1. Seeker kick-off workshop “State of the art” Simon Lacroix Laboratoire d’Analyse et d’Architecture des Systèmes CNRS, Toulouse

2. Disclaimer Learn last Thursday that I was to give this talk… Was in Barcelona Thursday / Friday… Had a week-end already “burnt” by work  Plus: Have not worked on planetary rovers since 2005 Not aware of latest Exomars developments Knows nothing on Mars Science Laboratory navigation (but who else than JPL knows?)

3. What state of what art ? MER missions 2004 baseline stems from mid 90’s research Has been used as a testbed for improvements (visOdom, global Nav with D*, target reaching) Exomars / MSL navigation approaches Publications related to planetary rover navigation Huge progresses / publications in vision & navigation in the robotics community

4. Seeker main axes of development Long range navigation Mission planning Science autonomy

5. A glimpse at recent publications Other essential information sources: ICRA and IROS space robotics workshops ASTRA and I-SAIRAS conferences Related to seeker Journal of Field Robotics 2007: 3 special issues on “Space Robotics” 2009: 2 special issues on “Space Robotics” More to come end of this year 21 papers 7 not on rovers (out of Seeker scope) 2 on rover chassis conception 4 on locomotion (advanced motion control) 2 on localization 2 on navigation 3 on high level planning 2 on “target reaching”

6. Seeker main axes of development Long range navigation Mission planning Science autonomy

7. Navigation Three main functionalities: Perception: data acquisition, environment map building, localization Decision: path and trajectory determination Action: locomotion control and monitoring (plus overall control / supervision)

8. MER approach  Main characteristic: validated !  Overview: simple loop 1.Data acquisition: stereovision 2.Environment modelling: local navigation map 3.Decision: elementary trajectory evaluation 4.Trajectory execution (short distance)  Localization: odometry + IMU (+ sun sensor)  Overall control: sequential loop

9. MER approach stereovision motion selection Locomotion, then stop traversability analysis

10. MER “extended” approach  VisOdom  “Itinerary planning” using D*  Target reaching

11. CNES approach  Main characteristic: experimentally validated  Overview: a bit more complex loop 1.Data acquisition: stereovision 2.Environment modelling: navigation map updating 3.Decision: 1.Sub-goal determination 2.Trajectory planning 3.Perception planning 4.Trajectory execution (limited distance)  Localization: odometry + IMU  Overall control: sequential loop

12. CNES approach stereovision traversability analysis Locomotion, then stop robot Sub-goal, trajectory and perception task selection

13. MER vs CNES approaches In 2004:  MER approach –The simplest, local navigation (“Obstacle avoidance” scheme)  CNES approach –More global reasoning (“Navigation planning”)  Able to more efficiently deal with longer missions  This comparison does not hold since D* integration on MER

14. (LAAS approach) Overall loop: sub-goal, trajectory, perception task and motion mode selection Easy terrain modeRough terrain mode Mode n … But: certainly too complex for Seeker

15. Lessons learned from MER  Many easy situations tackled under direct control  Localisation is a critical issue in some situations  Better locomotion abilities required (slip detection) Rover Autonav distance Total distance Spirit1253 m3405 m Opportunity224 m1264 m As of June 14, 2004 :

16. Lessons learned from MER  Higher autonomy required to traverse cluttered areas  Several ground interactions required to place the instruments  End of autonomous motions may leave rover in bad attitude (wrt. antenna, solar panel)

17. Localization  3D odometry integrates: –Wheel encoders –Wheel steering angles –Chassis angular configuration  Inertial localization: assess among the following possibilities –Attitude information (at stop and during motions) –Heading provided by the integration of a gyrometer (what drift? Are there space qualified FOGs ?) –Integration of 6-axis IMU - fused with odometry

18. Vision-based localization  Visual odometry principle Stereo : 3D points Motion estimation with matched 3D points TkTk T k+1

19. Vision-based localization  Numerous progresses since 2004:  Feature-based SLAM  Single cams, stereo cams, panoramic cams  Efficient EKF or optimization solutions  INS / odometry integration

20. Vision-based localization  Numerous progresses since 2004:  Appearance-based localization  E.g. fabMap @ Oxford  Efficient way to detect loop closures

21. Locomotion control and monitoring  Opportunity in April 2005

22. Locomotion control and monitoring  Opportunity in April 2005

23. Locomotion control and monitoring Locomotion monitoring of essential importance –Position tracking –Attitude and chassis internal angles checking ·Wrt fixed thresholds ·Wrt to a “configuration space trajectory” –Wheel slippage detection –Localisation algorithms monitoring Plus: Recovery procedure definition required Essential importance of diagnosis (FDIR) (non only locomotion, but overall navigation)

24. Seeker main axes of development Long range navigation Mission planning Science autonomy

25. ESA-driven GOAC project “Goal Oriented Autonomous Controller”: Goal-oriented operations: A goal tells the robot what to do, instead of how to do it. Model-level programming: High-level of abstraction raising the focus to the problem domain: features of the robot mechanisms, available behaviours, task domain. Robust execution in an uncertain environment: Let the robot decide how best to accomplish an objective, based on situation at hand. Safe execution: The model used by the planner can capture safety constraints, so that all plans produced are guaranteed to comply with these constraints. Correct-by-construction functional layer: Only allowed behaviours will be actually executed.

26. ESA-driven GOAC project The level of uncertainty is extremely high Planning involves ground assessment. Autonomous path planning is a must! Communications are scarce due to a narrow comms window and long distance (latency) Plan has to merge science activities with engineering activities Plan has to be validated by using the Simulator, before being uplinked The tactical operation’s process has very strict deadlines that have to be accomplished on a per-sol basis

27. As a conclusion Ongoing R&D issues (according to L. Matthies, 2005) –Much faster flight processor –3-D perception at night –Parachute for high elevation landing –Brushless motors –Nuclear power –Locomotion mechanisms for very steep terrain –Landmark recognition during descent –Single command target approach and instrument placement –Path planning for rough and steep terrain –Position estimation on slippery terrain –More automated long range position estimation and mapping –More automated sequence generation for mission planning Not related to Seeker Very relevant – but not in Seeker’s scope Definitely targeted by Seeker, many solutions exist in the literature