Juan Manuel Delfa Brian Yeomans

Yang Gao, Oskar von Stryk

ASTRA 13/05/2015

Autonomous Mission Planning And Execution

for Two Collaborative Mars Rovers

Introduction

• Lot of work conducted in path planning and mobility.

• Other types of autonomy use to be forgotten. • NASA has developed several autonomous

systems for MER and Curiosity: – On-Ground: MAPGEN mission planner. – On-Board: AEGIS opportunist science, Autoplace, VTT,

WATCH.

This presentation talks about tactic/strategic Mission Planning and Execution.

Motivation: More Autonomy

• Automated Mission Planning Process that, given and initial and goal state,

chooses and organizes actions by anticipating their expected outcomes in order to achieve the goals.

• Automated Execution Process that, given a plan composed of sequences of activities, command each activity to the appropriate

subsystem at the appropriate time.

Problem: Temporal Planning for complex problems is not solvable with modern computers.

The FASTER project

FASTER (Forward Acquisition of Soil and Terrain data for Exploration Rover) • EU-FP7 Program funded by European Union. • Consortium including. • Goal: To improve the security and speed of

planetary rovers. • Mission concept: Two collaborative rovers working

in tandem: − Primary: ExoMars-class. − Scout: Smaller, more robust, travering in front to

detect potential hazards.

Primary Rover • Bridget: ExoMars

testbed. • Constructed by

Airbus. • Modified with

extra-sensors for soil-sensing.

Scout Rover • High mobility. • Constructed by

DFKI and UoS.

FASTER - Rovers

Operations cycle for a Rover

Operations divided in two groups: • On-Ground

− Definition of the plan goals. − Definition of the Knowledge DataBase (Behaviours). − Plan generation.

• On-Board − Uplink of the plan. − Execution. − Plan repair.

Architecture

• Adaptable level of autonomy (E1-E5).

• Adaptable internal organization for different mission requirements.

• Thee-layer architecture

− Deliberative: Long-term planning.

− Reactive: Execution and short-term repair.

− Functional: Hardware dependent controllers.

Architecture - Components

• Deliberative: − RobCon: Middleware between

Planner and Executive. − Mission Planner:

QuijoteExpress.

• Reactive: − Primary rover Executives:

SanchoExpress. − Scout rover: Specific executive

(DFKI) subordinated to SanchoExpress.

• Functional: − Soil Sensor System. − Plath Planner. − Bridget Locomotion System.

Problem

Model

Planner Solution

Mission Planner - QuijoteExpress

Behaviours

QuijoteExpress - Novelties

Provide high levels of autonomy and collaborative capabilities to robots

Properties 1. How to produce faster solutions

Parallel planning Forward-chaining planning Heuristic guided 2. How to manage unknown situations

Partial planning 3. How to better help engineers to verify

& validate plans Hierarchical models & behaviours High level goals

Constraint

Action Subsystem

QE – FASTER Modelling

QE – Traverse Behaviours

QE – Traverse Behaviours

From Mission Planning to Execution

• Plan is represented with Timelines. • Timeline: Sequence of actions with an starting

and ending time frame. • One timeline per subsystem. • Transition: Time at which at least one timeline

change value.

SanchoExpress: Properties

Provides autonomous execution for robotic systems

Properties 1. Temporal Execution Flexible timelines 2. Parallel execution All timelines executed in a dedicated thread 3. FDIR Capabilities Primary Locomotion can detect and fix failures derived from traverse activities.

SE: Dedicated Executives • Generic Executive

− Platform independent. − Receives a plan. Commands individual actions. − Reports back to deliberative layer (user or planner depending

on level of autonomy). − Decides when to execute (next transition).

• Dedicated Executive − Platform dependent. One for each dedicated subsystem. − Receives/commands individual actions. − Reports back to Generic Executive. − FDIR capabilities.

SE: Example 1. Generic Executive (GE) receives new action TurnToWP. 2. Searches in a DataBase which dedicated executive knows how to execute it. 3. Primary Locomotion (PRLoc) calls the method TurnToWP, which contains 3 actions.

Why this approach? • No need to plan in such low

level of detail. • User doesn’t need to know

unless something wrong happens.

TurnToWP(goal)

FASTER – Tests & Final Demo

• Multiple test-campaigns: − 5 Integration: Oriented to integrate all subsystems. − 5 Mission-level: Oriented to make the subsystems

work together. • Testing Mission Planner and Executive

− Specially difficult: Both depend on the rest of subsystems.

− Simulation campaigns with dummy subsystems.

• Final Demonstration: Presented to European Commission on October, 2014 in the Mars Yard facility, Airbus DS, Stevenage.

Sand trap Loose soil

FASTER – Setup

Rovers in formation

Rocks of different sizes

FASTER – Plan

• Flexible plans generated in few seconds. • Final demo mission:

– Traverse 15 meters. – Demonstrate Soil Sensor System.

• Estimated 12 traverse cycles. • Each traverse cycle containing 18 transitions. • 5 timelines.

Planning Choose Target Generate Map

Generate Path

Scout Traverse

Primary Traverse

Update map

FASTER – Workflow

Results • Mission Planner

− Great performance. Time required negligible compared with more intensive processes related to image processing.

− Hierarchical planning worked successfully. − Flexible plans were crucial for the success. − Models and behaviours worked successfully.

• Executive − Worked flawlessly. − During final demo, short-scope plan repair was

required twice, helping to resume the mission without the need of re-planning.

Conclusions

• Several new technologies has been demonstrated − Novel mission planner. − Generation and Execution of collaborative plans. − On-the-fly plan repair.

• Next steps − Achieve opportunistic science. − Demonstrate re-planning with next generation

QuijoteExpress. − Go further in the integration with the path planner.

Contact Juan.Manuel.Delfa.Victoria@esa.int

Questions