As robots are equipped with software that makes them increasingly autonomous, it becomes harder for humans to understand and control these robots. Human users should be able to understand and, to a certain amount, predict what the robot will do. The software that drives a robotic system is often very complex, hard to understand for human users, and there is only limited support for ensuring robotic systems are also intelligible. Adding intelligibility to the behavior of a robotic system improves the predictability, trust, safety, usability, and acceptance of such autonomous robotic systems. Applying intelligibility to the interface design can be challenging for developers and designers of robotic systems, as they are expert users in robot programming but not necessarily experts on interaction design. We propose Choreobot, an interactive, online, and visual dashboard to use with our reference framework to help identify where and when adding intelligibility to the interface design is required, desired, or optional. The reference framework and accompanying input cards allow developers and designers of robotic systems to specify a usage scenario as a set of actions and, for each action, capture the context data that is indispensable for revealing when feedforward is required. The Choreobot interactive dashboard generates a visualization that presents this data on a timeline for the sequence of actions that make up the usage scenario. A set of heuristics and rules are included that highlight where and when feedforward is desired. Based on these insights, the developers and designers can adjust the interactions to improve the interaction for the human users working with the robotic system.

Collaborative robot-assisted production has great potential for high variety low volume production lines. These type of production lines are common in both personal fabrication settings as well as in several types of flexible production lines. Moreover, many assembly tasks are in fact hard to complete by a single user or a single robot, and benefit greatly from a fluent collaboration between both. However, programming such systems is cumbersome, given the wide variation of tasks and the complexity of instructing a robot how it should move and operate in collaboration with a human user. In this paper we explore the case of collaborative assembly for personal fabrication. Based on a CAD model of the envisioned product, our software analyzes how this can be composed from a set of standardized pieces and suggests a series of collaborative assembly steps to complete the product. The proposed tool removes the need for the end-user to perform additional programming of the robot. We use a low-cost robot setup that is accessible and usable for typical personal fabrication activities in Fab Labs and Makerspaces. Participants in a first experimental study testified that our approach leads to a fluent collaborative assembly process. Based on this preliminary evaluation, we present next steps and potential implications.

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