Abstract
This paper presents a physics-based locomotion controller based on online planning. At each time-step, a planner optimizes locomotion over multiple phases of gait. Stance dynamics are modeled using a simplified Spring-Load Inverted (SLIP) model, while flight dynamics are modeled using projectile motion equations. Full-body control at each instant is optimized to match the instantaneous plan values, while also maintaining balance. Different types of gaits, including walking, running, and jumping, emerge automatically, as do transitions between different gaits. The controllers can traverse challenging terrain and withstand large external disturbances, while following high-level user commands at interactive rates.
Supplemental Material
- Abe, Y., da Silva, M., and Popović, J. 2007. Multiobjective Control with Frictional Contacts. In Proc. SCA, 249--258. Google ScholarDigital Library
- Adamczyk, P. G., Collins, S. H., and Kuo, A. D. 2006. The advantages of a rolling foot in human walking. J. Exp. Biology 209, 3953--3963.Google ScholarCross Ref
- Alexander, R. M. 1980. Optimum walking techniques for quadrupeds and bipeds. J. Zoology 192, 97--117.Google ScholarCross Ref
- Chestnutt, J. 2007. Navigation Planning for Legged Robots. PhD thesis, Carnegie Mellon University.Google Scholar
- Collins, S., Ruina, A., Tedrake, R., and Wisse, M. 2005. Efficient Bipedal Robots Based on Passive Dynamic Walkers. Science 307, 1082--1085.Google ScholarCross Ref
- Coros, S., Beaudoin, P., and van de Panne, M. 2009. Robust Task-based Control Policies for Physics-based Characters. ACM Trans. Graphics 28, 5, 170. Google ScholarDigital Library
- da Silva, M., Abe, Y., and Popović, J. 2008. Interactive Simulation of Stylized Human Locomotion. ACM Trans. Graphics 27, 3, 82. Google ScholarDigital Library
- da Silva, M., Yeuhi, A., and Popović, J. 2008. Simulation of Human Motion Data using Short-Horizon Model-Predictive Control. Proc. Eurographics 27, 2.Google ScholarCross Ref
- de Lasa, M., Mordatch, I., and Hertzmann, A. 2010. Feature-Based Locomotion Controllers. ACM Trans. Graphics 29, 3. Google ScholarDigital Library
- Faloutsos, P., van de Panne, M., and Terzopoulos, D. 2001. Composable controllers for physics-based character animation. In Proc. SIGGRAPH, 251--260. Google ScholarDigital Library
- Full, R. J., and Koditschek, D. E. 1999. Templates and anchors: Neuromechanical hypotheses of legged locomotion on land. J. Exp. Biology 202, 3325--3332.Google Scholar
- Hansen, N. 2006. The CMA Evolution Strategy: A Comparing Review. In Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms. 75--102.Google Scholar
- Hodgins, J. K., Wooten, W. L., Brogan, D. C., and O'Brien, J. F. 1995. Animating human athletics. In Proc. SIGGRAPH, 71--78. Google ScholarDigital Library
- Kajita, S., Matsumoto, O., and Saigo, M. 2001. Real-time 3D walking pattern generation for a biped robot with telescopic legs. In Proc. ICRA, 2299--2306.Google Scholar
- Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K., and Hirukawa, H. 2003. Biped Walking Pattern Generation by using Preview Control of Zero-Moment Point. In Proc. ICRA, 1620--1626.Google Scholar
- Kuffner, J., Nishikawa, K., Kagami, S., Inaba, M., and Inoue, H. 2003. Motion Planning for Humanoid Robots. In Proc. ISRR, 365--374.Google Scholar
- Laszlo, J., van de Panne, M., and Fiume, E. 1996. Limit cycle control and its application to the animation of balancing and walking. In Proc. SIGGRAPH, 155--162. Google ScholarDigital Library
- Liu, C. K., Hertzmann, A., and Popović, Z. 2005. Learning Physics-Based Motion Style with Nonlinear Inverse Optimization. ACM Trans. Graphics 24, 3, 1071--1081. Google ScholarDigital Library
- Macchietto, A., Zordan, V., and Shelton, C. 2009. Momentum Control for Balance. ACM Trans. Graphics 28, 3, 80. Google ScholarDigital Library
- McGeer, T. 1990. Passive Dynamic Walking. Int. J. Robotics Research 9, 2, 62--82. Google ScholarDigital Library
- Muico, U., Lee, Y., Popović, J., and Popović, Z. 2009. Contact-aware Nonlinear Control of Dynamic Characters. ACM Trans. Graphics 28, 3, 81. Google ScholarDigital Library
- Pratt, J., and Tedrake, R. 2005. Velocity-Based Stability Margins for Fast Bipedal Walking. In Fast Motions in Robotics and Biomechanics--Optimization and Feedback Control, vol. 340, 299--324.Google ScholarCross Ref
- Pratt, J., Carff, J., Drakunov, S., and Goswami, A. 2006. Capture Point: A Step toward Humanoid Push Recovery. In Proc. Humanoid Robots, 200--207.Google Scholar
- Raibert, M. H., and Hodgins, J. K. 1991. Animation of dynamic legged locomotion. In Proc. SIGGRAPH 1991, 349--358. Google ScholarDigital Library
- Ramamoorthy, S., and Kuipers, B. 2008. Trajectory Generation for Dynamic Bipedal Walking through Qualitative Model Based Manifold Learning. In Proc. ICRA, 359--366.Google Scholar
- Rebula, J., Canas, F., Pratt, J., and Goswami, A. 2007. Learning Capture Points for Humanoid Push Recovery. In Proc. Humanoid Robots, 65--72.Google Scholar
- Schwind, W. J., and Koditschek, D. R. 2000. Approximating the stance map of a 2-DOF monoped runner. J. Nonlinear Science, 533--568.Google Scholar
- Sok, K. W., Kim, M., and Lee, J. 2007. Simulating Biped Behaviors from Human Motion Data. ACM Trans. Graphics 26, 3, 107. Google ScholarDigital Library
- Srinivasan, M., and Ruina, A. 2006. Computer optimization of a minimal biped model discovers walking and running. Nature 439, 7072, 72--75.Google Scholar
- Tsai, Y.-Y., Lin, W.-C., Cheng, K. B., Lee, J., and Lee, T.-Y. 2010. Real-Time Physics-Based 3D Biped Character Animation Using an Inverted Pendulum Model. Trans. Visualization and Computer Graphics 16, 325--337. Google ScholarDigital Library
- Wampler, K., and Popović, Z. 2009. Optimal Gait and Form for Animal Locomotion. ACM Trans. Graphics 28, 3, 60. Google ScholarDigital Library
- Witkin, A., and Kass, M. 1988. Spacetime Constraints. In Proc. SIGGRAPH, vol. 22, 159--168. Google ScholarDigital Library
- Yamane, K., and Hodgins, J. 2009. Simultaneous Tracking and Balancing of Humanoid Robots for Imitating Human Motion Capture Data. Proc. IROS, 2510--2517. Google ScholarDigital Library
- Yin, K., Loken, K., and van de Panne, M. 2007. SIMBI-CON: Simple Biped Locomotion Control. ACM Trans. Graphics 26, 3, 81. Google ScholarDigital Library
Index Terms
- Robust physics-based locomotion using low-dimensional planning
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