(de-)construction of computer-controlled behaviour with the robot operating system.

Robots and autonomous systems play an increasingly important role in modern societies. This role is expected to increase as the computational methods and capabilities advance. Robots and autonomous systems produce goal-directed and context-dependent behaviour with an aim to loosen the coupling between the machines and their operators. These systems are a domain of complex digital innovation that intertwines the physical and digital worlds with computer-controlled behaviour as robots and autonomous systems render their behaviour from the interaction with the surrounding environment. Complex product and system innovation literature maintains that designers are expected to have detailed knowledge of different components and their interactions. To the contrary, digital innovation literature holds that end-product agnostic components can be generatively combined from heterogeneous sources utilising standardised interfaces. An in-depth case study into the Robot Operating System (ROS) was conducted to explore the conceptual tension between the specificity of designs and distributedness of knowledge and control in the context of complex digital innovation. The thematic analysis of documentary evidence, field notes and interviews produced three contributions. First, the case description presents how ROS has evolved over the past ten years to a global open-source community that is widely used in the development of robots and autonomous systems. Second, a model that conceptualises robots and autonomous as contextually bound and embodied chains of transformation is proposed to describe the structural and functional dynamics of complex digital innovation. Third, the generative-integrative mode of development is proposed to characterise the process of innovation that begins from a generative combination of components and subsequently proceeds to the integration phase during which the system behaviour is experimented, observed and adjusted. As the initial combination builds upon underspecification and constructive ambiguity, the generative combination is gradually crafted into a more dependable composition through the iterative removal of semantic incongruences.