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Collaborative Autonomy Between High-Level Behaviors and Human Operators for Control of Complex Tasks with Different Humanoid Robots

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Book cover The DARPA Robotics Challenge Finals: Humanoid Robots To The Rescue

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 121))

Abstract

This chapter discusses the common reactive high-level behavioral control system used by Team ViGIR and Team Hector on separate robots in the 2015 DARPA Robotics Challenge (DRC) Finals. We present an approach that allows one or more human operators to share control authority with a high-level behavior controller in the form of a finite state machine (automaton). This collaborative autonomy leverages the relative strengths of the robotic system and the (remote) human operators; it increases reliability of the human-robot team performance and decreases the task completion time. This approach is well-suited to disaster scenarios due to the unstructured nature of the environment. The system allows the operators to adjust the robotic system’s autonomy on-the-fly in response to changing circumstances, and to modify pre-defined behaviors as needed. To enable these high-level behaviors, we introduce our system designs for several of the lower-level system capabilities such as footstep planning and template-based object manipulation. We evaluate the proposed approach in the context of our two teams’ participation in the DRC Finals using two different humanoid platforms, and in systematic experiments conducted in the lab afterward. We present a discussion about the lessons learned during the DRC, especially those related to transitioning between operator-centered control and behavior-centered control during competition. Finally, we describe ongoing research beyond the DRC that extends the systems developed during the DRC. All of our described software is available as open source software.

Portions of this chapter used by permission of Wiley from Romay, A., Kohlbrecher, S., Stumpf, A., von Stryk, O., Maniatopoulos, S., Kress-Gazit, H., Schillinger, P. and Conner, D. C. (2017), Collaborative Autonomy between High-level Behaviors and Human Operators for Remote Manipulation Tasks using Different Humanoid Robots. J. Field Robotics, 34: 333358. http://dx.doi.org/doi:10.1002/rob.21671.

A version of this article was previously published in the Journal of Field Robotics, vol. 34, issue 2, pp. 333–358, ©Wiley 2017.

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Notes

  1. 1.

    http://torc.ai/team-vigir-overview/ (accessed 11-Aug-2017).

  2. 2.

    http://www.torc.ai (accessed 11-Aug-2017).

  3. 3.

    http://www.sim.informatik.tu-darmstadt.de/en (accessed 11-Aug-2017).

  4. 4.

    http://research.cs.vt.edu/3di (accessed 11-Aug-2017).

  5. 5.

    http://mime.oregonstate.edu/research/rhcs (accessed 11-Aug-2017).

  6. 6.

    http://verifiablerobotics.com (accessed 11-Aug-2017).

  7. 7.

    https://www.irt.uni-hannover.de (accessed 11-Aug-2017).

  8. 8.

    http://www.teamhector.de (accessed 11-Aug-2017).

  9. 9.

    http://github.com/team-vigir (accessed 11-Aug-2017).

  10. 10.

    http://github.com/team-vigir/vigir_install/wiki (accessed 11-Aug-2017).

  11. 11.

    The term has also been used in a different context, that of a human operating a team of unmanned vehicles.

  12. 12.

    http://wiki.ros.org/actionlib (accessed 11-Aug-2017).

  13. 13.

    http://wiki.ros.org/ros_controllers (accessed 11-Aug-2017).

  14. 14.

    https://youtu.be/7Qv__bLa3j4 and https://youtu.be/vAtqVKGWvFM (accessed 11-Aug-2017).

  15. 15.

    http://moveit.ros.org (accessed 11-Aug-2017).

  16. 16.

    https://github.com/team-vigir/vigir_manipulation_planning (accessed 11-Aug-2017).

  17. 17.

    http://wiki.ros.org/rviz (accessed 11-Aug-2017).

  18. 18.

    http://wiki.ros.org/rqt (accessed 11-Aug-2017).

  19. 19.

    http://www.ogre3d.org/ (accessed 11-Aug-2017).

  20. 20.

    http://www.qt.io/ (accessed 11-Aug-2017).

  21. 21.

    We will omit “implementation”, whenever the meaning is unambiguous, for the sake of brevity.

  22. 22.

    https://github.com/team-vigir/flexbe_behavior_engine (accessed 11-Aug-2017).

  23. 23.

    https://github.com/FlexBE/flexbe_app (accessed 11-Aug-2017).

  24. 24.

    https://github.com/team-vigir/vigir_behaviors (accessed 11-Aug-2017).

  25. 25.

    We are assuming that the \(\mathtt {failed}\) transition’s autonomy threshold is such that it is not executed autonomously.

  26. 26.

    http://youtu.be/kX4rNbo5UYk (accessed 11-Aug-2017).

  27. 27.

    Many of these steps are open to automation given additional development time.

  28. 28.

    DARPA’s planned degradation of wireless communications was between the OCS and the field computer(s).

  29. 29.

    https://www.youtube.com/watch?v=5bSwwnQXfgQ (accessed 11-Aug-2017).

