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Recent Progress in Legged Robots Locomotion Control

  • Humanoid and Bipedal Robotics (E Yoshida, Section Editor)
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Abstract

Purpose of review

In recent years, legged robots locomotion has been transitioning from mostly flat ground in controlled settings to generic indoor and outdoor environments, approaching now real industrial scenarios. This paper aims at documenting some of the key progress made in legged locomotion control that enabled this transition.

Recent findings

Legged locomotion control makes extensive use of numerical trajectory optimization and its online implementation, model predictive control. A key progress has been how this optimization is handled, with refined models and refined numerical methods. This led the legged locomotion research community to heavily invest in and contribute to the development of new optimization methods and efficient numerical software.

Summary

We present an overview of the typical approach to legged locomotion control, which involves primarily planning a sequence of contacts with the environment and computing a corresponding dynamically feasible trajectory of the Center of Mass of the robot. We then detail recent progress in contact planning and trajectory optimization with either the full Lagrangian dynamics of legged robots or with reduced models.

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References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Waldron KJ, McGhee RB. The adaptive suspension vehicle. IEEE Control Syst Mag 1986;6: 7–12.

    Article  Google Scholar 

  2. Carpentier J, Benallegue M, Mansard N, Laumond J-P. Center of mass estimation for polyarticulated system in contact — a spectral approach. IEEE Trans Robot 2016;32(4):810–22.

    Article  Google Scholar 

  3. Vukobratović MK. Contribution to the study of anthropomorphic systems. Kybernetika 1972; 8(5):404–18.

    MATH  Google Scholar 

  4. Wieber P-B. Holonomy and nonholonomy in the dynamics of articulated motion. Proceedings of the Ruperto Carola symposium on fast motion in biomechanics and robotics; 2005.

  5. Orin DE, Goswami A, Lee S-H. Centroidal dynamics of a humanoid robot. Auton Robot 2013;35(2-3):161–76.

    Article  Google Scholar 

  6. Wieber P-B. On the stability of walking systems. Proceedings of the international workshop on humanoids and human friendly robots; 2002.

  7. Pratt J, Tedrake R. Velocity based stability margins for fast bipedal walking. Proceedings of the Ruperto Carola symposium on fast motion in biomechanics and robotics; 2005.

  8. Wieber P-B, Tedrake R, Kuindersma S. Modeling and control of legged robots. Handbook of robotics, chap 48. In: Siciliano B and Khatib O, editors. 2nd edn. Springer; 2016. p. 1203–34.

  9. Bretl T. Motion planning of multi-limbed robots subject to equilibrium constraints: the free-climbing robot problem. Int J Robot Res 2006;25(4):317–42.

    Article  Google Scholar 

  10. Hauser K, Bretl T, Latombe J-C, Harada K, Wilcox B. 2008. Motion planning for legged robots on varied terrain. Int J Robot Res.

  11. Escande A, Kheddar A, Miossec S. Planning contact points for humanoid robots. Robot Auton Syst 2013;61(5):428–42.

    Article  Google Scholar 

  12. Feng S, Xinjilefu X, Atkeson CG, Kim J. Robust dynamic walking using online foot step optimization. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2016.

  13. Kajita S, Kanehiro F, Kaneko K, Fujiwara K, Harada K, Yokoi K, Hirukawa H. Biped walking pattern generation by using preview control of zero moment point. Proceedings of the IEEE international conference on robotics & automation; 2003. p. 1620–26.

  14. Wieber P-B. Trajectory free linear model predictive control for stable walking in the presence of strong perturbations. Proceedings of the IEEE-RAS international conference on humanoid robots; 2006.

  15. Fernbach P, Tonneau S, Stasse O, Carpentier J, Taïx M. c-CROC: Continuous and convex resolution of centroidal dynamic trajectories for legged robots in multicontact scenarios. IEEE Trans Robot 2020;36(3):676–91.

