Robotic systems are traditionally widespread in the efficient automatization of industrial processes. Recent applications include material handling, reconnaissance, and agricultural tasks, besides the more traditional assembly line tasks. On the other hand, the recent advancements of robotic systems aim at enhancing and even replacing the human workforce in traditional social service tasks, like nursery, clerk positions, eldercare, and catering – collectively called social robotics. Developed countries generally suffer from the decreased available workforce in these areas, threatening the long-term availability of such essential services. The robots providing such services are required to appear and behave human-like to some degree to interact with people seamlessly. Human-like behavior requires complex software and hardware systems with learning capabilities to solve social situations appropriately. This paper investigates the relationship between human-robot interactions and sustainability and identifies the foundational similarities between the aims of the two interdisciplinary fields. The paper proposes the effect of complex interaction capabilities on sustainable factors and their possible qualitative verification. The quantitative factors described in this paper are the social perception of different robots and their expected functions defined by the foundational human-robot interaction roles. The paper proposes the possible contribution of future social robot applications to sustainability factors, such as the effect of telepresence. The paper also presents the result of a qualitative survey of participating university students on the acceptance of different types of robots based on their visual appearance. The assumption of possible integration of robots into social roles and what appearance is perceived as acceptable. In summary, this paper highlights the sustainable factors in human-robot interactions by identifying the effects of social robot roles and mapping between corresponsive sustainability factors, most importantly resolving workforce deficit.