1. Continual Coordination of Shared Activities Brad Clement & Tony Barrett Artificial Intelligence Group Jet Propulsion Laboratory California Institute of Technology {bclement,barrett}@aig.jpl.nasa.gov http://www-aig.jpl.nasa.gov/

2. Overview Why decentralized planning? Shared Activity Coordination (ShAC) –multiagent modeling –framework for developing roles and protocols –testbed for evaluating protocols –continual coordination algorithm Mars 2003 coordination scenario

3. Why Decentralized Planning? Why plan? –near-term actions can effect subsequent ones in achieving longer-term goals Why decentralize? –competing objectives (self-interest) –physically distributed points of control –limited shared resources –communication constraints/costs –computation constraints (parallel processing) –greater capabilities/efficiency of distributed assets

4. Motivation for NASA Over 40 multi-spacecraft missions proposed! –Autonomous single spacecraft missions have not yet reached maturity. –How can we cost-effectively manage multiple spacecraft? Earth Observing SystemSun-Earth Connections Origins Program Structure & Evolution of the Universe Mars Network NMP

5. Approach shared activities shared resource shared state Activities with constraints on shared resources/states are passed to other mission planners. Coordination involves planners resolving local conflicts by manipulating activities as permitted by their roles and sending changes and constraints to others. The plans are coordinated when they have consistent shared activities and no flaws.

6. Optimize a function of variable assignments with both local and non-local constraints. Distributed Constrained Optimization Control Executive Planner Analyst

7. Executive Planner Executive Planner Executive Planner Shared Activity Coordination Shared activities implement team plans, joint actions, and shared states/resources

8. Shared Activity Model identifier parameters (string, integer, etc.) –constraints (e.g. agent4 allows start_time [0,20], [40,50]) decompositions (shared subplans) permissions - to modify parameters, move, add, delete, choose decomposition, constrain roles - maps each agent to a local activity protocols - defined for each role –change constraints –change roles changes sharing agents and protocol assignments –handle changes received from other agents

9. Example

10. ShaC Algorithm Given: a plan with multiple activities, including a set of shared_activities with constraints, and a projection of plan into the future. 1.Revise projection using the currently perceived state and any newly added goal activities. 2.Alter plan and projection while honoring constraints. 3.Release relevant near-term activities of plan to the real-time execution system. 4.For each shared activity in shared_activities –if outside consensus window, apply each associated protocol to modify the activity –else apply simple consensus_protocol 5.Communicate changes in shared_activities and constraints. 6.Update shared_activities and constraints based on received communications. 7.Go to 1.

11. Default Protocol Capabilities joint intention mutual belief resource sharing active/passive roles master/slave roles

12. Extending Protocol Classes 1.modify permissions 2.modify local parameter constraints 3.add/delete sharing agents 4.change roles of sharing agents

13. Example Protocol Classes 1.modify permissions 2.modify local parameter constraints 3.add/delete sharing agents 4.change roles of sharing agents Argumentation (1,2) Delegation (3) Asynchronous weak commitment (1,2) Constraint-based conflict resolution (2,4) Round robin (1) Centralized conflict delegator (extends delegation)

14. Asynchronous Weak Commitment Modify permissions: –if have highest priority remove self’s modification permissions (add, move, delete) –else give self modification permissions Modify parameter constraints: –if cannot resolve local conflicts and conflicts with constraints of higher ranking agents set own rank to highest rank plus one generate parameter constraints (no-good) describing locally consistent values

15. Constraint-Based Conflict Resolution Modify parameter constraints: –if cannot resolve conflicts involving shared activity update parameter constraints describing locally consistent values Modify roles: –if reached consensus on constraints or time_elapsed > threshold switch to role for solution convergence (e.g. argumentation, voting, highest rank decides)

16. Coordination Protocol States flawed – schedule has conflicts changes sent – planner has sent local changes to other mission planners flawed, changes sent not flawed, changes not sent flawed, changes not sent not flawed, changes sent update not ok update update ok update not ok replan not ok send changes replan ok send changes Transitions update – changes received from other planners cause conflicts (not ok) or not (ok) replan – conflicts are resolved (ok) or not (not ok) send changes – updates other planners update ok

17. Coordinating the Commanding of Mars ‘03 Distributed Odyssey, MER A, and MER B ASPEN planners Schedules generated independently MERs share bandwidth and memory for downlinks from Odyssey Mars 2003

18. Coordinating the Commanding of Mars ‘03 Distributed Odyssey, MER A, and MER B ASPEN planners Schedules generated independently MERs share bandwidth and memory for downlinks from Odyssey Mars 2003

19. Coordinating the Commanding of Mars ‘03 Distributed Odyssey, MER A, and MER B ASPEN planners Schedules generated independently MERs share bandwidth and memory for downlinks from Odyssey Mars 2003

20. Motivation Considerable ground operations effort and cost involved in coordinating mission plans for interacting missions. Human collaboration can be error-prone and slow to react. Automating this coordination reduces operations costs and increases science return. Applies to autonomous missions

21. Mars 2003 Scenario MERs send critical data to Earth and need uplink to direct subsequent activities Odyssey can often get data to/from Earth faster than MERs MERs’ mission planners coordinate with Odyssey’s to determine how and when data is routed Bandwidth and memory is shared on Odyssey, and decisions affect other local resources, such as power which can restrict other activities Mars 2003

