A Programmatic View of CLARAty Richard Volpe JPL Space Exploration Technology Program Office NASA Mars Technology Program 2009 Mars Science Laboratory Project Jet Propulsion Laboratory California Institute of Technology

Overview Review of Technology Component Flow Chart Legacy & Current Robotics Flight Software CLARAty & Testbeds Competitively-Selected Technology Components’ Development Validation of Technology Components MDS Infusion Other Issues

Technology Component Flow

Legacy Technology

WITS Rover Interface

Legacy Software Selection Criteria (draft) Mars Application: Relevance of the technology to the Mars Exploration problem, particularly that expressed within the 2009 Mars Science Laboratory flight project Constraint Compliance: Ability of the technology component to live within expected mission constraints (CPU, memory, power, etc.) CLARAty Augmentation: Complementary versus duplicative nature of the technology component as compared to current CLARAty-based capabilities. Maturity: Maturity of the algorithms, and the software implementation Effort & Cost: Level of effort to capture the technology component, depending on complexity, documentation, intellectual property release, etc.

CLARAty and Testbeds

CLARAty Coupled Layer Architecture for Robotic Autonomy THE DECISION LAYER: Declarative model-based Mission and system constraints Global planning INTERFACE: Access to various levels Commanding and updates THE FUNCTIONAL LAYER: Object-oriented abstractions Autonomous behavior Basic system functionality

ROCKY 8 Development and Test Platforms ROCKY 7 K9 ROAMSDEXTER ATRV JR. FIDO FY01 Supported New In FY02

Multi-Level CLARAty / Subsystem Closed-Loop Control (for Rover) PASSTHROUGH Decision Layer Navigation Loco- motion Joint Control Decision Layer Navigation Decision Layer Navigation Planetary Rover Rover Level Navigation Level Motor Level Navigation Subsystem FL DL Subsystem Origins COTS systems (e.g. ATRV Jr.) Firmware (e.g. widget boards) Simulation (e.g. ROAMS) Legacy Loco- motion Joint Control Loco- motion Joint Control Loco- motion Joint Control

Goals enter at top Decision Layer Functional Layer Subsystem Layer granularity Elaboration – P&S, Exec Functional decomposition Subsystem details Rover and Instruments Granularity Matching between Layers of Decision, Function, and Subsystem Key points: Granularity penetration at each level may vary. Subsystem may exist at all levels of granularity. Decision Layer access to subsystem passes through Functional Layer, even at a single point. DL / FL interface independent of subsystem. Complete “subsystem” is accessed through stubbed-out FL System hardware Environment

Example: Simulation Goals enter at top Decision Layer Functional Layer Simulation Layer granularity Elaboration – P&S, Exec Functional decomposition Simulation details Rover and InstrumentsEnvironment Subsystem is the simulator. Primary work to be done is simulated environment development. Leverages: - FY02 CLARAty / ROAMS - ongoing MSL - MSF efforts at ARC

CLARATY INSTRUMENTS PACKAGE SCIENCE DATA PROC PKG Instrument Spectro- meter Science Processing Sim Spec Real Spec Sim Cam Rover Hardware (K9, R8, etc.) Spec Processing Roush Spec Proc Cam SIMULATION INSTRUMENT SIMULATORS Camera Simulator Spectrometer Simulator MSF Client Instrument Client Rover Client Terrain Model Spectral data K9 Client Instrument Client Rover Client CONDITIONAL EXECUTIVE Linux-based Planning System Proposed FY03 MSF – CLARAty Structure MOBILITY PACKAGE Rover Locomotor Motor Navigator Sim Motor Sim Rover Real Motor Sim Nav DEMs TERRAIN & ENV DATA SERVERMarsTERM CLIENT ROAMS High Level Rover Simulator Navigation Motor Simulator Real Cam Engineering Data Interface OO Terrain

Competitively Selected Technology Component Development

Competed Tasks Round 1 Selection Process 02/05/01 – Announcement of Research Opportunity released 02/28/01 – Proposal due date (36 proposals received) 05/03/01 – Selection of proposals Total funding (FY’01 – ’04): $5M Proposals (Awarded vs. Submitted) Awarded Funding Distribution Round 1 Selected Proposals