  30. 30.

    http://www.argos-challenge.com/en (accessed 11-Aug-2017).

  31. 31.

    http://www.total.com/en (accessed 11-Aug-2017).

  32. 32.

    That is, the correct-by-construction automaton guarantees the system behavior provided the environment does not violate the assumptions encoded in its specification.

  33. 33.

    For online specification during system operation the initial conditions could be detected automatically, but our system does not currently do this.

  34. 34.

    https://github.com/team-vigir/vigir_behavior_synthesis (accessed 11-Aug-2017).

  35. 35.

    https://github.com/team-vigir/ReSpeC (accessed 11-Aug-2017).

  36. 36.

    This was not included as a precondition of any of the actions.

  37. 37.

    https://github.com/team-vigir/vigir_behavior_synthesis/blob/master/vigir_sm_generation/src/vigir_sm_generation/configs/atlas.yaml and https://github.com/team-vigir/ReSpeC/blob/master/src/respec/config/atlas_config.yaml (accessed 11-Aug-2017).

  38. 38.

    One could argue that the robot should be switched into manipulate mode prior to planning the trajectory due to subtle shifts in pelvis position between stand and manipulate modes; however, this precondition for planning was not specified in our discrete abstraction. It would be up to the system designer to specify this is a required precondition.

  39. 39.

    https://www.youtube.com/watch?v=mez-7pegxuE (accessed 11-Aug-2017).

  40. 40.

    http://wiki.ros.org/navigation (accessed 11-Aug-2017).

  41. 41.

    https://github.com/CNURobotics/flexible_navigation (accessed 11-Aug-2017).

  42. 42.

    http://wiki.ros.org/global_planner (accessed 11-Aug-2017).

  43. 43.

    http://wiki.ros.org/base_local_planner (accessed 11-Aug-2017).

  44. 44.

    http://wiki.ros.org/actionlib (accessed 11-Aug-2017).

  45. 45.

    Videos of the demonstrations can be found at https://www.youtube.com/playlist?list=PLg9fIiOWSqkF27QpB3nUTO9U2XXkX3jBV (accessed 11-Aug-2017).

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Acknowledgements

This project was supported in part by the Defense Advanced Research Projects Agency (DARPA) under Air Force Research Lab (AFRL) contract FA8750-12-C-0337 to TORC Robotics; Team ViGIR would like to thank TORC Robotics for their support and overall project management. Team Hector would like to thank TORC Robotics for opening their doors and providing logistical support during final testing and transportation. Team ViGIR and Team Hector would like to thank all team members; their contribution and support enabled the realization of this work. We would also like to thank DARPA and its support staff for a well run competition, Boston Dynamics, Inc. for their support with the Atlas robot, ROBOTIS, Inc. for their support with THORMANG robot, and the Open Source Robotics Foundation (OSRF) for their support of ROS and Gazebo. The teams would also like to thank the contributors and maintainers of MoveIt! and the SMACH High-level Executive.

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Authors and Affiliations

  1. Capable Humanitarian Robotics & Intelligent Systems Lab, Department of Physics, Computer Science and Engineering, Christopher Newport University, Newport News, VA, 23606, USA

    David C. Conner

  2. Simulation, Systems Optimization and Robotics Group, Department of Computer Science, Technische Universität Darmstadt, Hochschulstrasse 10, 64289, Darmstadt, Hesse, Germany

    Stefan Kohlbrecher, Alberto Romay, Alexander Stumpf & Oskar von Stryk

  3. Bosch Center for Artificial Intelligence, Robert-Bosch-Campus 1, 71272, Renningen, Germany

    Philipp Schillinger

  4. Verifiable Robotics Research Group, School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, 14853, USA

    Spyros Maniatopoulos & Hadas Kress-Gazit

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  1. David C. Conner
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  2. Stefan Kohlbrecher
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  4. Alberto Romay
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  5. Alexander Stumpf
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  6. Spyros Maniatopoulos
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  7. Hadas Kress-Gazit
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  8. Oskar von Stryk
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Correspondence to David C. Conner .

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Editors and Affiliations

  1. The Robotics Lab, Illinois Institute of Technology (IIT), Chicago, Illinois, USA

    Matthew Spenko

  2. High Consequence Automation and Robotics, Sandia National Laboratories, Albuquerque, New Mexico, USA

    Stephen Buerger

  3. Robotic Mobility Group, Massachusetts Institute of Technology, Cambridge, Mississippi, USA

    Karl Iagnemma

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Conner, D.C. et al. (2018). Collaborative Autonomy Between High-Level Behaviors and Human Operators for Control of Complex Tasks with Different Humanoid Robots. In: Spenko, M., Buerger, S., Iagnemma, K. (eds) The DARPA Robotics Challenge Finals: Humanoid Robots To The Rescue. Springer Tracts in Advanced Robotics, vol 121. Springer, Cham. https://doi.org/10.1007/978-3-319-74666-1_12

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  • DOI: https://doi.org/10.1007/978-3-319-74666-1_12

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