    Article  Google Scholar 

  16. Sardain P, Bessonnet G. Forces acting on a biped robot. Center of pressure—zero moment point. IEEE Trans Sys Man Cybern – Part A 2004;34(5):630–37.

    Article  Google Scholar 

  17. Caron S, Pham Q-C, Nakamura Y. ZMP support areas for multi-contact mobility under frictional constraints. IEEE Trans Robot 2017;33(1):67–80.

    Article  Google Scholar 

  18. Kajita S, Tani K. Study of dynamic biped locomotion on rugged terrain – derivation and application of the linear inverted pendulum mode. Proceedings of the IEEE international conference on robotics & automation; 1991. p. 1405–11.

  19. Seyde T, Shrivastava A, Englsberger J, Bertrand S, Pratt J, Griffin R. Inclusion of angular momentum during planning for capture point based walking. Proceedings of the IEEE international conference on robotics & automation; 2018. p. 1791–98.

  20. Koolen T, de Boer T, Rebula J, Goswami A, Pratt J. Capturability-based analysis and control of legged locomotion, part 1: Theory and application to three simple gait models. Int J Robot Res 2012; 31(9):1094–1113.

    Article  Google Scholar 

  21. Kajita S, Kanehiro F, Kaneko K, Fujiwara K, Harada K, Yokoi K, Hirukawa H. Resolved momentum control: Humanoid motion planning based on the linear and angular momentum. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2003. p. 1644–50.

  22. Wieber P-B. Constrained dynamics and parametrized control in biped walking. Proceedings of the international symposium on mathematical theory of networks and systems; 2000.

  23. Fujimoto Y, Kawamura A. Simulation of an autonomous biped walking robot including environmental force interaction. IEEE Robot Autom Mag 1998;5(2):33–41.

    Article  Google Scholar 

  24. Kuindersma S, Permenter F, Tedrake R. An efficiently solvable quadratic program for stabilizing dynamic locomotion. Proceedings of the IEEE international conference on robotics & automation; 2014. p. 2589–94.

  25. Escande A, Mansard N, Wieber P-B. Hierarchical quadratic programming: Fast online humanoid-robot motion generation. Int J Robot Res 2014;33(7):1006–28.

    Article  Google Scholar 

  26. Wieber P-B, Escande A, Dimitrov D, Sherikov A. Geometric and numerical aspects of redundancy. Geometric and numerical foundations of movements. In: Laumond J-P, Mansard N, and Lasserre J-B, editors. Springer International Publishing; 2017. p. 67–85.

  27. Henze B, Roa MA, Ott C. 2016. Passivity-based whole-body balancing for torque-controlled humanoid robots in multi-contact scenarios. Int J Robot Res.

  28. Mesesan G, Englsberger J, Garofalo G, Ott C, Albu-Schäffer A. Dynamic walking on compliant and uneven terrain using DCM and passivity-based whole-body control. Proceedings of the IEEE-RAS international conference on humanoid robots; 2019.

  29. Kurtz V, Wensing PM, Lin H. 2020. Approximate simulation for template-based whole-body control. IEEE Robot Autom Lett.

  30. Takenaka T, Matsumoto T, Yoshiike T. Real time motion generation and control for biped robot -1st report: Walking gait pattern generation. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2009.

  31. Gouaillier D, Collette C, Kilner C. Omni-directional closed-loop walk for NAO. Proceedings of the IEEE-RAS international conference on humanoid robots; 2010.

  32. •• Kuindersma S. Recent progress on Atlas, the world’s most dynamic humanoid robot. This recorded lecture provides precise details about the complete control design behind Boston Dynamics’ world-leading robot videos. [Online]. Available: https://www.youtube.com/watch?v=EGABAx52GKI.

  33. Bellicoso CD, Jenelten F, Gehring C, Hutter M. Dynamic locomotion through online nonlinear motion optimization for quadrupedal robots. IEEE Robot Autom Lett 2018;3(3):2261–68.

