State of the Art on Control Strategies for Aerial Modular Self-Reconfigurable Robots

Aerial vehicles are increasingly utilized across a wide range of application domains in which their primary functions often involve monitoring, inspection, and vision-based operations. This paper explores a novel and underexplored application area for aerial vehicles: the autonomous selection and deployment of modular and reconfigurable structures. Specifically, in the broader context of Modular Self-Reconfigurable Robots (MSRR), the study examines the state-of-the-art control techniques that enable aerial vehicles to autonomously select proper structures depending on the considered working environment and self-reconfigure in the selected one. These structures hold significant potential for addressing challenges in emergency and critical scenarios, such as storms, floods, earthquakes, and fires. In such situations, a fleet of aerial vehicles can be requested to rapidly reach critical areas to transport useful materials and then self-assembly into reconfigurable structures of practical use, such as footbridges or complex structure inside spaces with narrow entrance, or in general structures to help endangered people or support first responders in their search and rescue activities. The surveyed articles are classified by considering two major control problems, i.e., reconfiguration planning and control, and task-shape matching. A discussion is provided regarding, on the one hand, the well established control methods for MSRR and their adaptability to aerial MSRR (AMSRR), and on the other hand the advancements and challenges of current control algorithms for AMSRR, identifying open issues and future research paths.