Towards a Shared Embodied Intelligence of Humanoid Robots: Optimization, Development, and Testing of the Human-Aware ergoCub Robot

Collaboration is an inherent aspect of human behavior, enabling tasks that are otherwise impossible for individuals alone. This collaborative ability stems from the capacity of individuals to coordinate their actions by leveraging internal representations of their companions—a concept known as shared intelligence. Additionally, humans are characterized by physical bodies and cognitive abilities that are optimized in response to their environment, a phenomenon referred to as embodied cognition. In this paper, we propose an architecture that combines shared intelligence and embodied cognition to enable robots to physically collaborate with humans, where robot hardware and control are optimized for human metrics, using representations of the human body and motion intelligence. By doing so, our ultimate aim is to design humanoid robots that possess a degree of shared embodied intelligence. More specifically, the proposed architecture optimizes the robot’s hardware and physical intelligence parameters with respect to human ergonomic metrics. We achieve this by deriving models of human-robot interaction parameterized with respect to the robot’s hardware configurations and by incorporating human models into the robot’s physical intelligence. As a tangible outcome of the proposed architecture, we present the humanoid robot ergoCub, whose body and physical intelligence have been optimized for performing collaborative actions with humans. Our approach yields concrete results in designing humanoid robots that prioritize human ergonomics at both the hardware and physical intelligence levels. The potential applications of this approach span diverse fields, including industrial and assistive robotics.