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Team THOR’s Entry in the DARPA Robotics Challenge Finals 2015

  • Stephen G. McGill
  • Seung-Joon Yi
  • Hak Yi
  • Min Sung Ahn
  • Sanghyun Cho
  • Kevin Liu
  • Daniel Sun
  • Bhoram Lee
  • Heejin Jeong
  • Jinwook Huh
  • Dennis Hong
  • Daniel D. Lee
Chapter
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 121)

Abstract

This paper describes Team THOR’s approach to human-in-the-loop disaster response robotics for the 2015 DARPA Robotics Challenge (DRC) Finals. Under the duress of unpredictable networking and terrain, fluid operator interactions and dynamic disturbance rejection become major concerns for effective teleoperation. We present a humanoid robot designed to effectively traverse a disaster environment while allowing for a wide range of manipulation abilities. To complement the robot hardware, a hierarchical software foundation implements network strategies that provide real-time feedback to an operator under restricted bandwidth using layered user interfaces. Our strategy for humanoid locomotion includes a backward facing knee configuration paired with specialized toe and heel lifting strategies that allow the robot to traverse difficult surfaces while rejecting external perturbations. With an upper body planner that encodes operator preferences, predictable motion plans are executed in unforeseen circumstances that are critical for manipulation in unknown environments. Our approach was validated during the DRC Finals competition, where Team THOR scored three points in 18 min of operation time, and the results are presented with analysis of each task.