    Article  Google Scholar 

  34. Mastalli C, Focchi M, Havoutis I, Radulescu A, Calinon S, Buchli J, Caldwell DG, Semini C. Trajectory and foothold optimization using low-dimensional models for rough terrain locomotion. Proceedings of the IEEE international conference on robotics & automation; 2017.

  35. Di Carlo J, Wensing PM, Katz B, Bledt G, Kim S. Dynamic locomotion in the MIT Cheetah 3 through convex model predictive control. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2018.

  36. Lafaye J, Gouaillier D, Wieber P-B. Linear model predictive control of the locomotion of Pepper, a humanoid robot with omnidirectional wheels. Proceedings of the IEEE-RAS international conference on humanoid robots; 2014.

  37. Bjelonic M, Sankar PK, Bellicoso CD, Vallery H, Hutter M. Rolling in the deep – hybrid locomotion for wheeled-legged robots using online trajectory optimization. IEEE Robot Autom Lett 2020;5(2): 3626–33.

    Article  Google Scholar 

  38. Klemm V, Morra A, Gulich L, Mannhart D, Rohr D, Kamel M, de Viragh Y, Siegwart R. LQR-Assisted whole-body control of a wheeled bipedal robot with kinematic loops. IEEE Robot Autom Lett 2020;5(2):3745–52.

    Article  Google Scholar 

  39. Lavalle SM. Planning algorithms. Cambridge: Cambridge University Press; 2006.

    Book  Google Scholar 

  40. Deits R, Tedrake R. Footstep planning on uneven terrain with mixed-integer convex optimization. Proceedings of the IEEE-RAS international conference on humanoid robots; 2014.

  41. Ponton B, Herzog A, Schaal S, Righetti L. A convex model of humanoid momentum dynamics for multi-contact motion generation. Proceedings of the IEEE-RAS international conference on humanoid robots; 2016.

  42. Aceituno-Cabezas B, Mastalli C, Dai H, Focchi M, Radulescu A, Caldwell DG, Cappelletto J, Grieco JC, Fernández-López G, Semini C. Simultaneous contact, gait, and motion planning for robust multilegged locomotion via mixed-integer convex optimization. IEEE Robot Autom Lett 2017;3 (3):2531–38.

    Google Scholar 

  43. Perrin N, Ott C, Englsberger J, Stasse O, Lamiraux F, Caldwell DG. Continuous legged locomotion planning. IEEE Trans Robot 2016;33(1):234–39.

    Article  Google Scholar 

  44. Carpentier J, Tonneau S, Naveau M, Stasse O, Mansard N. A versatile and efficient pattern generator for generalized legged locomotion. Proceedings of the IEEE international conference on robotics & automation. IEEE; 2016. p. 3555–61.

  45. Tonneau S, Del Prete A, Pettré J, Park C, Manocha D, Mansard N. An efficient acyclic contact planner for multiped robots. IEEE Trans Robot 2018;34(3):586–601.

    Article  Google Scholar 

  46. Kajita S, Morisawa M, Miura K, Nakaoka S, Harada K, Kaneko K, Kanehiro F, Yokoi K. Biped walking stabilization based on linear inverted pendulum tracking. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2010. p. 4489–96.

  47. Englsberger J, Ott C, Roa MA, Albu-Schäffer A, Hirzinger G. Bipedal walking control based on capture point dynamics. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2011.

  48. Englsberger J, Ott C, Albu-Schaffer A. Three-dimensional bipedal walking control based on divergent component of motion. IEEE Trans Robot 2015;31(2):355–68. [Online]. Available: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7063218.

    Article  Google Scholar 

  49. Khadiv M, Herzog A, Moosavian SAA, Righetti L. Walking control based on step timing adaptation. IEEE Trans Robot 2020;36(3):629–43. [Online]. Available: https://ieeexplore.ieee.org/document/9082021/.

    Article  Google Scholar 

  50. Scianca N, De Simone D, Lanari L, Oriolo G. 2020. MPC for humanoid gait generation: Stability and feasibility. IEEE Trans Robot 36.

