Insects inspire swarm of search and rescue drones

Liverpool University Professor Karl Tuyls is part a group whose new work is claimed to represent a significant step forward in the field of swarm robotics. Their findings are published in Science Robotics.

Swarms of flying robots could transform disaster search and rescue missions as their small size allows them to move in narrow spaces, and their light weight makes them safe to operate around people. According to Liverpool University, this task has so far been out of reach due to the lack of adequate navigation strategies.

Artificial evolution teaches robots to swarm in the wild

Smarticle robots built from smaller swarming robots

Now, researchers from TU Delft and Radboud University in the Netherlands and Liverpool University have presented their so-called ‘swarm bug algorithm’ that allows a swarm of tiny flying robots to autonomously explore unknown environments and return to the departure point.

As part of the project, researchers equipped 30g commercial drones with cameras and sent them out in an indoor office environment to find two dummies representing victims in a disaster scenario. Within six minutes, a swarm of six drones explored around 80 per cent of the open rooms – which would be impossible for one of the drones alone. Swarming also turned out be useful for redundancy; one drone found a victim, but due to a hardware failure of the camera, it could not return any images, an anomaly rectified by another drone fitted with a camera.

The drones detected and avoided each other by carrying a wireless communication chip and then making use of the signal strength between these chips. The drones were limited in terms of sensing and computation, so a major challenge was making the drones navigate an unknown environment by themselves. The team tackled this by drawing inspiration from the relative simplicity of insect navigation when developing their new ‘bug algorithm’.

According to Liverpool University, insects retain landmarks and behaviorally relevant places like food sources and their nest. “The main idea underlying the new navigation method is to reduce our navigation expectations to the extreme: we only require the robots to be able to navigate back to the base station”, said Guido de Croon, principal investigator of the project. “The swarm of robots first spreads out into the environment by having each robot follow a different preferred direction. After exploring, the robots return to a wireless beacon located at the base station.”

“The proposed navigation method is a novel type of bug algorithm”, said PhD student Kimberly McGuire, who carried out the project work. “Bug algorithms do not make maps of the environment but deal with obstacles on the fly. In principle, detailed maps are very convenient, because they allow a robot to navigate from any point in the map to any other point, along an optimal path. However, the costs of making such a map on tiny robots is prohibitive. The proposed bug algorithm leads to less efficient paths but has the merit that it can even be implemented on tiny robots.”

The project was financed by the Dutch national science foundation NWO Natural Artificial Intelligence programme.