Enhanced AutoNav for Perseverance Rover on Mars
National Aeronautics and Space Administration · JPL: Jet Propulsion Laboratory
Overview
- Development stage
- DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
- High-impact designation
- Not high-impactSource: c) Not high-impact
- Impact justification
- Not reported
- Start date
- 2020-07-01 (day precision)Source: 07/01/2020 00:00:00
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Science
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
AutoNav on the Perseverance Rover autonomously plans a safe path based on stereo navigation camera images, based on multiple technologies including a tree search for decision making, Dijkstra algorithm for global path planning, stereo processing for 3D terrain reconstruction, and Approximate Clearance Evaluation (ACE) for safety checks.
Expected benefits
AutoNav on the Perseverance Rover autonomously plans a safe path based on stereo navigation camera images, based on multiple technologies including a tree search for decision making, Dijkstra algorithm for global path planning, stereo processing for 3D terrain reconstruction, and Approximate Clearance Evaluation (ACE) for safety checks.
System outputs
Recommended navigation path for Mars Rover.
Technology
- AI classification
- Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
- System name(s)
- Mars2020 Rover
- Custom-developed code
- Yes
- Public source code
- Not reported
Sourcing
- How it was built
- Developed in-houseSource: b) Developed in-house
- Vendor (as reported)
- Not reported
- Vendors (standardized)
- None on the standard list
A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.
Data and privacy
- Involves PII
- No
- Privacy Impact Assessment
- Not reported
- Authorization to Operate
- No
- Demographic features
- Not reported
- Training and evaluation data
- stereo navigation camera images
- Federal Data Catalog
- Not reported
Governance
0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.
Potential impacts and how they were identified
Not reported