22. Mars 2003 Scenario no pending request request wait for uplink critical pancam comm earth comm odyssey MER activities Odyssey activities no pending request comm earth through Odyssey direct must-be wait wait for uplink no pending request request wait for uplink critical pancam comm earth must-be wait odyssey received no pending request comm earth comm odyssey wait for uplink downlink critical data uplink from DSN

23. Mars 2003 Scenario no pending request Odyssey MER A must wait comm earth MER activities Odyssey activities critical pancam comm earth comm odyssey traverse comm earth no pending request request no pending request wait for uplink science activities

24. Mars 2003 Scenario Odyssey MER A must wait comm earth MER activities Odyssey activities critical pancam comm earth comm odyssey traverse comm earth no pending request request no pending request wait for uplink science activities must wait critical pancam comm earth comm odyssey traverse comm earth no pending request request no pending request wait for uplink

25. Mars 2003 Scenario Odyssey MER A must wait comm earth MER activities Odyssey activities critical pancam comm earth comm odyssey traverse comm earth no pending request request no pending request wait for uplink science activities must wait critical pancam comm earth comm odyssey traverse comm earth no pending request request no pending request comm earth must wait wait for uplink

26. Mars 2003 Scenario Odyssey MER A must wait comm earth MER activities Odyssey activities critical pancam comm earth comm odyssey traverse comm earth no pending request request no pending request wait for uplink science activities critical pancam comm earth comm odyssey traverse comm earth no pending request request no pending request comm earth must wait wait for uplink odyssey received must wait wait for uplink no pending request

27. Mars 2003 Scenario Odyssey MER A comm earth MER activities Odyssey activities critical pancam comm earth comm odyssey traverse comm earth no pending request request no pending request science activities critical pancam comm earth comm odyssey traverse comm earth no pending request request comm earth must wait wait for uplink odyssey received must wait wait for uplink odyssey received no pending request

28. Mars 2003 Scenario Odyssey MER A comm earth MER activities Odyssey activities critical pancam comm earth comm odyssey traverse comm earth no pending request request science activities critical pancam comm earth comm odyssey traverse comm earth no pending request request comm earth must wait wait for uplink odyssey received must wait wait for uplink odyssey received no pending request

29. Coordination Interactions Mission Planner AMission Planner B Coordination Proxy ASPEN reqUpdate [schedChanged == true] reqUpdate notifyUpdateSent notifyRecvUpdate reqConflicts [schedChanged == true] notifyUpdateSent reqReplan reportConflicts notifyReplanDone * sendUpdates notifyReplanDone reqUpdate notifyUpdateSent notifyRecvUpdate * sendUpdates [schedChanged == false] reqConflicts reqReplan reportConflicts notifyReplanDone reqReplan [justReplanned == true] reqUpdate * sendUpdatesreqReplan reqUpdate notifyRecvUpdate notifyUpdateSent [justReplanned == true]

30. Evaluation Ground coordination time is greatly reduced for quicker reaction to current situation –Plan quality Increased science return Resource limiting approach sacrifices quality to alleviate coordination problem Automated coordination allows mission planners to optimize science return up front while ignoring interactions with others Coordination process seeks minimal concessions in mission plans while resolving shared resource conflicts –Operations cost Automated coordination minimizes human involvement in resolving shared resource conflicts

31. Summary Shared Activity Coordination (ShAC) –multiagent modeling –framework for developing roles and protocols –continual coordination algorithm Mars 2003 coordination scenario

32. Future Directions Evaluate protocols in testbed Quick group response to anomalies and discovered opportunities Use summary information for abstract reasoning Apply to –Ground operations for Techsat-21 –Antenna array automation for DSN –Distributed, autonomous missions Mars 2003

33. Related Work (partial list) Collaborative planning (D-SIPE) Team activity modeling (TEAMCORE) –TOP (Team Oriented Programming) Protocol Evaluation (TÆMS/GPGP) Plan merging/coordination –Georgeff, Ephrati & Rosenchein, Lansky –DPOCL –Summary information Joint Intentions –STEAM –Shared Plans

34. Proxy ASPEN Coordination Protocol report – conflicts remaining to determine status req – request replanning or update broadcasts notify – informs proxy when time to initiate replanning updates – activities sent and incorporated to create views of local and global schedule status – to determine if coordination has finished ASPEN Coordination Proxy ASPEN Coordination Proxy recv msg replan send updates status updates report merge updates notify req

35. 35 MER / ODY Sequence Development & Execution Timeline waggoner 6/14/01 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 MER A SOLs (n+) ODY Minisequence Seq ODY MER A MER A/B Strategic Planning Cycle Seq MER B Seq Dev ODY RTCs

36. Organizations and Data Flow Derived from Concepts ESOC/LOC MMO NAV MMO MPSET (SEQ/ASP) MMO MMCTLMA RTO MSSS-MOC MER IST/ SCT/SCI ESA Antenna LMA SCT MERAMERBODYBeagleMGSMEX MMO MPSET (PLANNING) Uplink and Downlink Data Ground Planning and Uplink Products Essential to Relay and DTE Communications MMO MDAPT DSN waggoner 6/14/01