Protein-Folding Inspired Programmable Control System for Robot Swarms

In swarm robotics, most of the control algorithms are inspired by the behaviors of animal swarms. The capability gap between robots and animals, however, hinders the reliability of these algorithms. Toward developing reliable algorithms of robot swarms, a promising solution is learning from the collective behaviors of low-intelligent natural swarms, such as cell collectives and molecular assemblies. Here, we proposed a programmable control system inspired by protein folding. Using our homemade RoboFold platform, we demonstrated a protein-folding inspired programmable control method for robot swarms. By programming and designing the sequence of a thread of protein-like robots, the developed system can mimic the formation of hierarchical structures in robot swarms as the three-level of protein structures. We quantitatively characterized the specific features of self-organized morphologies. The experimental results together demonstrated the feasibility of this method. To summarize, this work successfully translated the principles of protein-folding into programming methods to control the morphology of robot swarms. Considering that the protein folding problem is essentially a physicochemical problem, this system is not only beneficial for the control of swarm robots but also has the potential to develop into a tool for studying the protein folding problem.