New Team, Shining Result

Mentored by Ryan Zhang, Chrono Solvers celebrates winning the Robot Performance Award and Champion’s Award 2nd Place at the 2025 FLL regional tournament

Chrono Solvers made an impressive FLL debut, winning Robot Performance Award 1st Place and Champion’s Award 2nd Place. The new SolversMind team also created DecoScript, an AI Innovation Project that helps recognize and reconstruct damaged ancient scripts (Toronto Downsview Qualifying Tournament - Saturday, December 6, 2025).

By SolversMind Robotics
Published December 6, 2025 | Updated July 17, 2026
Reviewed by SolversMind Robotics mentors

It is time to talk about time travel.

Chrono Solvers, SolversMind Robotics’ newest FIRST LEGO League team, made an impressive debut during the 2025-2026 UNEARTHED season.

What did Chrono Solvers achieve in their first FLL season?

Chrono Solvers achieved a strong debut during the 2025-2026 FIRST LEGO League UNEARTHED season. At the Toronto Downsview Qualifying Tournament on December 6, 2025, the new SolversMind team earned Robot Performance Award, 1st Place, with the highest robot score, and Champion’s Award, 2nd Place. These results advanced the team to the Ontario Provincial Championship. Chrono Solvers also developed DecoScript, an artificial intelligence platform for preserving and interpreting damaged or incomplete ancient writing. As their FLL Innovation Project, students researched archaeology and epigraphy, interviewed experts, and combined computer vision with natural language processing. Their system recognizes ancient scripts and predicts missing characters or text using machine-learning models. The project explored Chinese, Persian, Greek, Latin, and Indian writing systems while connecting robotics education with cultural heritage. Chrono Solvers’ first season demonstrated technical independence, research ability, teamwork, and student leadership, while showing how young learners can use AI to address meaningful real-world problems.

Trophies won by Chrono Solvers in regional FLL tournament

How did Chrono Solvers build their robot?

Chrono Solvers worked independently on their robot design while seeking guidance from SolversMind’s experienced FRC youth mentors. Students tested attachments, refined their programs, analyzed robot performance, and learned from each unsuccessful attempt.

Their approach reflects SolversMind’s student-led robotics model. Mentors provide guidance and technical support, while students make decisions, explain their reasoning, and take ownership of the engineering process.

The team also looked to its sister team, FLL Team 52777 Solvers of X & Y, for inspiration while developing its own identity and technical confidence.

What is the DecoScript Innovation Project?

Chrono Solvers began with an important question:

How can technology help preserve the voices of ancient civilizations before they are lost forever?

Ancient scripts preserve stories about mathematics, astronomy, trade, government, religion, and everyday life. However, many inscriptions are damaged, incomplete, or written in languages with few or no living speakers. This makes them difficult to interpret and preserve.

To understand the challenge, the students researched archaeology and epigraphy and interviewed experts, including Professor Amir, who studies Middle Eastern inscriptions, and Professor Li, who explained how ancient writing preserves the collective memory of civilizations.

The students learned that artificial intelligence cannot replace archaeologists. However, it can support experts by helping organize evidence, recognize patterns, and accelerate research.

How does DecoScript use artificial intelligence?

Chrono Solvers designed DecoScript as an AI-assisted platform that combines computer vision and natural language processing.

The system is designed to:

  • Recognize ancient writing systems from images

  • Identify damaged or incomplete characters

  • Predict missing text using surrounding context

  • Help students and researchers explore cultural heritage

The students began with Google Teachable Machine to learn the fundamentals of image classification. They later studied AlexNet and ResNet convolutional neural networks to improve image recognition.

With guidance from mentors and computer-vision experts, the team used Roboflow to organize larger datasets and improve model training. They also integrated a BERT language model to help predict missing characters based on the context surrounding an inscription.

DecoScript supports several ancient writing systems, including Chinese, Persian, Greek, Latin, and Indian scripts.

Explore the project: DecoScript

What did Chrono Solvers learn?

Chrono Solvers’ first season showed that FLL can connect robotics, programming, research, artificial intelligence, history, and cultural preservation.

The students developed technical skills, but they also strengthened communication, teamwork, project management, critical thinking, and presentation skills. Their work demonstrates how young students can use emerging technology to investigate meaningful problems and create practical solutions.

Congratulations to Chrono Solvers on a remarkable first season. What a shining start!

Tags:

FIRST LEGO League, FIRST Core Values, LEGO Robotics, Teamwork, STEM Education, Student Leadership, Gracious Professionalism, SolversMind, Champion’s Award, DecoScript, Artificial Intelligence, Computer Vision, Ancient Scripts, Digital Archaeology, Cultural Heritage, Natural Language Processing

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