  51. Winkler AW, Bellicoso CD, Hutter M, Buchli J. Gait and trajectory optimization for legged systems through phase-based end-effector parameterization. IEEE Robot Autom Lett 2018;3(3):1560–67.

    Article  Google Scholar 

  52. Herzog A, Schaal S, Righetti L. Structured contact force optimization for kino-dynamic motion generation. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2016. p. 2703–10.

  53. Bledt G, Kim S. Extracting legged locomotion heuristics with regularized predictive control. Proceedings of the IEEE international conference on robotics & automation; 2020. p. 406–12.

  54. Bledt G, Kim S. Implementing regularized predictive control for simultaneous real-time footstep and ground reaction force optimization. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2019. p. 6316–23.

  55. Orsolino R, Focchi M, Caron S, Raiola G, Barasuol V, Caldwell DG, Semini C. Feasible region: an actuation-aware extension of the support region. IEEE Trans Robot 2020;36(4):1239–55.

    Article  Google Scholar 

  56. Carpentier J, Mansard N. Multicontact locomotion of legged robots. IEEE Trans Robot 2018; 34(6):1441–60.

    Article  Google Scholar 

  57. Dai H, Valenzuela A, Tedrake R. Whole-body motion planning with centroidal dynamics and full kinematics. Proceedings of the IEEE-RAS international conference on humanoid robots; 2014. p. 295–302.

  58. Herzog A, Rotella N, Schaal S, Righetti L. Trajectory generation for multi-contact momentum control. Proceedings of the IEEE-RAS international conference on humanoid robots; 2015. p. 874–80.

  59. Grandia R, Farshidian F, Ranftl R, Hutter M. Feedback MPC for torque-controlled legged robots. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2019.

  60. Budhiraja R, Carpentier J, Mansard N. Dynamics consensus between centroidal and whole-body models for locomotion of legged robots. Proceedings of the IEEE international conference on robotics & automation. IEEE; 2019. p. 6727–33.

  61. Sherikov A, Dimitrov D, Wieber P-B. Whole body motion controller with long-term balance constraints. Proceedings of the IEEE-RAS international conference on humanoid robots; 2014. p. 444–50.

  62. Posa M, Kuindersma S, Tedrake R. Optimization and stabilization of trajectories for constrained dynamical systems. Proceedings of the IEEE international conference on robotics & automation; 2016.

  63. Hereid A, Hubicki CM, Cousineau EA, Ames AD. Dynamic humanoid locomotion: a scalable formulation for HZD gait optimization. IEEE Trans Robot 2018;34(2):370–87.

    Article  Google Scholar 

  64. Koch KH, Mombaur K, Stasse O, Souè res P. Optimization based exploitation of the ankle elasticity of HRP-2 for overstepping large obstacles. 2014 IEEE-RAS international conference on humanoid robots. IEEE; 2014. p. 733–40.

  65. Diehl M, Bock HG, Diedam H, Wieber P-B. Fast direct multiple shooting algorithms for optimal robot control. Fast motions in biomechanics and robotics. Springer; 2006. p. 65–93.

  66. Mordatch I, Todorov E, Popović Z. Discovery of complex behaviors through contact-invariant optimization. ACM Trans Graph (TOG) 2012;31(4):1–8.

    Article  Google Scholar 

  67. Posa M, Cantu C, Tedrake R. A direct method for trajectory optimization of rigid bodies through contact. Int J Robot Res 2014;33(1):69–81.

    Article  Google Scholar 

  68. Giftthaler M, Neunert M, Stäuble M, Buchli J. The control toolbox — an open-source C++ library for robotics, optimal and model predictive control. 2018 IEEE international conference on simulation, modeling, and programming for autonomous robots (SIMPAR); 2018. p. 123–29.

  69. Howell TA, Jackson BE, Manchester Z. ALTRO: A fast solver for constrained trajectory optimization. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2019. p. 7674–79.

  70. Mastalli C, Budhiraja R, Merkt W, Saurel G, Hammoud B, Naveau M, Carpentier J, Righetti L, Vijayakumar S, Mansard N. Crocoddyl: an efficient and versatile framework for multi-contact optimal control. Proceedings of the IEEE international conference on robotics & automation; 2020. p. 2536–42.

  71. Giftthaler M, Neunert M, Stäuble M, Frigerio M, Semini C, Buchli J. Automatic differentiation of rigid body dynamics for optimal control and estimation. Adv Robot 2017;31(22):1225–37.

    Article  Google Scholar 

  72. Ayusawa K, Yoshida E. Comprehensive theory of differential kinematics and dynamics towards extensive motion optimization framework. Int J Robot Res 2018;37(13-14):1554–72.

    Article  Google Scholar 

  73. Carpentier J, Mansard N. Analytical derivatives of rigid body dynamics algorithms. Robotics: Science and systems (RSS 2018); 2018.

  74. Koenemann J, Prete AD, Tassa Y, Todorov E, Stasse O, Bennewitz M, Mansard N. Whole-body model-predictive control applied to the HRP-2 humanoid. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2015.

  75. Neunert M, Stäuble M, Giftthaler M, Bellicoso CD, Carius J, Gehring C, Hutter M, Buchli J. Whole-body nonlinear model predictive control through contacts for quadrupeds. IEEE Robot Autom Lett 2018;3(3):1458–65.

    Article  Google Scholar 

  76. Hwangbo J, Lee J, Dosovitskiy A, Bellicoso D, Tsounis V, Koltun V, Hutter M. 2019. Learning agile and dynamic motor skills for legged robots. Sci Robot 4(26).

  77. •• Lee J, Hwangbo J, Wellhausen L, Koltun V, Hutter M. 2020. Learning quadrupedal locomotion over challenging terrain. Sci Robot 5(47).

  78. Hwangbo J, Lee J, Hutter M. Per-contact iteration method for solving contact dynamics. IEEE Robot Autom Lett 2018;3(2):895–902.

    Article  Google Scholar 

  79. Geisert M, Del Prete A, Mansard N, Romano F, Nori F. Regularized hierarchical differential dynamic programming. IEEE Trans Robot 2017;33(4):819–33.

    Article  Google Scholar 

  80. Felis ML. RBDL: An efficient rigid-body dynamics library using recursive algorithms. Auton Robot 2017;41(2):495–511.

    Article  Google Scholar 

  81. Carpentier J, Saurel G, Buondonno G, Mirabel J, Lamiraux F, Stasse O, Mansard N. The Pinocchio C++ library – a fast and flexible implementation of rigid body dynamics algorithms and their analytical derivatives. IEEE international symposium on system integrations (SII); 2019.

  82. Koolen T, Deits R. Julia for robotics: simulation and real-time control in a high-level programming language. Proceedings of the IEEE international conference on robotics & automation; 2019. p. 604–11.

  83. Lee J, Grey MX, Ha S, Kunz T, Jain S, Ye Y, Srinivasa SS, Stilman M, Liu CK. DART: Dynamic animation and robotics toolkit. J Open Sour Softw 2018;3(22):500.

    Article  Google Scholar 

  84. Camurri M, Ramezani M, Nobili S, Fallon M. Pronto: A multi-sensor state estimator for legged robots in real-world scenarios. Front Robot AI 2020;7(68):1–18. [Online]. Available: https://www.frontiersin.org/article/10.3389/frobt.2020.00068.

    Google Scholar 

  85. Tedrake R, the Drake Development Team. 2019. Drake: Model-based design and verification for robotics. [Online]. Available: https://drake.mit.edu.

  86. Lapeyre M, Rouanet P, Grizou J, N’Guyen S, Falher AL, Depraetre F, Oudeyer P. Poppy: Open source 3D printed robot for experiments in developmental robotics. Proceedings of the international conference on development and learning and on epigenetic robotics; 2014.

