Temple Tunnel Rover
Our wooden rover uses camera-based observation and mapping to explore tight, fragile spaces and support VR experiences.
Identify — core problems
Quick summary and visual evidence from our early research, site visits, and reading.
Quick takeaways
- We studied preservation methods at the MET.
- We watched excavation documentaries to spot real‑world risks.
- We voted to focus on the highest‑impact safety problem.
Research photos
Two visuals that summarize our early research.
Research themes brainstormed
Main challenges we compared.
Final focus after voting
Expert interview summary - Grace Howe
We are presenting: Field challenges + key site
Visuals to support the Identify + Research story: risky environments and the Temple of the Feathered Serpent.
Problem statement
Archaeologists must explore fragile, narrow temple tunnels and caves, but human entry is unsafe and can damage artifacts. Existing tools are too large or disruptive, so a compact, low‑impact rover is needed to safely map and document these spaces.
We are presenting: Design timeline
A vertical timeline showing how each person contributed to the process.
We are presenting: Goals tracker
A simple spreadsheet-style view of who owned each goal.
| Owner | Goal | Deadline | Status | Evidence | Next step |
|---|---|---|---|---|---|
| Owen | Cardboard mock sizing, wheelbase, and component placement | 09/14/2025 | Complete | Cardboard models photo; tunnel clearance check | Compare against LEGO chassis size |
| Owen | Component layout map (motors, hub, sensors) | 09/21/2025 | Complete | Placement sketch + photos | Confirm cable routing paths |
| First‑year FLL participant | LEGO drivetrain assembly + stability baseline | 09/28/2025 | Complete | LEGO prototype photos; short movement trial | Adjust bumper height and wheel clearance |
| First‑year FLL participant | Rebuild for tighter turning radius | 10/05/2025 | Complete | Photo + notes on turning test | Share changes with CAD team |
| Isabella | CAD: tread design + mounting brackets | 10/12/2025 | Complete | Tinkercad screenshots; print preview | Print test piece for fit |
| Isabella | CAD: protective plate + sensor mount revisions | 10/26/2025 | Complete | Fit check photos; mounting notes | Finalize print settings |
| Jonathan | Programming: camera frame processing + obstacle logic | 11/09/2025 | Complete | Code screenshots; camera hallway test log | Tune low-light exposure and frame rate |
| Jonathan | Programming: map logging for VR pipeline | 11/23/2025 | Complete | Sample map exports + test run | Integrate export format with VR viewer |
| Team | Testing: terrain traction + tread durability | 12/07/2025 | In progress | Rover test GIFs + wear notes | Adjust tread thickness |
| Team | Testing: camera mapping + blind-spot checks | 12/21/2025 | Complete | Camera mapping runs + blind-spot test notes | Improve capture quality in dark tunnels |
| Team | Presentation: storyboard + demo script | 01/05/2026 | Planned | Slides outline + demo checklist | Add timing and transitions |
| Team | Judging practice + final polish | 01/19/2026 | Planned | Q&A list + rehearsal notes | Run full demo rehearsal |
Research — what we compared
A quick look at common inspection tools and why they fall short in fragile, narrow tunnels.
Human exploration
Archaeologists enter with protective gear and lights to study artifacts up close.
- Pros: Direct observation and detailed study.
- Cons: Tight spaces, poor air, unstable tunnels; human movement can damage fragile walls/artifacts.
Large robots & scanners
Large robotic platforms and scanning machines collect data without direct human entry.
- Pros: Helpful scans and measurements.
- Cons: Often too big for narrow tunnels, hard to transport to remote sites, and vibrations can damage fragile areas.
Underwater archaeology robots
Specialized robots used underwater (like the one Grace Howe shared).
- Pros: Improves safety compared to human entry.
- Cons: Expensive, complex, and built for underwater environments — not tight, fragile tunnels or caves.
We are presenting: Key gap we found
Current solutions either put people at risk or use large, expensive tools that don’t fit narrow, fragile tunnels — leaving a clear gap for a small, low‑impact rover.
We are presenting: Clear targets before we designed
These were the outcomes we aimed for to guide planning and brainstorming.
We are presenting: Project goals infographic
These goals set our direction before planning and brainstorming.
We are presenting: Why VR matters
VR lets people explore ancient spaces from the rover’s perspective — without traveling, without entering danger, and without risking damage.
We are presenting: Design — planning the rover
We used IDEO’s 7 rules to brainstorm, sketch, compare tradeoffs, and organize responsibilities.
We are presenting: IDEO brainstorming rules
We are presenting: Sketches collage
We are presenting: Create, iterate, communicate
Timeline of builds, feedback, and upgrades.
We are presenting: Build timeline
With a plan in place, we moved into the create phase and began building multiple versions of our rover. Our first model was made from cardboard so we could quickly visualize the size, layout, and placement of components before building with LEGO. After that, we built fully LEGO-based prototypes to test movement, stability, motor placement, structure, and cable management.
We reached out to science and technology teachers for feedback. They noted SPIKE Prime wheels struggle on uneven terrain. We researched treads, designed custom ones in Tinkercad, and 3D‑printed them. We also designed a protective plate to shield the treads in rough environments.
After creating our 3D‑printed parts, we reached out to Grace Howe again. She stressed reducing blind spots and capturing what archaeologists actually need to see. We first tested multiple distance sensors, then developed camera-based observation and mapping logic. Our rover now maps with camera data, so we no longer rely on distance sensors as the primary mapping method.
We added a new full iteration cycle by building a wooden rover version, then refining camera mapping logic on that platform. This helped us test durability and mapping quality together in one workflow, instead of treating hardware and programming as separate steps.
We are presenting: Programming — camera observation + mapping logic
We tested multiple approaches and now use camera observations to map surroundings in tight spaces with better context.
We are presenting: Programming highlights
- Camera-first logic: observe surroundings, classify open space/obstacles, then move
- Distance sensors are now used only for early calibration checks
- We log camera observations and map updates for debugging and VR prep
These visuals show our early baseline before we shifted to camera-based mapping.
We are presenting: Current status + next improvements
We completed a wooden rover version and camera-based mapping logic. Next we are improving low-light capture and turning map output into smoother VR walkthroughs.
We are presenting: Completed upgrades + next steps
- Completed: moved to a wooden rover build for stronger protection in rough environments
- Completed: developed camera logic to observe surroundings and map without relying on distance sensors
- Next: improve low-light camera performance and stabilize map output for VR scenes
We are presenting: Why these updates matter
Our wooden rover increases durability while staying light. Camera-based mapping captures richer visual context than simple distance readings, and VR helps archaeologists and museums share discoveries safely.
Future Visuals
A preview of our next-phase builds — precision laser-cut wood paneling and immersive VR archaeology walkthroughs powered by our camera mapping logic.
We are presenting: Closing summary
This project protects people and history. We now have a wooden rover and camera-based mapping logic, and we are continuing to improve map quality for immersive VR exploration.