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Design and Development of a Work Cell with a One-Handed Soldering Tool for Enhanced Human-Robot Collaboration

Natchanon Suppaadirek, Maximilien Sonnic, Raul Ariel Duran Jimenez, Tomohiro Shibata

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Abstract

The challenge of human-robot collaboration, par- ticularly in the context of enhancing the productivity of work processes, has been a pivotal area of research and development for many years. Despite significant advancements, there remains a substantial gap in the design of these systems to cater specifically to individuals with disabilities. This paper presents an innovative approach in assistive robotics, focusing on the development of a work cell designed to facilitate individuals with single-arm functionality. Through the integration of depth camera technology, machine learning algorithms, and Medi- apipe human tracking, our system is capable of interpreting human intentions, thereby making interactions with robots more intuitive and effective. Central to our research is the design of a specialized workspace that assists in object handling and incorporates a fully functional One-Handed Soldering Tool, integrated within a robotic arm setup. This work cell is tailored for users with limited arm functionality, demonstrating the system’s versatility and providing invaluable insights into the practical implementation of applied robotics to bridge the theoretical and practical aspects of assistive technology.

Index terms

Intention Recognition Machine Learning for Robot Control Human-Robot Collaboration