Mechanical and Industrial Engineering Department, Università degli Studi di Brescia, Via Branze 38, 25123 Brescia, Italy.
STIIMA-CNR-Institute of Intelligent Industrial Technologies and System, National Researcher Council of Italy, 00185 Roma, Italy.
Sensors (Basel). 2023 Jun 20;23(12):5762. doi: 10.3390/s23125762.
Safety plays a key role in human-robot interactions in collaborative robot (cobot) applications. This paper provides a general procedure to guarantee safe workstations allowing human operations, robot contributions, the dynamical environment, and time-variant objects in a set of collaborative robotic tasks. The proposed methodology focuses on the contribution and the mapping of reference frames. Multiple reference frame representation agents are defined at the same time by considering egocentric, allocentric, and route-centric perspectives. The agents are processed to provide a minimal and effective assessment of the ongoing human-robot interactions. The proposed formulation is based on the generalization and proper synthesis of multiple cooperating reference frame agents at the same time. Accordingly, it is possible to achieve a real-time assessment of the safety-related implications through the implementation and fast calculation of proper safety-related quantitative indices. This allows us to define and promptly regulate the controlling parameters of the involved cobot without velocity limitations that are recognized as the main disadvantage. A set of experiments has been realized and investigated to demonstrate the feasibility and effectiveness of the research by using a seven-DOF anthropomorphic arm in combination with a psychometric test. The acquired results agree with the current literature in terms of the kinematic, position, and velocity aspects; use measurement methods based on tests provided to the operator; and introduce novel features of work cell arranging, including the use of virtual instrumentation. Finally, the associated analytical-topological treatments have enabled the development of a safe and comfortable measure to the human-robot relation with satisfactory experimental results compared to previous research. Nevertheless, the robot posture, human perception, and learning technologies would have to apply research from multidisciplinary fields such as psychology, gesture, communication, and social sciences in order to be prepared for positioning in real-world applications that offer new challenges for cobot applications.
安全性在协作机器人（cobot）应用中的人机交互中起着关键作用。本文提供了一种通用程序，以保证安全工作站允许人类操作、机器人贡献、动态环境和一组协作机器人任务中的时变物体。所提出的方法侧重于参考框架的贡献和映射。通过考虑自我中心、分配中心和路线中心的观点，同时定义了多个参考框架表示代理。代理被处理，以提供对正在进行的人机交互的最小和有效的评估。所提出的公式基于多个协作参考框架代理的推广和适当合成。因此，通过实施和快速计算适当的安全相关定量指标，可以实时评估与安全相关的影响。这允许我们定义并及时调节所涉及的 cobot 的控制参数，而不会受到被认为是主要缺点的速度限制。已经进行了一系列实验来验证该研究的可行性和有效性，使用了一个七自由度拟人臂与心理测试相结合。所获得的结果在运动学、位置和速度方面与当前文献一致；使用基于提供给操作员的测试的测量方法；并引入了工作单元布置的新特征，包括虚拟仪器的使用。最后，相关的分析拓扑处理使得能够开发一种安全和舒适的人机关系测量方法，与之前的研究相比，实验结果令人满意。然而，机器人姿势、人类感知和学习技术将不得不应用多学科领域的研究，如心理学、手势、通信和社会科学，以便为在提供新挑战的现实世界应用中进行定位做好准备。
