research-article

Terrain-adaptive bipedal locomotion control

Authors:

Zoran PopovićAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 29, Issue 4

Article No.: 72, Pages 1 - 10

https://doi.org/10.1145/1778765.1778809

Published: 26 July 2010 Publication History

Abstract

We describe a framework for the automatic synthesis of biped locomotion controllers that adapt to uneven terrain at run-time. The framework consists of two components: a per-footstep end-effector path planner and a per-timestep generalized-force solver. At the start of each footstep, the planner performs short-term planning in the space of end-effector trajectories. These trajectories adapt to the interactive task goals and the features of the surrounding uneven terrain at run-time. We solve for the parameters of the planner for different tasks in offline optimizations. Using the per-footstep plan, the generalized-force solver takes ground contacts into consideration and solves a quadratic program at each simulation timestep to obtain joint torques that drive the biped. We demonstrate the capabilities of the controllers in complex navigation tasks where they perform gradual or sharp turns and transition between moving forwards, backwards, and sideways on uneven terrain (including hurdles and stairs) according to the interactive task goals. We also show that the resulting controllers are capable of handling morphology changes to the character.

Supplementary Material

JPG File (tp096-10.jpg)

Download
11.19 KB

Supplemental material. (072.zip)

Download
91.59 MB

MP4 File (tp096-10.mp4)

Download
123.13 MB

References

[1]

Abe, Y., da Silva, M., and Popović, J. 2007. Multiobjective control with frictional contacts. In SCA '07: Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation, Eurographics Association, 249--258.

Digital Library

[2]

Abend, W., Bizzi, E., and Morasso, P. 1982. Human Arm Trajectory Formation. Brain 105, 2, 331--348.

[3]

Atkeson, C., and Morimoto, J. 2002. Nonparametric representation of policies and value functions: A trajectory-based approach. In Neural Information Processing Systems 2002.

[4]

Bernstein, N. 1967. The Co-ordination and Regulation of Movements. Oxford: Pergamon Press.

[5]

Bullock, D., and Grossberg, S. 1988. Neural dynamics of planned arm movements: Emergent invariants and speed-accuracy properties during trajectory formation. Psychological Review 95, 1, 49--90.

[6]

Carey, T. S., and Crompton, R. H. 2005. The metabolic costs of 'bent-hip, bent-knee' walking in humans. Journal of Human Evolution 48, 1, 25--44.

[7]

Chestnutt, J., Kuffner, J., Nishiwaki, K., and Kagami, S. 2003. Planning biped navigation strategies in complex environments. In Proceedings of the 2003 International Conference on Humanoid Robots.

[8]

Coros, S., Beaudoin, P., Yin, K. K., and van de Pann, M. 2008. Synthesis of constrained walking skills. ACM Transactions on Graphics 27, 5 (Dec.), 113:1--113:9.

Digital Library

[9]

Coros, S., Beaudoin, P., and van de Panne, M. 2009. Robust task-based control policies for physics-based characters. ACM Transactions on Graphics 28, 5 (Dec.), 170:1--170:9.

Digital Library

[10]

Craig, J. J. 1989. Introduction to Robotics: Mechanics and Control. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA.

Digital Library

[11]

da Silva, M., Abe, Y., and Popović, J. 2008. Simulation of human motion data using short-horizon model-predictive control. Computer Graphics Forum 27, 2, 371--380.

[12]

Farley, C. T., and Gonzlez, O. 1996. Leg stiffness and stride frequency in human running. Journal of Biomechanics 29, 2, 181--186.

[13]

Hansen, N. 2006. The CMA evolution strategy: a comparing review. In Towards a new evolutionary computation. Advances on estimation of distribution algorithms, J. Lozano, P. Larranaga, I. Inza, and E. Bengoetxea, Eds. Springer, 75--102.

[14]

Hauser, K., Bretl, T., Latombe, J.-C., Harada, K., and Wilcox, B. 2008. Motion Planning for Legged Robots on Varied Terrain. The International Journal of Robotics Research 27, 11--12, 1325--1349.

[15]

Hodgins, J. K., Wooten, W. L., Brogan, D. C., and O'Brien, J. F. 1995. Animating human athletics. In Proceedings of SIGGRAPH 95, ACM, Computer Graphics Proceedings, Annual Conference Series, 71--78.

Digital Library

[16]

Khatib, O. 1987. A unified approach for motion and force control of robot manipulators: The operational space formulation. Robotics and Automation, IEEE Journal of 3, 1 (Feb.), 43--53.

[17]

Kuffner, J. J., J., Nishiwaki, K., Kagami, S., Inaba, M., and Inoue, H. 2001. Footstep planning among obstacles for biped robots. In Intelligent Robots and Systems, 2001. Proceedings. 2001 IEEE/RSJ International Conference on, vol. 1, 500--505.

