鲁棒性，插入时间仅为9.48 S，而插入时间仅为3.19 S。因此，本文为制造应用中机器人退化对人-机器人协作系统的影响提供了知识和有用的度量。
【来源】 Smart and Sustainable Manufacturing Systems 2022, vol.6, no.1
【标题】Active learning based on computer vision and human-robot interaction for the user profiling and behavior personalization of an autonomous social robot
【参考中译】基于计算机视觉和人机交互的自主社交机器人用户特征和行为个性化主动学习
【关键词】 Active learning; Human-robot interaction; Social robots; User profiling; User recognition
【参考中译】 主动学习；人机交互；社交机器人；用户特征描述；用户识别
【作者】 Marcos Maroto-Gomez; Sara Marques-Villaroya; Jose Carlos Castillo; Alvaro Castro-Gonzalez; Maria Malfaz
【摘要】 Social robots coexist with humans in situations where they have to exhibit proper communication skills. Since users may have different features and communicative procedures, personalizing human-robot interactions is essential for the success of these interactions. This manuscript presents Active Learning based on computer vision and human-robot interaction for user recognition and profiling to personalize robot behavior. The system identifies people using Intel-face-detection-retail-004 and FaceNet for face recognition and obtains users' information through interaction. The system aims to improve human-robot interaction by (i) using online learning to allow the robot to identify the users and (ii) retrieving users' information to fill out their profiles and adapt the robot's behavior. Since user information is necessary for adapting the robot for each interaction, we hypothesized that users would consider creating their profile by interacting with the robot more entertaining and easier than taking a survey. We validated our hypothesis with three scenarios: the participants completed their profiles using an online survey, by interacting with a dull robot, or with a cheerful robot. The results show that participants gave the cheerful robot a higher usability score (82.14/100 points), and they were more entertained while creating their profiles with the cheerful robot than in the other scenarios. Statistically significant differences in the usability were found between the scenarios using the robot and the scenario that involved the online survey. Finally, we show two scenarios in which the robot interacts with a known user and an unknown user to demonstrate how it adapts to the situation.
【参考中译】 在社交机器人必须表现出适当的沟通技能的情况下，它们与人类共存。由于用户可能具有不同的功能和交流过程，个性化的人-机器人交互对于这些交互的成功至关重要。这篇手稿介绍了基于计算机视觉和人-机器人交互的主动学习，用于用户识别和剖析，以个性化机器人行为。该系统使用Intel-Face-Detect-Retail-004和FaceNet进行人脸识别，并通过交互获取用户信息。该系统旨在通过(I)使用在线学习来允许机器人识别用户和(Ii)检索用户的信息来填写他们的个人资料并调整机器人的S行为，从而改善人与机器人的交互。由于用户信息是使机器人适应每次交互所必需的，因此我们假设用户会考虑通过与机器人交互来创建他们的个人资料，这比进行调查更有趣、更容易。我们用三种情景验证了我们的假设：参与者通过在线调查、通过与枯燥的机器人互动或与快乐的机器人互动来完成他们的个人资料。结果显示，参与者给快乐机器人的可用性评分更高(82.14/100分)，与其他场景相比，他们使用快乐机器人创建个人资料时更具娱乐性。在使用机器人的场景和涉及在线调查的场景之间，在可用性方面发现了统计上的显著差异。最后，我们展示了机器人与已知用户和未知用户交互的两个场景，以演示它如何适应这种情况。
【来源】 Engineering Applications of Artificial Intelligence 2023, vol.117, no.Pt.B