General biped motion and balance of a human model

Joo H. Kim, Yujiang Xiang, Rajan Bhatt, Jingzhou Yang, Hyun Joon Chung, Amos Patrick, Anith J. Mathai, Jasbir S. Arora, Karim Abdel-Malek, John P. Obusek

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


We propose an algorithm of predicting dynamic biped motions of Santos™ human model. An alternative and efficient formulation of the Zero-Moment Point (ZMP) for dynamic balance and the approximated ground reaction forces/moments are derived from the resultant reaction loads, which includes the gravity, the externally applied loads, and the inertia. The optimization problem is formulated to address the redundancy of the human task, where the general biped and the task-specific constraints are imposed depending on the task requirements. The proposed method is fully predictive and generates physically feasible human-like motions from scratch without any input reference from motion capture or animation. The resulting generated motions demonstrate how a human reacts effectively to different external load conditions in performing a given task by showing realistic features of cause and effect.

Original languageEnglish
JournalSAE Technical Papers
StatePublished - 2008
EventDigital Human Modeling for Design and Engineering Conference and Exhibition - Pittsburgh, PA, United States
Duration: Jun 17 2008Jun 19 2008


  • Lagrangian dynamics
  • Zero-Moment Point
  • human motion generation
  • optimization


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