Human‐Robot Interaction: An Artificial Cognition‐Based Study for Criminal Investigations

The alliance between humans and robots is becoming increasingly significant in our community. Accordingly, there is a thriving interest in the evolution of models that can strengthen and improve the interactions between humans and robots. A critical challenge in the human-robot interaction (HRI) is to furnish robots with cognitive and affective skills, by evolving architectures that allow them to establish compassionate relationships with users. Over the last few years, many models were formulated to face this challenge. This paper contributes a survey of the different cognitive structures and a brief discussion on most relevant architectures. In fact, it proposes a synopsis of the architectures present in literature concentrating on three aspects of HRI: the evolution of adaptive/acquirable behavioral models, the structure of cognitive architectures, and the skill to establish empathy with the companion. While summarizing the current progress in the cognitive architecture exploration, this survey interprets various strategies and ideas that have earlier been attempted and the comparative accomplishment in modeling the human cognitive capacities, later section of the paper states which aspects of cognitive behavior still require more research and thus can further interpret how cognitive science can lead to advancements in fields like digital forensics. In the end, we have discussed about the role of social robots, equipped with cognitive skills to fight the COVID-19 pandemic.