Hundreds of small robots can work in a team to create biology-inspired shapes without an underlying master plan, purely based on local communication and movement. To achieve this, the biological principles of self-organization were introduced to swarm robotics. The only information installed in the coin-sized robots was basic rules on how to interact with neighbors. The robots in the swarm were specifically programmed to act similarly to cells in a tissue. Those genetic rules mimic the system responsible for patterns seen in nature, like the arrangement of fingers on a hand or the spots on a leopard. The robots rely on infrared messaging to communicate with neighbors within a 10-centimeter range. This makes the robots similar to biological cells, as they can only directly communicate with other cells physically close to them.
The swarm forms various shapes by relocating robots from areas with low morphogen concentration to areas with high morphogen concentration, which leads to the growth of protrusions reaching out from the swarm. There is no master plan — the shapes emerge as a result of simple interactions between the robots.
At least 300 robots were used in most experiments. A special setup made it easy to start and stop experiments and reprogram all the robots at once using light. More than 20 experiments with large swarms were done, with each experiment taking around 3-1/2 hours.
The early part of the project was done in computer simulations, and it took the team about three years before the real robot swarm made its first shape. But the robots’ limitations also forced the team to devise robust mechanisms to orchestrate the swarm patterning. By taking inspiration from shape formation in biology, the team was able to show that the robot shapes could adapt to damage and self-repair. The large-scale shape formation of the swarm is far more reliable than each of the little robots, with the whole being greater than the sum of the parts.
While inspiration was taken from nature to grow the swarm shapes, the goal is ultimately to make large robot swarms for real-world applications. This includes hundreds or thousands of tiny robots growing shapes to explore a disaster environment after an earthquake or fire, or sculpting themselves into a dynamic 3D structure such as a temporary bridge that could automatically adjust its size and shape to fit any building or terrain.