Digital Engineering Journal

We used multiple renders to inspect the robot from the top, front, sides, and attachment angles. Click any thumbnail to enlarge.

The gallery helps judges see both the finished model and the design thinking behind the build.

Straight Line PID Testing

We tested different Kp and Kd values to see how our robot drives on a straight line.

Experiment, test, improve! Small changes in Kp and Kd make a big difference in how our robot drives.

def drive_straight(distance_mm, speed, kp=1.15, kd=0.02):
  robot.reset_gyro()
  robot.reset_encoders()
  
  while robot.get_distance() < distance_mm:
      error = robot.get_heading()
      correction = (kp * error) + (kd * (error - prev_error))
      left_power = speed - correction
      right_power = speed + correction
      
      robot.set_motors(left_power, right_power)
      prev_error = error
  
  robot.stop()

def turn(degrees, speed, kp=1.0):
  robot.reset_gyro()
  
  while abs(robot.get_heading()) < abs(degrees):
      error = degrees - robot.get_heading()
      power = kp * error
      
      robot.set_motors(power, -power)
  
  robot.stop()

Our drive-straight code uses PID-style corrections with optimized values: Kp=1.15 and Kd=0.02. These values emerged from systematic testing across different speeds and distances.

The result is repeatable and reliable performance, even under varying loads and battery levels. We also manage our code using GitHub for collaboration and version control.

Helping archaeologists explore caves more safely

Our Innovation Project began during a field trip to the Museum of Natural History, where we learned about archaeology and became fascinated by caves. Curious about the challenges archaeologists face when exploring these environments, we chose Cave Safety as the focus of our project.

Research

Using Google Scholar and other reliable sources, we researched the challenges archaeologists face when exploring caves. We learned that caves can be dangerous due to low oxygen levels, unstable rock formations, flooding risks, and narrow passages. While technologies such as drones and gas detectors already exist, our research showed that many current solutions are too large, too heavy, too expensive, or designed to solve only a single problem.

Initial Idea

When we first started designing, we knew we wanted to build something that could travel into caves and do more than one job. Our first sketches included lots of exciting ideas, such as digging tools, cameras, sensors, and even a robot that could both drive and fly! We explored many different concepts and imagined how a rover and drone could work together as a team to help archaeologists explore hard-to-reach areas. During this ideation phase, we focused on generating as many creative ideas as possible before deciding which features would be the most useful and practical.

Expert Feedback

• Adam Niesley told us caves are wet and tools need to be waterproof.
• Margaret J. Furtner said tools should be portable and connect to phones.
• Judges encouraged us to focus on the most dangerous cave conditions and explain impact clearly.

Iteration

After gathering feedback from experts and learning more about the real challenges archaeologists face, we decided to improve our design. We removed many of the extra tools and features that were not directly related to cave safety and focused on the sensors that could help identify dangerous conditions. We redesigned the system to be smaller, lighter, and easier to transport through tight cave passages and rough terrain.

We also wanted our solution to be affordable and practical so that archaeologists and research teams could use it in real-world fieldwork without needing expensive or specialized equipment. By simplifying our design and focusing on the most important safety needs, we created a solution that is more effective, portable, and realistic to use in the field.

Tidal Scout Rover (Gen 1 Prototype)

Our first-generation Tidal Cave Scout Rover was designed to help archaeologists assess cave conditions before entering potentially dangerous environments. We wanted to create a compact, lightweight, and affordable solution that could travel into caves and gather important safety information. To keep costs low while still building a capable rover, we used Thunder3D, a 3D-printed robotic platform that gave us a strong foundation for our design.

The rover was equipped with four key sensors that monitor some of the most common cave hazards. An air quality sensor checks for unsafe conditions, a distance sensor helps detect obstacles and narrow passages, a vibration sensor can identify unstable surfaces, and a temperature and humidity sensor monitors environmental conditions inside the cave. Together, these sensors help answer one critical question: Is it safe for archaeologists to enter the cave? By collecting this information before people enter, our rover can help reduce risk and improve safety.

To bring our rover to life, we used a Pimoroni Pico Plus 2 W microcontroller as the brain of the system. An OLED screen displays sensor readings in real time, allowing users to quickly understand cave conditions. We also used a STEMMA hub and custom soldering to connect all of the components efficiently while keeping the rover lightweight and easy to transport. Building this first-generation prototype taught us valuable lessons about electronics, programming, sensor integration, and designing technology for real-world challenges.

