A Reconfigurable Robotic Fabrics Framework for Scalable Collective Behaviours of Robot Swarms

Modular reconfigurable robotics is advancing the development of intelligent autonomous systems. Robotic fabrics are emerging systems from this field that have shown great potential in morphing their shapes dynamically to suit many environments and to perform difficult tasks. These fabrics are formed by mechanically coupling modules of swarm robots to create different configurations. Specifically, this work focuses on the development of robotic fabrics for planar (2D) motion. Despite their numerous capabilities, existing robotic fabrics are mostly not modular, cannot self-propel, and are often limited in scalability and reconfigurability. In this thesis, a novel framework for producing deformable, scalable, and easily reconfigurable robotic fabrics using self-propelling Kilobot modules is proposed, realized, and implemented for different applications. The framework is made up of rigid holding rings and deformable links. Based on the geometry, the deformable links are of two types: spring-based and rod-based. These components of the fabrics, which were realized through advanced additive manufacturing, support fabrics of arbitrary size and shape, and enable easy plug-and-play reconfiguration. An open-loop and a deformation-correcting controller were first implemented on four robotic fabrics configured with the two deformable links. The results demonstrated that spring-based fabrics achieved improved coordination under the deformation-correcting controller, while rod-based fabrics performed more effectively with open-loop control. This was attributed to their lower elasticity. A probabilistic controller was derived and implemented on 7 × 7 configurations. The robotic fabrics successfully turned left and right at the four specified rotation radii. They were also used to demonstrate manipulation capabilities. Finally, robotic fabrics were utilized to implement four random walk strategies for fabrics of different sizes, with up to 100 physically linked modules. Self-propelling robotic fabrics based on distributed, embodied intelligence could pave the way for novel applications, from search and rescue operations to medical uses within the human body.