This paper sets up a framework to assess co-agency in human-robot interactions, and applies it specifically to the socio-technical safety analysis of collaborative robots. We also examine to what extent the concept of Situation Awareness can be applied to assess collaborative robots as efficient team members in socio-technical systems. We explain some theoretical concerns with traditional concepts of Situation Awareness and defend why the concept of Joint Cognitive Systems, which maps the conceptualization of the cognitive system onto the work system as a whole, is best suited for issues of distributed cognition and controllability in human-robot interaction. Thereafter we present a five-step methodology specifically conceived for cobot applications serving the aim of goal coordination between multiple agents by functional interactions. The proposed framework merges two existing safety and resilience analysis methods, being the Functional Resonance Analysis Method and Interdependence Analysis. These methods are used in combination to assess shared control in safe and efficient human-robot interaction from a systems-thinking perspective. This allows to describe the systemic conditions for Distributed Situation Awareness in terms of observable system interactions and as an emergent object of distributed cognition. Instead of looking at undesirable safety outcomes, we have imposed the focus of co-agency as the unit of analysis in line with the Joint Cognitive Systems perspective. The theoretical insights from this paper are additionally applied to a hypothetical but credible demonstration case study with collaborative warehouse robots.

Despite their undisputed potential, the uptake of collaborative robots remains below expectations. Collaborative robots (cobots) are used differently from conventional industrial robots. The current safety focus of collaborative workspaces is predominantly on the technological design; additional factors also need to be considered to cope with the emerging risks associated with complex systems. Cobot technologies are characterized by an inherent tradeoff between safety and efficiency. They introduce new, emergent risks to organizations and can create psychosocial impacts on workers. This leads to a confusing body of information and an apparent contradiction about cobot safety. Combined with a lack of safety knowledge, this impedes the introduction of cobots. A multi-step methodology was used, including a literature review and conceptual modeling. This article argues for the need for a system-wide safety awareness readiness assessment in the consideration phase of cobot implementation to alleviate the knowledge deficit and confusion. This work will benefit both researchers and practitioners. In addition, it defends the appropriateness of a maturity grid model for a readiness assessment tool. The building blocks for an easy-to-use and practically applicable tool are proposed, as well as an agenda for the next steps.

Human Factors (HF) is the scientific discipline concerned with the understanding of interactions among human and other elements of a system with the aim to optimize system performance. One important concept within HF is Situation Awareness (SA). Since the early 1990s, the original models of individual SA have been complemented by additional models of shared and distributed SA. Although SA has already been the subject of investigation in many complex socio-technical systems, there is not a great body of scientific work on SA in relation to collaborative robots (cobots). This paper explains and reviews the most relevant models and evolutions in SA thinking and examines to which extent the concept of SA, and more particularly Distributed Situation Awareness (DSA), can be applied to cobots. Individual models of cobot SA to detect human presence and predict future human activity from a cobot-centered perspective are technologically feasible and are currently applied in industrial applications. We defend that the SA within the cobot has to be of a higher order than the level of the individual human or technological agent, and needs to be ‘set free’ in order to not only be shared with human team members, but also to understand how SA is distributed throughout the system as a whole. This paper proposes to inform future cobot design with DSA analysis from a socio-technical perspective.