Real Rover(s) CLARAty Decision Layer CLARAty Functional Layer Real Rover(s) Real Terrain Sim Terrain(s) SIMULATION ENVIRONMENT Decision Layer GOALSSTATUS Component Technology Alternate Decision Layer Example: Roush Autonomous Science Algorithms Example: Washington Conditional Sequencer Volpe – 2/21/02 REPLACE INSERT Rover(s) Sim Instrument(s) Tech Component Capture in CLARAty High Detail Sim MTP Tech Components Primarily go to Functional Layer. IS Program Technology provides alternate Decision Capabilities.

Technology Validation

‘09 MSL Validation Scenario #1: Approach & Instrument Placement Description: Enable placement of a science instrument on a designated target, specified in imagery taken from a stand-off distance. Placement accuracy to be within 1cm or 0.1%, from a stand off distance not greater than 10m. rover Max designation range < 10m partial panorama instrument placement placement error ellipse goal designation error

Description: Enable autonomous traverse, obstacle avoidance, and position estimation providing up to 600m/sol with less than 3% error relative to starting position. start stop error ellipse goal traverse leg length < 600m actual path autonomously executed ‘09 MSL Validation Scenario #2: Long Range Traverse

Description: Enable processing of science data onboard the rover system. This will be used for the progressively more challenging issues of: intelligent data compression (inlier detection) and prioritization, anomaly recognition (outlier detection) with stop and communicate result, conditional actions based on either of first two. Example: “Terrain classification while doing long traverse” Layers detected in blue regions Rocks targeted for spectral analysis (green) Compound Horizon Determined (red) ‘09 MSL Validation Scenario #3: Onboard Science Data Processing

Technology Infusion Into MDS

MSL Flight Software MSL Rover Testing MTP Tech Dev Legacy S/W NOW Overview of Software Flow in Time MTP Tech Dev

Component Technology Development Technology Software Infrastructure MDS Core for MSL Existing Tech MDS Adaptation for MSL Flight Software Infrastructure CLARAty for MSL MSL CLARAty-based demos MDS-based demos ‘01‘02‘03‘04‘05‘00 CLARAty after MSL Currently funded competed tasks TBD NRA tasks pre-MSL demos pre-MSL MDS Core pre-MSL CLARAty LONG TRAVERSE INSTRUMENT PLACEMENT AUTO SCIENCE Technology Timeline for MSL

CLARAty and MDS Principal Attributes of Each System CLARAty (Coupled Layer Architecture for Robotic Autonomy) For research and development Rovers, robotic systems Tool suite for rapid prototyping Integrate disparate research efforts (NASA Centers, Universities, JPL) Interoperability across platforms (integration and comparison) MDS (Mission Data System) For JPL missions For complete spacecraft systems (control, fault protection, communication, end-to-end flight- ground system) Integration across project activities (systems engineering, software engineering, software reliability) Reuse across projects (accumulate multi-mission legacy)

CLARAty / MDS Infusion Configurations MDS CLARAty Decision Layer CLARAty for researchMDS for flight CLARAty Functional Layer Encapsulation with modular Inclusions Full Translation (Standard MDS Adaptation) MDS CLARAty Functional Layer Full Encapsulation MDS Translation with modular Inclusions Hardware flight configurationsdevelopment and test configurations CLARAty functional modules

Existing Tech Components in MDS on Rocky 7 Hardware Adaptor State Variables EstimatorsControllers Constraint Network ElaboratorsMPE Scheduler Component Scheduler Parameters Proxy State Variables MER NavigationMDS Framework ROAMS SimulationR7 with PPC 750Benchtop Hardware

Other Issues ITAR, IP, open-source, RETF New funded participants: MTP, IS, ASTEP, etc. Possible new unfunded participants CLARAty Development versus User communities - ‘CLARAty to Universities’ study underway - release and core-upgrade management MSL Mission Scenario - nonzero chance of change to fixed lander - level of autonomy continues to change