To give a short summary of the original proposal, we must dive into the relationship between stimulus and impact over users. Specifically, robot physical and social characteristics have a distinct influence over user perception, being objectively measurable within a range of neuronal and psychological modalities. Considering there is a growing adoption of robotics in our time, there is also a need to understand this influence and the polarized impact certain traits incur. By doing so, we are able to work towards greater machine acceptance, better working conditions, and consequential enhanced efficiency. Thus, CoDRI aims to associate robot activity and its attributes with observational and self-measurable psychological factors, as well as neural correlates detectable by non-invasive brain-computer interfaces (BCI). This way, we can explore how certain activations may serve as direct feedback for deep learning controlling machinery, in addition to correlating them with system ergonomics, to achieve more natural interactions. Ideally, this realizes improvements for both the industrial and social aspects of collaborative robotics.

Having clarified that, a full proposal was drafted and presented, to which the original grant was awarded and allowed us to formulate the team and start working on the topic. Naturally, this started with a first public dissemination opportunity, where Gustavo, the principal investigator, pitched CoDRI.