Laudante Gianluca, Mirto Michele, Pennacchio Olga, Pirozzi Salvatore
Engineering Department, University of Campania "Luigi Vanvitelli", Aversa, Italy.
Front Robot AI. 2025 Jun 10;12:1581154. doi: 10.3389/frobt.2025.1581154. eCollection 2025.
The rapid advancement of collaborative robotics has driven significant interest in Human-Robot Interaction (HRI), particularly in scenarios where robots work alongside humans. This paper considers tasks where a human operator teaches the robot an operation that is then performed autonomously.
A multi-modal approach employing tactile fingers and proximity sensors is proposed, where tactile fingers serve as an interface, while proximity sensors enable end-effector movements through contactless interactions and collision avoidance algorithms. In addition, the system is modular to make it adaptable to different tasks.
Demonstrative tests show the effectiveness of the proposed system and algorithms. The results illustrate how the tactile and proximity sensors can be used separately or in a combined way to achieve human-robot collaboration.
The paper demonstrates the use of the proposed system for tasks involving the manipulation of electrical wires. Further studies will investigate how it behaves with object of different shapes and in more complex tasks.
协作机器人技术的迅速发展引发了人们对人机交互(HRI)的浓厚兴趣,特别是在机器人与人类并肩工作的场景中。本文考虑的任务是,人类操作员向机器人传授一种操作,然后由机器人自主执行该操作。
提出了一种采用触觉手指和接近传感器的多模态方法,其中触觉手指作为接口,而接近传感器通过非接触式交互和碰撞避免算法实现末端执行器的运动。此外,该系统是模块化的,使其能够适应不同的任务。
演示测试表明了所提出的系统和算法的有效性。结果说明了触觉和接近传感器如何单独使用或组合使用以实现人机协作。
本文展示了所提出的系统在涉及电线操作的任务中的应用。进一步的研究将调查它在处理不同形状物体和更复杂任务时的表现。