Enhancing Human-Robot Collaboration Through Reinforcement Learning

Abstract

In the realm of human-robot collaboration, the effective interaction between humans and robots plays a pivotal role. Reinforcement learning, a subfield of machine learning, has emerged as a promising approach to enhance this collaboration. This paper explores the application of reinforcement learning techniques to improve human-robot cooperation and coordination in various domains. We delve into the challenges and opportunities associated with this technology, highlighting its potential to optimize task execution, adapt to changing environments, and enable robots to learn from human feedback. Furthermore, ethical considerations are discussed to ensure responsible deployment of reinforcement learning in human-robot collaboration.