SFT 2026-27 - Lunar Base Micrometeorite Inspection Robot(s)
SFT 2026-27 - Lunar Base Micrometeorite Inspection Robot(s)
NASA Reference Name: GLENN-P5-METEOR-2026
Executive Summary
Design, build, and program a robotic system that inspects a lunar base for micrometeorite impacts and structural damage. On a regular basis, and after each impact event, the robot(s) autonomously (or partially autonomously) survey the habitat, landing pad, and surrounding surfaces to detect and analyze damage — without hitting people or vehicles. Objective: inspect a 1-km-radius base (including a 500 m landing pad located 1 km from center) and survey all buildings. Deliverables span a software/AI & VR track (VR/GUI control interface, an AI computer-vision pipeline with code and docs, a digital habitat model, a longitudinal report, and a presentation) and a physical track (a physical rover, a habitat model with impact holes, and sensor integration).
Requested By
NASA Glenn Research Center (GRC) - NASA HUNCH. Ideated by: Nancy R. Hall (GRC-MSI0), GRC HUNCH & XMIPT Project Manager. Author: Michael Hayes - NASA HUNCH.
Problem Statement
With no atmosphere to burn up debris, micrometeorites strike lunar habitats at ~20 km/s — risking cracks, slow leaks, loss of pressure, and astronaut safety. On a regular basis, and after each impact event, the robot(s) must autonomously inspect the lunar base to identify and analyze damage to structures, the landing pad, and surrounding surfaces.
Requirements Overview
Inspect >=110% of the base surface, including habitat and landing pad (SYS-001)
Autonomous plus remote-controlled operation (SYS-002)
Real / near-real-time data, latency <2 s (SYS-003, HW-007)
Modular sensors: RGB >=1080p, IR, LiDAR (HW-002)
Detect pits >=0.1 mm diameter; measure depth to 0.05 mm (HW-003)
Traverse flat, curved, and vertical surfaces to 90 degrees (ME-003/005/006)
AI detects and classifies impacts vs. a baseline (SW-003)
Assess severity and decompression risk (SW-005); VR/GUI control (SW-001); battery >=120 min (HW-005)
Major Constraints
Lunar environment: ~1/6 g with simulated lunar lighting (deep shadows and dark areas), with large temperature variation across a day and when crossing shadows; regolith covers most areas and some building surfaces (for radiation control)
Curved and vertical habitat surfaces demand reliable adhesion
Must detect very small impacts — pits as small as 0.1 mm in diameter
Telemetry and control over a 2-km inspection area with <2 s latency
Key Challenges
Telling a brand-new impact apart from normal surface features
Keeping adhesion while climbing curved and vertical surfaces (sides and roof)
Measuring hole length, width, and depth accurately in 3D
Estimating decompression risk from detected damage
Reliable low-latency streaming plus rover localization across a 2-km area
Missions
## Basic Operations — Missions 1–6
**Mission 1 — Lunar Inspection Patrol**
The robot must travel a predetermined route around a scale lunar habitat, stop at designated inspection points, and safely return to its starting location. Students must demonstrate autonomous or remote-controlled navigation without striking the habitat, equipment, astronauts, or simulated lunar vehicles, reflecting the project's requirement for autonomous plus remote operation. ([nasahunch.com][1])
**Mission 2 — Find the Micrometeorite Impacts**
Place four clearly visible simulated impact holes on the habitat, and challenge the robot to locate each using a camera or another student-selected sensor. The system must photograph each impact, record its location, and mark it on a digital habitat map; HUNCH suggests physical test holes of **1, 5, 10, and 20 mm** for high-school demonstrations. ([nasahunch.com][1])
**Mission 3 — Measure the Damage**
Finding the impact is no longer sufficient: the robot must estimate the **length, width, and depth** of each simulated crater using cameras, LiDAR, structured light, stereo vision, or another measurement technique. Students must demonstrate repeatable measurements and automatically associate those measurements with the correct damage location. ([nasahunch.com][1])
**Mission 4 — New Damage or Old Damage?**
The robot first performs a baseline inspection of the habitat and stores images and locations of existing surface features; afterward, several new impacts are secretly introduced. During its second inspection, the software must compare current observations with the baseline and identify **NEW DAMAGE** while ignoring previously documented impacts, seams, bolts, scratches, and other unchanged features. ([nasahunch.com][1])
**Mission 5 — Into the Lunar Shadows**
Hide impacts in brightly illuminated, partially shadowed, and very dark sections of the habitat, forcing the inspection system to operate under dramatically different lighting conditions. The robot must automatically compensate using onboard illumination, exposure control, IR, image processing, or another technique and successfully identify damage despite the simulated lunar lighting environment. ([nasahunch.com][1])
**Mission 6 — Full Habitat Inspection**
The robot receives a complete inspection assignment and must determine a route that examines the habitat while tracking inspected and uninspected areas. At completion, it must generate a **Lunar Habitat Inspection Report** containing its route, inspection coverage, detected impacts, images, measurements, timestamps, and any areas it could not inspect—progressing toward HUNCH's ≥110% surface-inspection objective. ([nasahunch.com][1])
# Innovative / Out-of-the-Box Missions — Missions 7–14
**Mission 7 — Climb the Habitat**
Impacts are moved from easily accessible surfaces onto curved walls, steep inclines, vertical surfaces, and eventually the habitat roof. Students must develop a climbing, tethered, articulated, adhesive, magnetic-simulation, robotic-arm, deployable-camera, or other innovative inspection method capable of examining surfaces approaching **90 degrees**, one of the project's explicit mechanical challenges. ([nasahunch.com][1])
**Mission 8 — AI Micrometeorite Detective**
Cover the habitat with decoys—including bolts, seams, scratches, dust, shadows, dents, labels, and old impacts—and require the robot to determine which observations are likely new micrometeorite damage. The AI must classify each finding, provide a confidence level, and explain what evidence caused it to flag the feature for further inspection, extending HUNCH's AI baseline-comparison requirement. ([nasahunch.com][1])
**Mission 9 — Which Impact Is the Emergency?**
Give the system multiple impacts with different dimensions and locations, but allow enough time to investigate only some of them immediately. The software must use damage size, depth, location, confidence, and other student-defined engineering factors to assign **LOW, MEDIUM, HIGH, or CRITICAL** inspection priority and identify potential decompression hazards for human review. ([nasahunch.com][1])
**Mission 10 — Swarm Inspection Team**
Instead of one inspection robot, students deploy two or more robots that must divide the habitat into inspection zones and collaboratively complete the survey without duplicating unnecessary work or colliding with one another. If one robot becomes unavailable, the remaining robots must automatically redistribute its unfinished inspection areas and continue the mission.
**Mission 11 — VR Mission Control**
Create a virtual-reality or immersive 3D Mission Control environment in which an operator can see the robot's position, camera imagery, telemetry, detected impacts, and inspection coverage mapped onto a digital lunar habitat. Advanced teams could allow the operator to take temporary control through VR and incorporate simulated haptic feedback when the robot encounters difficult terrain or structural damage, building on HUNCH's VR teleoperation innovation concept. ([nasahunch.com][1])
**Mission 12 — The Habitat That Remembers Every Impact**
Build a **digital twin** containing every inspection performed over simulated months or years, allowing the AI to compare today's habitat against its entire inspection history. The system must identify new impacts, determine whether previously discovered damage has changed, visualize the evolution of the habitat surface, and identify locations experiencing unusual concentrations of damage—extending HUNCH's proposed longitudinal Research Mode. ([nasahunch.com][1])
**Mission 13 — Predict Where the Next Problem Will Be**
Using historical inspection records, simulated impact events, habitat geometry, surface orientation, landing operations, and other student-selected variables, the system must identify areas that deserve increased inspection attention. The robot then autonomously changes its normal inspection route to spend more time examining these areas, creating a **risk-based inspection strategy** rather than treating every square meter identically.
**Mission 14 — Meteor Storm: Save the Lunar Base**
Without warning, simulate a micrometeorite event that creates multiple new impacts across habitats, equipment, and the landing area while some routes are blocked by astronauts or vehicles; the system must autonomously dispatch one or more robots, determine what should be inspected first, detect and measure new damage, compare it against the digital twin, and rapidly escalate potentially dangerous findings. Mission Control must receive a final **Emergency Lunar Base Damage Report** showing robot routes, inspection coverage, before/after imagery, 3D damage measurements, AI confidence, severity classifications, potential decompression concerns, and recommended inspection/repair priorities—demonstrating an integrated **robotics + sensors + autonomy + AI + digital-twin + human-interface** system.
[1]: https://nasahunch.com/projects/sft-2026-27-lunar-base-micrometeorite-inspection-robot-s--dh9lxq4ckk0oa6346rvvghm4 "SFT 2026-27 - Lunar Base Micrometeorite Inspection Robot(s)"
Please NOTE: All Robot Projects require a Tracking and Logging of the status of their robots I recommend you implement this input file, plus a ticketing system from Project 4. https://nasahunch.com/projects/sft-2026-27-additional-resource-hub-for-software-and-hardware-engineering-plus-robotics-hqao7leix1a9ux5ql75nif0g
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More Info below
1 — Examples of Excellence
The rover autonomously traverses the full habitat exterior (sides and roof) and finds every simulated impact hole
The AI correctly flags new impacts vs. the baseline with high confidence
The system measures hole size and depth and estimates decompression risk
Grounded in real NASA/ESA work: Perseverance (HazCams/Navcams), VIPER (10 cm feature detection), Astrobee, and ESA METERON teleoperation
3 — Examples of Innovation
VR teleoperation with optional haptic feedback (ESA METERON-inspired)
Deep-learning semantic segmentation for anomaly detection (NASA MMOD analogues)
Longitudinal / time-series surface-degradation analysis (Research Mode)
Automatic severity ranking and prioritized impact reports
Digital-twin habitat for simulation before physical testing
Suggestions for High School Students
The software/AI track may design a virtual 3D habitat instead of a physical one (HAB-005)
A physical habitat model needs at least 4 holes of different sizes — 1, 5, 10, and 20 mm (HAB-002) for testing
An Earth-scale classroom/lab demo is acceptable; lunar gravity can be modeled conceptually
The AI may be rule / threshold-based for beginner teams; use ML for advanced teams
Robots can do the survey, while a local processor handles visualization and detection