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University of Arizona

SST footprint: 1 project (ML asteroid navigation) | TechPort footprint: 2 projects across 2 programs (SST, FO) under Dante Lauretta | Outcome: transitioned (algorithms for small-body proximity operations) | PI profile: OSIRIS-REx Principal Investigator ($800M+ flagship asteroid sample return)

Last updated: 2026-04-14 (session 19)

The Story

Dante Lauretta is the most prominent individual PI in the SST portfolio — he is the Principal Investigator of OSIRIS-REx, NASA's first asteroid sample return mission ($800M+, sample returned September 2023). But the causal direction is reversed from the typical SST pipeline: Lauretta didn't use SST to build toward a flagship mission. He was already the flagship PI and used SST as a mechanism to develop supporting ML navigation technology while simultaneously operating the mission. SST was a side-channel for a flagship PI to advance ancillary tech.

SST Project

ML Algorithms for Asteroid Navigation 95600

  • Period: 2018-03-03 to 2020-10-31
  • TRL: 3 → 5 (target 5)
  • Lead org: University of Arizona
  • PI: Dante S Lauretta
  • TX: TX17.2.1 Onboard Navigation Algorithms
  • Partner: Goddard Space Flight Center
  • Destinations: Others Inside the Solar System
  • Description: Machine-learning algorithms for onboard asteroid shape model determination and spacecraft navigation. The "Markov brain" approach aims to supplant thousands of hours of human effort in image-intensive optical navigation, stereophotoclinometry shape model generation, and natural-feature tracking terrain-relative navigation.

Key context: This SST project started in March 2018 — OSIRIS-REx had launched in September 2016 and arrived at Bennu in December 2018. Lauretta was developing ML navigation tech while actively operating the flagship mission that needed it. The SST project was not a precursor to OSIRIS-REx; it was a parallel technology development effort by the same PI.

Full TechPort Footprint (Dante S Lauretta)

Project Program Period TRL Role Lead Org Status
95600 ML Asteroid Nav SST 2018–2020 3→5 PI U Arizona Completed
12244 OSIRIS-REx regolith sampling tests FO 2012–2015 5→6 Co-I Lockheed Martin Completed

The FO project [12244] is a pre-SST connection: low-gravity regolith sampling tests for OSIRIS-REx, led by Lockheed Martin with Lauretta as Co-I and GSFC as partner. This confirms Lauretta was embedded in the OSIRIS-REx program years before the SST award.

OSIRIS-REx: The Flagship Context

  • Mission cost: $800M+ (New Frontiers class)
  • Launched: September 8, 2016 (Atlas V 411)
  • Arrived Bennu: December 3, 2018
  • Sample collected: October 20, 2020 (Touch-And-Go)
  • Sample returned: September 24, 2023 (Utah Test and Training Range)
  • Sample mass: 121.6 grams from asteroid 101955 Bennu
  • First US asteroid sample return
  • Lauretta became PI in 2011 after original PI Michael Julian Drake died

The SST ML navigation project (2018–2020) developed algorithms that would automate the labor-intensive optical navigation and shape modeling that OSIRIS-REx performed manually with extensive ground-based human effort. The vision: future small-body missions could do this onboard, autonomously, enabling CubeSat-class asteroid explorers.

Downstream Impact

Direct: ML Navigation Algorithms (TRL 3→5)

The Markov brain approach to onboard shape model determination and terrain-relative navigation advanced to TRL 5 under SST. These algorithms are relevant to: - Future small-body reconnaissance missions (CubeSat-class asteroid surveyors) - Autonomous proximity operations around irregular bodies - Any mission requiring onboard image-based navigation without ground support

Confidence: suggestive — no confirmed flight adoption yet, but the TRL 5 demonstration with OSIRIS-REx data provides a validated proof of concept.

Indirect: OSIRIS-REx Heritage

Lauretta's broader OSIRIS-REx work has produced: - Largest asteroid sample ever returned to Earth - Surprising phosphate mineral findings in Bennu samples (reported 2024) - Extended mission: OSIRIS-APEX (asteroid Apophis, arriving 2029) - Hundreds of peer-reviewed publications - Regents Professor of Planetary Science at U Arizona Lunar and Planetary Laboratory

However, this heritage is attributable to the OSIRIS-REx program (New Frontiers), not to SST.

Assessment

Lauretta's SST project represents an unusual pattern: "Flagship PI Seeds Side Technology."

  • Most SST university projects follow the pattern: SST funds early-career researcher → researcher grows → flagship mission
  • Lauretta inverts this: established flagship PI uses SST to develop ancillary ML tech that could enable future small spacecraft to do what his flagship mission did with expensive ground support
  • The SST investment is small (~$200K–$500K typical SST university award) relative to the flagship context ($800M+), but it targets a genuine capability gap: making small-body navigation autonomous enough for CubeSats

This is a different ROI model than the People Chain archetype. The "return" isn't the PI's career advancement (Lauretta was already a Regents Professor and flagship PI). The return is the algorithm — if future missions adopt onboard ML shape modeling, the SST seed will have enabled CubeSat-class asteroid exploration.

People & Connections

  • Dante S Lauretta — Regents Professor, U Arizona LPL. OSIRIS-REx PI. OSIRIS-APEX PI.
  • GSFC — Partner on both TechPort projects (SST [95600] and FO [12244])
  • Lockheed Martin — OSIRIS-REx prime contractor, FO [12244] lead org

Cross-References

Open Questions

  1. Has any subsequent mission or proposal adopted the Markov brain navigation algorithms from SST [95600]?
  2. Did OSIRIS-APEX incorporate any SST-funded ML navigation capabilities?
  3. Are there U Arizona students from Lauretta's group who have carried SST-adjacent ML nav tech to other institutions or companies?