Artificial Intelligences in Industrial Robots: A Framework Based on Gardner’s Multiple Intelligences
Jorge A. Ruíz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Eric Simancas-Acevedo, Ricardo A. Barrera-Cámara · International Journal of Combinatorial Optimization Problems and Informatics. · 2024
Industrial robots, both in manufacturing and non-manufacturing sectors, are evolving rapidly, driven by advancements in artificial intelligence (AI). This paper presents a comprehensive survey of industrial robots, framed through the lens of Howard Gardner’s theory of multiple intelligences. By categorising various AI capabilities in industrial robots—such as visual recognition, decision-making, and collaborative interaction—based on Gardner’s intelligence framework, we provide a novel taxonomy that bridges human cognitive abilities and artificial systems. The survey explores the historical development of industrial robots, the current state of AI implementation, and future trends in robotics. Additionally, we discuss the implications of these advancements for industries and their workforce, as well as the ethical considerations surrounding the growing autonomy of AI systems. This paper aims to serve as a reference point for researchers and professionals seeking to understand the intersection of cognitive science and industrial AI, highlighting the potential and challenges of integrating AI into robotic systems.