[18]

Laszlo, J., van de Panne, M., and Fiume, E. 1996. Limit cycle control and its application to the animation of balancing and walking. In Proceedings of SIGGRAPH 96, ACM, Computer Graphics Proceedings, Annual Conference Series, 155--162.

Digital Library

[19]

Liu, C. K., Hertzmann, A., and Popović, Z. 2005. Learning physics-based motion style with nonlinear inverse optimization. ACM Transactions on Graphics 24, 3 (Jul.), 1071--1081.

Digital Library

[20]

Mosek ApS, 2009. The mosek optimization software version 6.0. http://www.mosek.com/.

[21]

Muico, U., Lee, Y., Popović, J., and Popović, Z. 2009. Contact-aware nonlinear control of dynamic characters. ACM Transactions on Graphics 28, 3 (Aug.), 81:1--81:9.

Digital Library

[22]

Nocedal, J., and Wright, S. J. 2006. Numerical Optimization, 2nd ed. Springer.

[23]

NVIDIA Corporation, 2008. NVIDIA PhysX SDK version 2.8.1. http://developer.nvidia.com/object/physx.html.

[24]

Pratt, J., Dilworth, P., and Pratt, G. 1997. Virtual model control of a bipedal walking robot. In IEEE Conference on Robotics and Automation, 193--198.

[25]

Raibert, M. H., and Hodgins, J. K. 1991. Animation of dynamic legged locomotion. In Computer Graphics (Proceedings SIGGRAPH 91), ACM, 349--358.

Digital Library

[26]

Rose, C., Guenter, B., Bodenheimer, B., and Cohen, M. F. 1996. Efficient generation of motion transitions using spacetime constraints. In Proceedings of SIGGRAPH 96, ACM, Computer Graphics Proceedings, Annual Conference Series, 147--154.

Digital Library

[27]

Safonova, A., Hodgins, J. K., and Pollard, N. S. 2004. Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces. ACM Transactions on Graphics 23, 3 (Aug.), 514--521.

Digital Library

[28]

Stewart, A. J., and Cremer, J. F. 1992. Animation of 3d human locomotion: climbing stairs and descending stairs. In Eurographics Workshop on Animation and Simulation, 152--168.

[29]

Sun, H. C., and Metaxas, D. N. 2001. Automating gait generation. In Proceedings of SIGGRAPH 2001, ACM, Computer Graphics Proceedings, Annual Conference Series, 261--270.

Digital Library

[30]

Todorov, E. 2004. Optimality principles in sensorimotor control. Nature Neuroscience 7, 9 (Sep.), 907--915.

[31]

van de Panne, M., and Lamouret, A. 1995. Guided optimization for balanced locomotion. In 6th Eurographics Workshop on Animation and Simulation, Computer Animation and Simulation, September, 1995, Springer, Maastricht, Pays-Bas, D. Terzopoulos and D. Thalmann, Eds., Eurographics, 165--177.

[32]

van de Panne, M., Fiume, E., and Vranesic, Z. 1992. A controller for the dynamic walk of a biped across variable terrain. In Decision and Control, 1992., Proceedings of the 31st IEEE Conference on, 2668--2673 vol.3.

[33]

Wampler, K., and Popović, Z. 2009. Optimal gait and form for animal locomotion. ACM Transactions on Graphics 28, 3 (Aug.), 60:1--60:8.

Digital Library

[34]

Wang, J. M., Fleet, D. J., and Hertzmann, A. 2009. Optimizing walking controllers. ACM Transactions on Graphics 28, 5 (Dec.), 168:1--168:8.

Digital Library

[35]

Yin, K., Loken, K., and van de Panne, M. 2007. SIMBICON: simple biped locomotion control. ACM Transactions on Graphics 26, 3 (Jul.), 105:1--105:10.

Digital Library

[36]

Yin, K., Coros, S., Beaudoin, P., and van de Panne, M. 2008. Continuation methods for adapting simulated skills. ACM Transactions on Graphics 27, 3 (Aug.), 81:1--81:7.

Digital Library

[37]

Zhang, L., Pan, J., and Manocha, D. 2009. Motion planning of human-like robots using constrained coordination. In Humanoid Robots, 2009. Humanoids 2009. 9th IEEE-RAS International Conference on, 188--195.

Cited By

Wang KHu ZTisnikar PHelander OChappell DKormushev P(2024)When and where to step: Terrain-aware real-time footstep location and timing optimization for bipedal robotsRobotics and Autonomous Systems10.1016/j.robot.2024.104742179(104742)Online publication date: Sep-2024
https://doi.org/10.1016/j.robot.2024.104742
Ahn JIm ELee Y(2023)Learning Impulse-Reduced Gait for Quadruped Robot using CMA-ES2023 20th International Conference on Ubiquitous Robots (UR)10.1109/UR57808.2023.10202519(261-266)Online publication date: 25-Jun-2023
https://doi.org/10.1109/UR57808.2023.10202519
Gibson GDosunmu-Ogunbi OGong YGrizzle J(2022)Terrain-Adaptive, ALIP-Based Bipedal Locomotion Controller via Model Predictive Control and Virtual Constraints2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS47612.2022.9981969(6724-6731)Online publication date: 23-Oct-2022
https://doi.org/10.1109/IROS47612.2022.9981969
Show More Cited By

Index Terms

Terrain-adaptive bipedal locomotion control
1. Computing methodologies
  1. Computer graphics
    1. Animation

Recommendations

Terrain-adaptive bipedal locomotion control
SIGGRAPH '10: ACM SIGGRAPH 2010 papers

We describe a framework for the automatic synthesis of biped locomotion controllers that adapt to uneven terrain at run-time. The framework consists of two components: a per-footstep end-effector path planner and a per-timestep generalized-force solver. ...
End-effector control for bipedal locomotion
A Control Strategy for Terrain Adaptive Bipedal Locomotion

Rhythmic movements of a five-link sagittal biped with muscle-like actuators are considered. In walking, as the support phases change contact is periodically made with the environment. The inputs to every actuator are modeled after the inputs to muscles in ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 29, Issue 4

July 2010

942 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/1778765

Issue’s Table of Contents

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 July 2010

Published in TOG Volume 29, Issue 4

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

58
Total Citations
View Citations
1,392
Total Downloads

Downloads (Last 12 months)26
Downloads (Last 6 weeks)6

Reflects downloads up to 13 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Wang KHu ZTisnikar PHelander OChappell DKormushev P(2024)When and where to step: Terrain-aware real-time footstep location and timing optimization for bipedal robotsRobotics and Autonomous Systems10.1016/j.robot.2024.104742179(104742)Online publication date: Sep-2024
https://doi.org/10.1016/j.robot.2024.104742
Ahn JIm ELee Y(2023)Learning Impulse-Reduced Gait for Quadruped Robot using CMA-ES2023 20th International Conference on Ubiquitous Robots (UR)10.1109/UR57808.2023.10202519(261-266)Online publication date: 25-Jun-2023
https://doi.org/10.1109/UR57808.2023.10202519
Gibson GDosunmu-Ogunbi OGong YGrizzle J(2022)Terrain-Adaptive, ALIP-Based Bipedal Locomotion Controller via Model Predictive Control and Virtual Constraints2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS47612.2022.9981969(6724-6731)Online publication date: 23-Oct-2022
https://doi.org/10.1109/IROS47612.2022.9981969
Kim YLee S(2021)Keyframe-based multi-contact motion synthesisThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-020-01956-937:7(1949-1963)Online publication date: 1-Jul-2021
https://dl.acm.org/doi/10.1007/s00371-020-01956-9
Tang YTan JHarada T(2020)Learning Agile Locomotion via Adversarial Training2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS45743.2020.9341777(6098-6105)Online publication date: 24-Oct-2020
https://doi.org/10.1109/IROS45743.2020.9341777
Bermudez LTessendorf JZimmermann DZordan VCharalambous PChrysanthou YJones BLee J(2018)Real-time locomotion with character-fluid interactionsProceedings of the 11th ACM SIGGRAPH Conference on Motion, Interaction and Games10.1145/3274247.3274515(1-8)Online publication date: 8-Nov-2018
https://dl.acm.org/doi/10.1145/3274247.3274515
Yu WTurk GLiu C(2018)Learning symmetric and low-energy locomotionACM Transactions on Graphics10.1145/3197517.320139737:4(1-12)Online publication date: 30-Jul-2018
https://dl.acm.org/doi/10.1145/3197517.3201397
Hwang JKim JSuh IKwon T(2018)Real‐time Locomotion Controller using an Inverted‐Pendulum‐based Abstract ModelComputer Graphics Forum10.1111/cgf.1336137:2(287-296)Online publication date: 22-May-2018
https://doi.org/10.1111/cgf.13361
Lee YKwon T(2017)Performance-Based Biped Control using a Consumer Depth CameraComputer Graphics Forum10.5555/3128975.312901036:2(387-395)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.5555/3128975.3129010
Zhao YFernandez BSentis L(2017)Robust optimal planning and control of non-periodic bipedal locomotion with a centroidal momentum modelInternational Journal of Robotics Research10.1177/027836491773060236:11(1211-1242)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1177/0278364917730602
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents