Abstract
In this chapter, we discuss the generation of natural behaviors of humanoids (virtual human characters in particular) responsive to the physical interaction with the user such as push and pull. These physical interactions play an important role for increasing the level of immersion of the user and lay foundations for more advanced level of interactions. One of the key components for physical interaction is the generation of suitable balancing behaviors of humanoids against user inputs. We review three major approaches for humanoid balancing, namely the ZMP-based methods, data-driven methods, and momentum-based methods. For each method, we discuss its basic ideas and principles, exemplar work, as well as important future research directions.
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References
Abdallah M, Goswami A (2005) A biomechanically motivated two-phase strategy for biped upright balance control. In: Proceedings of the 2005 IEEE international conference on robotics and automation, ICRA ’05, pp 1996–2001
Abe Y, da Silva M, Popović J (2007) Multiobjective control with frictional contacts. In: Proceedings of the ACM SIGGRAPH Eurographics symposium on computer animation 2007, Eurographics Association, pp 249-258
Featherstone R (1987) Robot dynamics algorithm. Kluwer Academic Publishers, Boston
Geijtenbeek T, Pronost N, van der Stappen F (2012) Simple data-driven control for simulated bipeds. In: Proceedings of the ACM SIGGRAPH/Eurographics symposium on computer animation 2012, Eurographics Association, pp 211–219
Golliday CL Jr, Hemami H (1976) Postural stability of the two-degree-of-freedom biped by general linear feedback. IEEE Trans Autom Control 21(1):74–79
Ha S, Ye Y, Liu CK (2012) Falling and landing motion control for character animation. ACM Trans Graph 31(6):155:1–155:9
Kajita S, Harada K, Hirukawa H, Yokoi K (2014) Introduction to humanoid robotics. Springer, New York
Kajita S, Kanehiro F, Kaneko K, Fujiwara K, Harada K, Yokoi K, Hirukawa H (2003) Resolved momentum control: humanoid motion planning based on the linear and angular momentum. In: Proceedings of 2003 IEEE/RSJ international conference on intelligent robots and systems, IROS ’03, pp 1644–1650
Kajita S, Kanehiro F, Kaneko K, Yokoi K, Hirukawa H (2001) The 3D linear inverted pendulum mode: a simple modeling for a biped walking pattern generation. In: Proceedings of 2001 IEEE/RSJ international conference of intelligent robots and systems, IROS ’01, pp 239–246
Lee S-H, Goswami A (2012) A momentum-based balance controller for humanoid robots on non-level and non-stationary ground. Auton Robots 33(4):399–414
Liu L, Yin K, van de Panne M, Shao T, Xu W (2010) Sampling-based contact-rich motion control. ACM Trans Graph 29(4):128:1–128:10
Macchietto A, Zordan VB, Shelton CR (2009) Momentum control for balance. ACM Trans Graph 28(3):80:1–80:8
Nam HN, Arista CR, Karen L, Victor BZ (2012) Adaptive dynamics with hybrid response. In: SIGGRAPH Asia technical briefs 5(1–5):4
Orin DE, Goswami A, Lee S-H (2013) Centroidal dynamics of a humanoid robot. Auton Robots 35(2–3):161–176
Pratt J, Chew C-M, Torres A, Dilworth P, Pratt G (2001) Virtual model control: an intuitive approach for bipedal locomotion. Int J Robot Res 20(2):129–143
Vukobratovic M (1990) Biped locomotion. Springer, New York
Vukobratovic M, Frank AA, Juricic D (1970) On the stability of biped locomotion. IEEE Trans Biomed Eng 17(1):25–36
Wu C-C, Zordan VB (2010) Goal-directed stepping with momentum control. In: Proceedings of the 2010 ACM SIGGRAPH/Eurographics symposium on computer animation, Eurographics Association, pp 113–118
Yin K, Pai DK, van de Panne M (2005) Data-driven interactive balancing behaviors. In: Proceedings of the 13th Pacific conference on computer graphics and applications, Pacific Graphics ’05, pp 118–121
Yun S, Goswami A (2011) Momentum-based reactive stepping controller on level and non-level ground for humanoid robot push recovery. In: Proceedings of 2011 IEEE/RSJ international conference on intelligent robots and systems, IROS ’11, pp 3943–3950
Zordan VB, Majkowska A, Chiu B, Fast M (2005) Dynamic response for motion capture animation. ACM Trans Graph, pp 697–701
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Lee, S., Lee, SH. (2016). Responsive Motion Generation. In: Magnenat-Thalmann, N., Yuan, J., Thalmann, D., You, BJ. (eds) Context Aware Human-Robot and Human-Agent Interaction. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-319-19947-4_8
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DOI: https://doi.org/10.1007/978-3-319-19947-4_8
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