Researchers at Adelaide University have developed a swarm robotics system inspired by the collective behaviour of bees and ants that could improve the safety, efficiency and adaptability of mining operations. The research, published in Natural Sciences, examines how social insects cooperate to locate and transport food and applies those principles to teams of small autonomous robots. Rather than relying on a central control system, the robots operate as a decentralized swarm, enabling them to continue functioning even if individual units fail.
The study addresses challenges facing the mining industry as operations move into deeper, more remote and less accessible locations. Although automation has increased safety and productivity, many existing systems depend on centralized control, which can reduce flexibility and create single points of failure.
Using Zumo 2040 robots in a laboratory environment designed to replicate mining conditions, the researchers evaluated three approaches: a baseline system in which robots collected ore and immediately returned, an ant-inspired system that divided tasks between robots, and a honeybee-inspired system in which robots first explored and mapped the environment before collecting resources.
The honeybee-inspired approach achieved the strongest performance. According to the researchers, it reduced travel distance by up to 80%, lowered energy consumption by approximately 50%, and completed ore transport tasks up to 60% faster than the baseline system by allowing robots to identify and remember resource locations before collection began. The ant-inspired approach also improved performance by assigning different roles to individual robots, with one robot locating resources while another transported them.
Lead author Dr Joven Tan, who conducted the research as part of a PhD at the University’s School of Chemical Engineering, said social insects demonstrate effective methods of collective problem-solving that can be applied to robotics. The researchers tested the systems using physical robots rather than relying solely on computer simulations, demonstrating that the swarm-based approaches could operate in a laboratory environment representative of mining operations. Co-author and project leader Dr Noune Melkoumian said the findings illustrate how biological systems can inform the development of practical engineering solutions.
The researchers noted that further work is required before the technology can be deployed in commercial mines, including improvements to sensors, battery life and the ability to operate in unpredictable underground environments. They added that swarm robotic systems could eventually be used in hazardous or inaccessible mining areas to reduce risks to workers and improve operational efficiency. The team also identified potential applications in future space mining missions, where autonomous robotic systems would be required for resource exploration and transport.