  87. • Grimminger F, Meduri A, Khadiv M, Viereck J, Wüthrich M, Naveau M, Berenz V, Heim S, Widmaier F, Flayols T, Fiene J, Badri-Spröwitz A, Righetti L. An open torque-controlled modular robot architecture for legged locomotion research. IEEE Robot Autom Lett 2020;5(2):3650–57.

    Article  Google Scholar 

  88. Mirabel J, Tonneau S, Fernbach P, Seppälä A-K, Campana M, Mansard N, Lamiraux F. HPP: A new software for constrained motion planning. 2016 IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE; 2016. p. 383–89.

  89. Manuelli L, Tedrake R. Localizing external contact using proprioceptive sensors: the contact particle filter. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2016. p. 5062–69.

  90. Blösch M. 2017. State estimation for legged robots - kinematics, inertial sensing and computer vision. Eidgenössische Technische Hochschule zürich PhD thesis.

  91. Flayols T, Del Prete A, Wensing P, Mifsud A, Benallegue M, Stasse O. Experimental evaluation of simple estimators for humanoid robots. Proceedings of the IEEE-RAS international conference on humanoid robots. IEEE; 2017. p. 889–95.

  92. Rotella N. 2017. Estimation-based control for humanoid robots. University of Southern California PhD thesis.

  93. Fourmy M, Flayols T, Mansard N, Solà J. Contact forces pre-integration for the whole body estimation of legged robots. Proceedings of the IEEE international conference on robotics & automation; 2021.

  94. Samson C, Espiau B. Application of the task-function approach to sensor-based control of robot manipulators. IFAC Proc Vol 1990;123(8, Part 5):269–74.

    Article  Google Scholar 

  95. Del Prete A, Mansard N. Robustness to joint-torque-tracking errors in task-space inverse dynamics. IEEE Trans Robot 2016;32(5):1091–105.

    Article  Google Scholar 

  96. Farshidian F, Jelavić E, Winkler AW, Buchli J. Robust whole-body motion control of legged robots. Proceedings of the IEEE/RSJ international conference on intelligent robots & systems; 2017. p. 4589–96.

  97. Villa NA, Englsberger J, Wieber P-B. Sensitivity of legged balance control to uncertainties and sampling period. IEEE Robot Autom Lett 2019;4(4):6.

    Article  Google Scholar 

  98. Hammoud B, Khadiv M, Righetti L. 2021. Impedance optimization for uncertain contact interactions through risk sensitive optimal control. IEEE Robot Autom Lett.

  99. Kheddar A, Caron S, Gergondet P, Comport A, Tanguy A, Ott C, Henze B, Mesesan G, Englsberger J, Roa MA, Wieber P-B, Chaumette F, Spindler F, Oriolo G, Lanari L, Escande A, Chappellet K, Kanehiro F, Rabaté P. Humanoid robots in aircraft manufacturing: the Airbus use cases. IEEE Robot Autom Mag 2019;26(4):30–45.

    Article  Google Scholar 

  100. Gehring C, Fankhauser P, Isler L, Diethelm R, Bachmann S, Potz M, Gerstenberg L, Hutter M. 2021. ANYMal in the field: Solving industrial inspection of an offshore HVDC platform with a quadrupedal robot. Field Serv Robot 247–60.

  101. Werner A, Henze B, Loeffl F, Leyendecker S, Ott C. Optimal and robust walking using intrinsic properties of a series-elastic robot. Proceedings of the IEEE-RAS international conference on humanoid robots; 2017.

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Acknowledgements

The authors would like to thank Stéphane Caron for discussions that helped shape the present document.

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  1. École normale supérieure, CNRS, PSL Research University, Paris, France

    Justin Carpentier

  2. INRIA, Paris, France

    Justin Carpentier

  3. INRIA Grenoble - Rhône-Alpes, Paris, France

    Pierre-Brice Wieber

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Correspondence to Pierre-Brice Wieber.

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Carpentier, J., Wieber, PB. Recent Progress in Legged Robots Locomotion Control. Curr Robot Rep 2, 231–238 (2021). https://doi.org/10.1007/s43154-021-00059-0

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