References

  1. Burke, J. L., Murphy, R. R., Rogers, E., Lumelsky, V. J., & Scholtz, J. (2004). Final report for the DARPA/NSF interdisciplinary study on human-robot interaction. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 34(2), 103–112.CrossRefGoogle Scholar
  2. Buss, S. R., & Kim, J. S. (2005). Selectively damped least squares for inverse kinematics. Journal of Graphics, GPU, and Game Tools, 10(3), 37–49.  https://doi.org/10.1080/2151237X.2005.10129202.CrossRefGoogle Scholar
  3. Chang, P. H. (1987). A closed-form solution for inverse kinematics of robot manipulators with redundancy. IEEE Journal of Robotics and Automation, 3(5), 393–403.  https://doi.org/10.1109/JRA.1987.1087114.CrossRefGoogle Scholar
  4. Chen, F., Taguchi, Y., & Kamat, V. R. (2014). Fast plane extraction in organized point clouds using agglomerative hierarchical clustering. In 2014 IEEE International Conference on Robotics and Automation (ICRA) (pp. 6218–6225).Google Scholar
  5. Cheng, Y. (1995). Mean shift, mode seeking, and clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(8), 790–799.CrossRefGoogle Scholar
  6. Chiaverini, S. (1997). Singularity-robust task-priority redundancy resolution for real-time kinematic control of robot manipulators. IEEE Transactions on Robotics and Automation, 13(3), 398–410.  https://doi.org/10.1109/70.585902.CrossRefGoogle Scholar
  7. Cohen, B., Chitta, S., & Likhachev, M. (2014). Single- and dual-arm motion planning with heuristic search. The International Journal of Robotics Research, 33(2), 305–320.  https://doi.org/10.1177/0278364913507983.CrossRefGoogle Scholar
  8. Fankhauser, P., Bloesch, M., Rodriguez, D., Kaestner, R., Hutter, M., & Siegwart, R. (2015). Kinect v2 for mobile robot navigation: Evaluation and modeling. In 2015 International Conference on Advanced Robotics (ICAR) (pp. 388–394).Google Scholar
  9. Goodrich, M. A., & Schultz, A. C. (2007). Human-robot interaction: A survey. Foundations and Trends in Human-Computer Interaction, 1(3), 203–275.CrossRefGoogle Scholar
  10. Hebert, P., Bajracharya, M., Ma, J., Hudson, N., Aydemir, A., Reid, J., et al. (2015). Mobile manipulation and mobility as manipulationdesign and algorithms of robosimian. Journal of Field Robotics, 32(2), 255–274.CrossRefGoogle Scholar
  11. Heger, F. W., & Singh, S. (2006). Sliding autonomy for complex coordinated multi-robot tasks: Analysis & experiments.Google Scholar
  12. Hollerbach, J. M. (1985). Optimum kinematic design for a seven degree of freedom manipulator. In Robotics Research: The Second International Symposium (pp. 215–222). Cambridge: MIT Press.Google Scholar
  13. Holz, D., Holzer, S., Rusu, R. B., & Behnke, S. (2011). Real-time plane segmentation using RGB-D cameras. In RoboCup 2011: Robot Soccer World Cup XV (pp. 306–317). Springer.Google Scholar
  14. Jeong, H., & Lee, D. D. (2016). Learning complex stand-up motion for humanoid robots. In Proceedings of the 30th Association for the Advancement of Artificial Intelligence (AAAI 2016).Google Scholar
  15. Johnson, M., Shrewsbury, B., Bertrand, S., Wu, T., Duran, D., Floyd, M., et al. (2015). Team IHMC’s lessons learned from the DARPA robotics challenge trials. Journal of Field Robotics, 32(2), 192–208.CrossRefGoogle Scholar
  16. Klein, C., & Huang, C. H. (1983). Review of pseudoinverse control for use with kinematically redundant manipulators. IEEE Transactions on Systems, Man and Cybernetics, SMC-13(2), 245–250.  https://doi.org/10.1109/TSMC.1983.6313123.CrossRefGoogle Scholar
  17. Kohlbrecher, S., Romay, A., Stumpf, A., Gupta, A., von Stryk, O., Bacim, F., et al. (2015). Human-robot teaming for rescue missions: Team ViGIR’s approach to the 2013 DARPA robotics challenge trials. Journal of Field Robotics, 32(3), 352–377.CrossRefGoogle Scholar
  18. Lloyd, J. E., & Hayward, V. (2001). Singularity-robust trajectory generation. The International Journal of Robotics Research, 20(1), 38–56.  https://doi.org/10.1177/02783640122067264.CrossRefGoogle Scholar
  19. Michel, O. (2004). WebotsTM: Professional mobile robot simulation. http://arxiv.org/abs/cs/0412052.
  20. Murphy, R. R. (2015). Meta-analysis of autonomy at the DARPA robotics challenge trials. Journal of Field Robotics, 32(2), 189–191.CrossRefGoogle Scholar
  21. Na, M., Yang, B., & Jia, P. (2008). Improved damped least squares solution with joint limits, joint weights and comfortable criteria for controlling human-like figures. In 2008 IEEE Conference on Robotics, Automation and Mechatronics (pp. 1090–1095). IEEE.  https://doi.org/10.1109/RAMECH.2008.4681441.
  22. Nakamura, Y., & Hanafusa, H. (1986). Inverse kinematic solutions with singularity robustness for robot manipulator control. Journal of Dynamic Systems, Measurement, and Control, 108(3), 163–171.  https://doi.org/10.1115/1.3143764.CrossRefGoogle Scholar
  23. Nishiwaki, K., Chestnutt, J., & Kagami, S. (2012). Autonomous navigation of a humanoid robot over unknown rough terrain using a laser range sensor. The International Journal of Robotics Research, 31(11), 1251–1262.  https://doi.org/10.1177/0278364912455720.CrossRefGoogle Scholar
  24. Rouleau, M., & Hong, D. (2014). Design of an underactuated robotic end-effector with a focus on power tool manipulation. In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (pp. V05BT08A027–V05BT08A027). American Society of Mechanical Engineers.Google Scholar
  25. Schulman, J., Ho, J., Lee, A., Awwal, I., Bradlow, H., & Abbeel, P. (2013). Finding locally optimal, collision-free trajectories with sequential convex optimization. In Proceedings of Robotics: Science and Systems, Berlin, Germany.Google Scholar
  26. Shimizu, M., Kakuya, H., Yoon, W. K., Kitagaki, K., & Kosuge, K. (2008). Analytical inverse kinematic computation for 7-DOF redundant manipulators with joint limits and its application to redundancy resolution. IEEE Transactions on Robotics, 24(5), 1131–1142.  https://doi.org/10.1109/TRO.2008.2003266.CrossRefGoogle Scholar
  27. Siciliano, B. (1990). Kinematic control of redundant robot manipulators: A tutorial. Journal of Intelligent and Robotic Systems, 3(3), 201–212.CrossRefGoogle Scholar
  28. Slotine, J. J. E. (1985). The robust control of robot manipulators. The International Journal of Robotics Research, 4(2), 49–64.  https://doi.org/10.1177/027836498500400205. http://ijr.sagepub.com/content/4/2/49.abstract.CrossRefGoogle Scholar
  29. Stentz, A., Herman, H., Kelly, A., Meyhofer, E., Haynes, G. C., Stager, D., et al. (2015). CHIMP, the CMU highly intelligent mobile platform. Journal of Field Robotics, 32(2), 209–228.CrossRefGoogle Scholar
  30. Weghe, M. V., Ferguson, D., & Srinivasa, S. S. (2007). Randomized path planning for redundant manipulators without inverse kinematics. In 2007 7th IEEE-RAS International Conference on Humanoid Robots (pp. 477–482). IEEE.  https://doi.org/10.1109/ICHR.2007.4813913.
  31. Yanco, H. A., Norton, A., Ober, W., Shane, D., Skinner, A., & Vice, J. (2015). Analysis of human-robot interaction at the DARPA robotics challenge trials. Journal of Field Robotics, 32(3), 420–444.CrossRefGoogle Scholar
  32. Yi, S. J., Hong, D., & Lee, D. D. (2013). A hybrid walk controller for resource-constrained humanoid robots. In 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids).Google Scholar
  33. Yi, S. J., McGill, S., He, Q., Vadakedathu, L., Yi, H., Cho, S., et al. (2015). Robocup 2014 humanoid adultsize league winner. In RoboCup 2014: Robot World Cup XVIII (pp. 94–105). Springer.CrossRefGoogle Scholar
  34. Yi, S. J., McGill, S. G., Vadakedathu, L., He, Q., Ha, I., Han, J., et al. (2014). Team THOR’s entry in the DARPA robotics challenge trials 2013. Journal of Field Robotics, 32(3), 315–335.  https://doi.org/10.1002/rob.21555.CrossRefGoogle Scholar
  35. Zucker, M., Joo, S., Grey, M. X., Rasmussen, C., Huang, E., Stilman, M., et al. (2015). A general-purpose system for teleoperation of the DRC-HUBO humanoid robot. Journal of Field Robotics, 32(3), 336–351.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Stephen G. McGill
    • 1
  • Seung-Joon Yi
    • 2
  • Hak Yi
    • 3
  • Min Sung Ahn
    • 4
  • Sanghyun Cho
    • 4
  • Kevin Liu
    • 4
  • Daniel Sun
    • 4
  • Bhoram Lee
    • 1
  • Heejin Jeong
    • 1
  • Jinwook Huh
    • 1
  • Dennis Hong
    • 4
  • Daniel D. Lee
    • 1
  1. 1.GRASP LabUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.School of Electrical EngineeringPusan National UniversityBusanSouth Korea
  3. 3.School of Mechanical EngineeringKyungpook National UniversityDaeguSouth Korea
  4. 4.RoMeLa LabUniversity of California at Los AngelesLos AngelesUSA

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