Application of Emotional Intelligence in Improvement of Human-Robot Collaboration

Introduction

The field of technology is undergoing rapid development, and as a result, robots are increasingly being integrated into human-centric environments. They are transitioning from performing activities that are mechanistic to taking on positions that need nuanced human interaction. This shift presents the problem of enabling robots to comprehend human emotions and respond appropriately to them in a manner that is appropriate. When emotional intelligence (EI) is included into robotics, it has the potential to revolutionize these relationships, converting them from simple functional exchanges into nuanced and empathic collaborations. The ability to notice, analyze, manage, and respond to one's emotions is a component of emotional intelligence (EI), which has long been regarded as a uniquely human capability that is crucial for managing social interactions and relationships (Tyagi, et al.2022). We are able to improve the effectiveness and harmony of human-robot cooperation by incorporating EI into robots. This will result in encounters that seem more natural and productive. This chapter investigates the application of emotional intelligence (EI) in robots, with a special emphasis on real-world applications such as healthcare, where robots can provide comfort and support to vulnerable populations, and retail, where they adapt to the emotional states of customers in order to improve service delivery. Furthermore, it dives into the ethical issues and design concepts that are required for the development of emotionally intelligent robots that respect privacy and adhere to moral norms. This contributes to the redefinition of the future possibilities of human-robot relationships in a society that is technologically evolved. According to (Amorim, et al. 2019, Kumar, et al. 2024), the application of artificial intelligence (AEI) for the purpose of enhancing service efficiency and dependability may be broken down into three distinct dimensions: augmenting, assisting, and mimicking the production capabilities of customers and/or providers. A model was proposed by (Noohi, et al. 2016) that enables us to compute the interaction force that occurs during a dyadic cooperative object-handling task. This model is derived directly from the various hypotheses that have been developed regarding the movements of the human arm.

Human-Robot Collaboration

Human-robot collaboration (HRC) is at the forefront of technological innovation, supporting the formation of dynamic collaborations between humans and robots in a variety of different industries. HRC promises to enhance human capacities, improve efficiency, and open up new possibilities across a wide range of industries, including manufacturing, healthcare, education, and service sectors. It is important to note that this paradigm shift is not devoid of difficulties. It is of the utmost importance to ensure safe engagement, effective communication, and to address any ethical problems that may arise. However, as technology continues to advance, human-robot collaboration (HRC) has the potential to bring about a revolution in the way we work, learn, and live. Villani, et al. (2018) highlighted a lengthy review on human–robot collaboration in industrial environments, with a particular emphasis on difficulties related to physical and cognitive interaction. This review was discussed in considerable detail.

This might usher in a future in which people and robots work together in a seamless manner for the sake of mutual benefit and advancement. In the context of adaptive collaborative robots, (Mukherjee, et al. (2021), gave a detailed assessment of the machine learning (ML) approaches and industrial applications of all of these methodologies. It is worth to note that that data must be de-noised before analysis (Tripathi & Siddiqi 2016, Tripathi 2020).

Figure 1.

Human-Robot collaboration in industry