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Video abstract for the article 'Collective motion dynamics of active solids and active crystals' by Eliseo Ferrante, Ali Emre Turgut, Marco Dorigo and Cristián Huepe (Eliseo Ferrante et al 2013 New J. Phys. 15 095011). Read the full article in New Journal http://iopscience.iop.org/1367-2630/15/9/095011. Part of Focus on Swarming in Biological and Related Systems GENERAL SCIENTIFIC SUMMARY Introduction and background. Collective motion (CM) is observed in various biological systems, from cell colonies to bird flocks. Most prevailing theories of CM are strongly influenced by the Vicsek model; an extension of the XY-model where self-propelled spins advance in their pointing directions, coupled through aligning interactions that depend only on relative heading angles. We study CM in systems with a very different type of interactions, introducing a simple active elastic sheet (AES) model where neighbouring agents interact through attraction--repulsion forces that depend only on relative positions. Main results. The AES model displays a discontinuous transition at a critical noise level, below which the group self-organizes into a collectively translating or rotating state. CM results here from a novel elasticity-based mechanism: the emergence and growth of regions of coherent motion due to the cascading of self-propulsion energy towards lower-energy elastic modes. We investigate the AES dynamics for different parameters, agent configurations and system sizes. We study the propagation of perturbations and heterogeneous systems. We derive analytical stability conditions for the translating state using a continuous elastic sheet approximation. Wider implications. Our work explores a new, simple and robust mechanism for CM that could be relevant in various biological systems and can be used to control robotic swarms. It introduces the simple idea that the selection of lower, more coherent elastic modes can lead to self-organization in active matter. Many natural systems likely combine alignment- and elasticity-based mechanisms. Our results suggest methods to determine experimentally, based only on collective dynamics, the role each one plays in specific systems.