Pattern formation algorithms for swarms of robots can find applications in many fields from surveillance and monitoring to rescue missions in post-disaster scenarios. Complex formation configurations can be of interest to be the central element in an exhibition or maximize surface coverage for surveillance of a specific area. Existing algorithms that enable complex configurations usually require a centralized control, a communication protocol among the swarm in order to achieve consensus, or predefined instructions for individual agents. Nonetheless, trivial shapes such as flocks can be accomplished with low sensing and interaction requirements. We propose a pattern formation algorithm that enables a variety of shape configurations with a distributed, communication-free and index-free implementation with collision avoidance. Our algorithm is based on a formation definition that does not require indexing of the agents. We show the potential of the algorithm by simulating the formation of non-trivial shapes such as a wedge and a T-shaped configuration. We compare the performance of the algorithm for single and double integrator models for the dynamics of the agents. Finally, we run a preliminary test of our algorithm by implementing it with a group of small cars equipped with a Lidar for sensing and orientation calculation. (C) 2019 The Authors. Published by Elsevier B.V.