Enabling Cognitive Robotics Through Autonomous Motion Planning and Model-Driven Intuitive Programming

This paper explores innovation in cognitive robotics to automate complex mission-critical processes. By autonomously generating its models of the surrounding environment, the system localizes its target, detects any obstacle, calculates cycle time optimization and collision-free path planning and makes decisions that intuitively refine its movements and actions. All this technical complexity is hidden behind a simple and effective user interface based on low-code programming. Comau and CNR have embedded AI-powered methodologies in an innovative model-driven intuitive programming framework, applied to a self-adaptive system that autonomously inspects helicopter blades measuring up to 7 m. The focus will be given to the system’s versatility while performing tapping tests and multispectral surface inspection along the helicopters’ blades.