Open-World Mission Specification for Reactive Robots - ICRA 2014

1. Open-World Mission Specification for Reactive Robots Spyros Maniatopoulos Matthew Blair, Cameron Finucane, Hadas Kress-Gazit Sibley School of Mechanical and Aerospace Engineering Cornell University sm2296@cornell.edu verifiablerobotics.com

2. Controller Synthesis Robot Environment Mission Specification Workspace Hybrid Controller Reactive Synthesis Discrete Strategy

3. Meet the mailbot 3

4. Challenges 4 Letters letter_Spyros letter_Matt letter_Cameron The mailbot’s world is open with respect to letter recipients. letter_Hadas

5. “Closed” vs. “Open” Worlds 5 “Closed-World Assumption” Only elements of the world modeled a priori can be taken into account during execution. Robotic assembly by DENSO’s robot arms. Source: www.robots.com

6. “Closed” vs. “Open” Worlds 6 “Open-World” New elements and objectives arise during execution. Photo: Panagiotis Papadakis Source: spectrum.ieee.org

7. Open-World Challenges • Not all mission variables known a priori • Mission objectives change during execution • React to unexpected events during execution • Incorporate/learn new functionality on-the-fly 7

8. Related Work 8 S. C. Livingston, R. M. Murray, and J. W. Burdick, “Backtracking temporal logic synthesis for uncertain environments,” ICRA, 2012. S. C. Livingston, P. Prabhakar, A. B. Jose, and R. M. Murray, “Patching task-level robot controllers based on a local μ-calculus formula,” ICRA, 2013. M. Guo, K. H. Johansson, and D. V. Dimarogonas, “Revising motion planning under linear temporal logic specifications in partially known workspaces,” ICRA, 2013. A. I. Medina Ayala, S. B. Andersson, and C. Belta, “Temporal logic motion planning in unknown environments,” RSS, 2013. S. Sarid, B. Xu, and H. Kress-Gazit, “Guaranteeing high-level behaviors while exploring partially known maps,” RSS, 2012.

9. Discrete Abstraction 9 Region Propositions Action Propositions Sensor Propositions

10. Logic-based Mission Specification 10 Boolean Operators Temporal Operators Linear Temporal Logic Robot starts in r1 If you are sensing alarm then visit r2 Structure d English “Starting in region r1, repeatedly visit the region r2 if you are not sensing an alarm” GR(1)

11. Approach Overview 11

12. Detecting New Elements 12 Detector propositions Proposition Grounding function

13. Adding New Elements 13

14. Adding New Elements 14

16. Open-World Abstractions – Groups 16 Group Letters is letter_Spyros, letter_Matt, letter_Cameron Groups of Propositions Letters (sensors) letter_Spyros letter_Matt letter_Cameron Offices (regions) office_Spyros office_Matt office_Cameron

17. Open-World Abstractions – Quantifiers 17 Quantification over Groups of propositions – all Letters letter_Spyros letter_Matt letter_Cameron all Letters

18. Open-World Abstractions – Quantifiers 18 Quantification over Groups of propositions – any Letters letter_Spyros letter_Matt letter_Cameron any Letters

19. Open-World Abstractions – Quantifiers 19 Quantification over Groups of propositions – each Offices office_Spyros office_Matt office_Cameron Go to each Office • Go to office_Spyros • Go to office_Matt • Go to office_Cameron

20. Open-World Abstractions – Correspondence 20 Correspondence between Propositions Letters letter_Spyros letter_Matt letter_Cameron Offices office_Spyros office_Matt office_Cameron

21. Open-World Abstractions – Correspondence 21 Letters correspond to Offices If you are sensing any Letter then go to the corresponding Office Correspondence between Propositions

22. Open-World Abstractions – Example 22 What about a new proposition, say, letter3?

24. Letters letter_Spyros letter_Matt letter_Cameron Offices office_Spyros office_Matt office_Cameron Adding new propositions 24 letter_Hadas

25. Adding new propositions 25 If you are sensing newLetter then add to group Letters

27. Resynthesis 27 If you are sensing newLetter then add to group Letters and resynthesize Global Resynthesis S. Sarid, B. Xu, and H. Kress-Gazit, “Guaranteeing high-level behaviors while exploring partially known maps,” RSS, 2012

28. Summary of our Approach 28

29. Simulation in LTLMoP* – Mission 29 “Patrol, and deliver letters to their recipients’ offices.” *Linear Temporal Logic MissiOn Planning (ltlmop.github.io)

30. Simulation in LTLMoP – Execution 30

31. Implementing an open-world mailbot 31 Abhishek Sriraman, Undergraduate Research Project (Spring 2014)

32. Summary & Future Work 32 Summary • Open-world abstractions allow implicit reference to propositions • New elements are automatically incorporated in the specification • Changes reflected in robot’s controller via (global) resynthesis Future Work • Automatic removal of propositions • Efficient resynthesis • Proposition grounding

33. Open-World Mission Specification for Reactive Robots Spyros Maniatopoulos Matthew Blair, Cameron Finucane, Hadas Kress-Gazit Sibley School of Mechanical and Aerospace Engineering Cornell University sm2296@cornell.edu verifiablerobotics.com