NASA · NASA-450 · record R0248

Onboard Planner for Mars2020 Rover (Perseverance)

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

The M2020 onboard scheduler incrementally constructs a feasible schedule by iterating through activities in priority-first order.

Expected benefits

Research, experiments, and engineering to empower future rovers with onboard autonomy; planning, scheduling & execution; path planning; onboard science; image processing; terrain classification; fault diagnosis; and location estimation. This is a multi-faceted effort and includes experimentation and demonstrations on-site at JPL's simulated mars navigation yard.

System outputs

When considering each activity it computes the valid time intervals for placement, taking into account preheating, maintenance heating, and wake/sleep of the rover as required. After an activity is placed (other than a preheat/maintenance or wake/sleep), the activity is never reconsidered by the scheduler for deletion or moving. Therefore the scheduler can be considered non backtracking, and only searches in the sense that it computes valid timeline intervals for legal activity placement.

Technology

AI classification: Agentic AISource: Agentic AI: AI systems that perform tasks or make decisions autonomously with minimal human intervention.
System name(s): Multiple approved space-based systems
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: terrain input
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.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported