By understanding how social insects work together to find and transport food, researchers at Adelaide University applied those same ideas to teams of small robots. The robots work together without needing a single control center, allowing them to respond more effectively to changing conditions.
Mining is becoming more challenging as companies move into deeper, more remote and harder-to-access locations. While automation improved safety and productivity, quite a few existing systems are expensive, inflexible and can be vulnerable if a central control system fails.
Using small Zumo 2040 robots in a laboratory set-up designed to mimic a mine, the researchers tested three different approaches:
- A basic system where robots collect ore and immediately return
- An ant-inspired system where robots share tasks
- A honeybee-inspired system where robots first explore and map an area before collecting resources more efficiently
Robots Swarm
Instead of relying on one central controller, the robots operate as a swarm, making their own decisions while working together. Moreover, this allows the system to keep operating even if individual robots stop working.
This study shows the value of learning from nature, said lead author Dr. Joven Tan. He conducted the research as part of his PhD at the School of Chemical Engineering.
“Social insects have developed very efficient ways of solving problems together,” Tan said. “By applying these ideas to robotics, we can create systems that are more efficient, adaptable and reliable for industries such as mining.”
An AI generated image demonstrating the value of social insects like honeybees can help solve operational challenges in the mining industry.
Source: Adelaide University
The results were striking, with the honeybee-inspired approach performing best in all tests. By first exploring the area and remembering the location of resources, it:
- Reduced travel distance by up to 80 percent
- Reduced energy use by about 50 percent
- Completed ore delivery tasks up to 60 percent faster than the basic approach
The ant-inspired approach also improved performance by dividing the work between robots. One robot would find resources while another transported them.
The research was not limited to computer simulations. The team tested the approaches using real robots in a laboratory environment that replicated mining operations, demonstrating the concepts can work in practice.
“Nature has spent millions of years developing efficient ways for groups to work together,” said Project leader and co-author Dr. Noune Melkoumian from the School of Chemical Engineering. “By learning from these systems, we can develop new technologies that are more flexible, reliable and efficient.”
Challenges Remain
There are still challenges to overcome before the technology can end up used in mines, including improving sensors, extending battery life and adapting to unpredictable underground conditions, the researchers said.
Despite these challenges, the potential applications are significant.
“Swarm robotic systems could end up used in dangerous or difficult-to-reach mining areas, reducing risks for workers while improving productivity,” Melkoumian said.
“They could also play an important role in future space mining missions, where fully autonomous systems will be essential,” Melkoumian said. “Our research shows that swarm robotics is no longer just a theoretical idea. These systems can be built, tested and operated in real environments, with the potential to change how resources are explored, excavated and transported.”
Click here to view the paper, entitled, “Bio-Inspired Swarm Robots Design for Mine Automation.”