Robotics Students Win SICK $10K Challenge 2025 with Mine-Navigating Robot
Department of Computer Science & Engineering (CS&E) postdoctoral associate Ajay Kumar Gurumadaiah advised the University of Minnesota team that won the SICK $10K Challenge 2025. Robotics masters students Abhishek Chaudhari and Sujeendra Ramesh developed SICK-MINE-GUARD, an autonomous 4WD ground robot designed for hazardous underground mining environments. Equipped with the SICK multiScan100 LiDAR, the robot provides real-time 3D mapping, obstacle detection, and safety monitoring. The focus was to enhance safety and operational efficiency in mining through robotics and perception systems.
“Our students did a lot of research on projects from previous years to get ideas about the type of applications we could explore for our submission,” Ajay said. “We also looked into current trends and scientific problems in the U.S., which led us to the mining industry. Mining is an important field as we look to address future resources and supply critical minerals. There are certain processes that will need to be automated in the future. That’s the area that we looked to address with our project.”
SICK established its U.S. subsidiary in 1976 and is headquartered in Minneapolis. The company is the leading manufacturer of factory, logistics, and process automation technology worldwide, with more than 1,000 patents for its products. The SICK $10K Challenge selected 15 teams across the country to compete for the top prize by solving a problem, creating a solution, and bringing a new application that utilizes the SICK scanner in any industry.
The mining industry has always been demanding and hazardous, exposing workers to extreme conditions underground. Now, with a growing demand for earth materials intensifying and the U.S. federal government increasing investments in mining research, innovation is more critical than ever. Autonomous mining robots offer a game-changing solution—enhancing safety, efficiency, and sustainability by reducing human exposure to risks, optimizing resource extraction, and operating 24/7 without fatigue. Equipped with AI and advanced sensors, they boost productivity, minimize environmental impact, and address labor shortages through remote operation. As demand for critical minerals grows, embracing automation is essential for a safer, smarter, and more competitive mining industry.
The UMN team installed their robot with the LiDAR technology and worked with the Coldspring Mine, an open pit mine outside of St. Cloud, Minnesota, for their initial testing. They then went up to the Iron Range to test their robot in the Soudan Mine, which is 2,241 feet underground. The SICK-MINE-GUARD model focused on path planning, localization, and perception of the environment.
“When you are driving on a normal road, you need a GPS signal to know exactly where you are,” said Ajay. “When the robot is operating underground, it needs precise location information. We developed a specific location estimation system for the mine using the LiDAR sensors, which enables it to navigate the complex network of routes in a mine.”
“We also had safety metrics,” Chaudhari said. “So as the robot moves, it can give safety warnings about the environment. Our software processed the data from the LiDAR sensor and then we came up with the metrics to give proper safety warnings. Our work really centered around the safety and efficiency of the mining industry.”
The SICK-MINE-GUARD team was supported by the Minnesota Robotics Institute, Robo Robotics, and the Coldspring and Soudan Mines. They would especially li
“As an academic, we learn a lot by working with industry,” Ajay said. “It helps us understand the challenges so we can work on tools that address their specific needs. This was a great experience to develop those skills and make sure our world addresses real-world problems and applications.”
Learn more about the project by watching the SICK-MINE-GUARD video.