When our FIRST LEGO League team started researching fossil and artifact sorting, we quickly realized the process was much harder than we expected. To learn more, we interviewed Edgar Lobaton, a computer engineering professor from North Carolina State University who designs robotics and AI systems that sort microscopic fossils.
The Challenges of Sorting Fossils
During the interview, Dr. Lobaton explained why fossil sorting is so difficult. Fossils come in many different shapes and sizes, and many of them break easily. Dirt and debris can also cover fossils and make them harder to identify. He told us that scientists still sort many microfossils by hand under microscopes using tiny brushes. This process takes a long time and requires a lot of patience.
One of the most interesting things we learned was how hard it is to move objects that are so small. Dr. Lobaton explained that normal robotic grippers often damage the fossils. Static electricity can also make tiny fossils stick to surfaces, which creates even more challenges.
Building a Better Robot
To solve these problems, Dr. Lobaton’s team created a robotic system that uses suction to move the fossils carefully. The system also uses imaging towers with microscopes and LEDs to identify the fossils more accurately.
Dr. Lobaton also explained that his team tested many different ideas before finding a solution that worked well. They tried tweezers, shaking plates, and other tools before choosing suction. Even after they chose suction, they still faced problems like clogging and static electricity.
This interview taught our team an important lesson about robotics and engineering. Engineers do not usually find the perfect solution right away. Instead, they test ideas, fix problems, and improve their designs step by step.
Talking with a real-world expert helped us better understand the challenges engineers face when designing scientific robots. Most importantly, we learned that robotics is not just about making something work once. It is about building systems that work reliably and solve real-world problems.