Feedback Round 2

We did not stop after our first redesign. We shared our updated Tidal Cave Scout with archaeologists, subject matter experts, and FLL judges to gather even more feedback. Their suggestions helped us understand what would make the rover more useful in real-world cave exploration. They encouraged us to focus on making the rover easier to operate, lighter to carry through difficult terrain, and more capable of navigating the uneven surfaces commonly found in caves.

Using this feedback, we made several important improvements. We upgraded the tracks to provide better grip on rough cave surfaces, reduced the overall weight to improve portability, and developed a phone-based interface that allows archaeologists to control the rover and view sensor data directly from their smartphones. These enhancements made the Tidal Cave Scout more practical, user-friendly, and better suited for real-world fieldwork.

Tidal Scout Rover (Gen 2 Prototype)

To make the Tidal Cave Scout even more effective, we continued improving both the hardware and technology inside the rover. We reduced the rover's weight by switching to PLA Aero filament, a lightweight 3D-printing material that made the rover easier to carry and more energy efficient. We also added a UPS battery system to provide a more reliable power supply, helping the rover operate longer and reducing the risk of unexpected shutdowns during cave exploration.

At the same time, we upgraded several of the rover's key components. We improved the sensors to provide more accurate environmental data, added a night vision camera to help navigate dark cave environments, and upgraded the onboard computer to a Raspberry Pi 4. This gave the rover more processing power, allowing it to collect, analyze, and display information more efficiently while supporting additional features and future upgrades. We also learned how a 28BYJ-48 stepper motor can work with a ULN2003 motor driver and Raspberry Pi. Stepper motors move in small, controlled steps, making them ideal for precise robot functions such as rotating cameras, moving gears, or positioning sensors. The ULN2003 driver allows the Raspberry Pi to control the motor through four input signals, while a dedicated motor power supply helps make the system safer, more stable, and more reliable.

To make the rover easier for archaeologists to use in the field, we added wireless connectivity through a portable router. This allows the Tidal Cave Scout to connect directly to a smartphone, giving users access to live camera footage, sensor readings, and rover controls from almost anywhere near the exploration site. Together, these improvements transformed the rover from a basic prototype into a smarter, more capable, and more reliable tool for real-world cave exploration.

Stepper Motor Engineering Notes

• The ULN2003 driver has four main control inputs: IN1, IN2, IN3, and IN4.
• The Raspberry Pi activates the inputs in a sequence of small steps. Reversing the sequence changes the motor's direction.
• The tutorial maps Raspberry Pi GPIO pins 14, 15, 18, and 23 to the four driver inputs.
• A Python control function can set both direction and speed, making the motor easier to test and tune.
• Because motors draw significant current, the tutorial recommends powering the motor through the driver with an external power supply instead of relying on the Raspberry Pi for extended use.

Source: 28BYJ-48 stepper motor with Raspberry Pi and ULN2003 tutorial.

Custom PCB Engineering Notes

To make our rover smaller, cleaner, and more reliable, we designed and built our own custom PCB. We started by testing our ideas on a breadboard and creating a working circuit. Our first manufacturing approach was to use a UV printer to transfer the PCB design onto a copper board and then use ferric chloride to etch away the unwanted copper. While the PCB looked great, we had difficulty cutting and finishing the board accurately. After learning from this challenge, we switched to a CNC carving method, which allowed us to precisely carve the copper traces and drill the holes. We then carefully soldered all the components onto the board. The finished PCB reduced wiring clutter, saved space inside the rover, created stronger connections, and transformed our prototype into a more reliable system for real-world cave exploration.

Tidal Engineers reflects a complete rookie-season design cycle: identifying problems, brainstorming, testing, and iterating. By combining friendship, swim-team discipline, mechanical design, programming, and teamwork, we are building a robot story that is reliable, efficient, and repeatable.

This process helped us qualify at John Jay Middle School, earn 3rd place and the Best Innovation Award at the Hudson Valley Regional Championship, and grow from four rookies into one amazing team.

Now we are preparing for the American Robotics Invitational on June 6-7, 2026, where we will represent the New York State area and keep building on the same cycle of testing, learning, improving, and having fun.