Towards seamless collaboration of humans and high-payload robots: An automotive case study. (October 2023)

• Record Type: Journal Article
• Authors: Andronas, Dionisis; Kampourakis, Emmanouil; Papadopoulos, Giorgos; Bakopoulou, Katerina; Kotsaris, Panagiotis Stylianos; Michalos, George; Makris, Sotiris
• Is Part Of: Robotics and computer-integrated manufacturing. Volume 83(2023)
• Publication Date: 2023-10
• Subjects: Human robot collaboration -- Interaction -- Augmented reality -- Safety -- Design; Robots, Industrial -- Periodicals; Computer integrated manufacturing systems -- Periodicals; Robotics -- Periodicals; Robots industriels -- Périodiques; Productique -- Périodiques; Robotique -- Périodiques; 670.285
• DOI: 10.1016/j.rcim.2023.102544
• Languages: English
• ISSNs: 0736-5845

Abstract

Highlights: Design and implementation of a human robot collaboration system for heavyweight component assembly Multi-modal human-robot interaction pipeline Gesture-based contactless manual guidance module Fenceless safety monitoring system and logic Augmented reality (AR) based training application for operator inclusion Validation and testing of integrated system on automotive use case Abstract: Despite the ergonomic challenges that large-sized product assemblies underlay for human operators, related processes are deselected from hybrid automation mostly due to the payload limitations of collaborative robots. Driven by industrial requirements for ergonomic and performance improvement, this paper presents the implementation of a human-high payload robot symbiotic workstation and discusses the key enabling technologies for seamless collaboration, namely: a) a multi-modal human-robot interaction pipeline, b) a gesture based contactless manual guidance module, c) fenceless safety monitoring system and logic, and d) an augmented reality-based training application for operator inclusion. An automotive case study is used for validating the complete hybrid system's usability and performance besides improved operator ergonomics and well-being. This work's findings prove that high-payload robots can support operators through intuitive means of interaction and businesses can rely on collaborative systems for improved performance metrics and job openness. Graphical abstract: Image, graphical abstract