Towards Peak Torque Minimization for Modular Self-Folding Robots

Modular self-folding robots are versatile systems that can change their own shape from two-dimensional patterns at instant commands. This reconfigurability is commonly restrained by power limitation in autonomous environments, The robotic systems with insufficient torque may lead to inaccurate movements and even transformation failures. This paper presents methodology for optimized reconfiguration planning with torque limitation in modular self-folding robots. We determine reconfiguration schemes with optimal initial pattern and robotic base that result in minimal peak torque by minimizing robotic inertia of the modular architecture. We present minimal bounding box and capacitated spanning tree heuristic algorithms to generate optimal initial patterns and propose 3 heuristic rules for robotic base selection. Our approach is demonstrated in simulation by applying the algorithms to the robotic concept of Mori, a modular origami robot. The simulation results show that the proposed algorithms yield reconfiguration schemes with low peak torque, thereby appropriate for real-time applications in modular robotic systems.