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Dynamically balanced and plausible trajectory planning for human-like characters

Chonhyon Park 1 Jae Sung Park 1 Steve Tonneau 2 Nicolas Mansard 2 Franck Multon 3, 4 Julien Pettré 5 Dinesh Manocha 1 
2 LAAS-GEPETTO - Équipe Mouvement des Systèmes Anthropomorphes
LAAS - Laboratoire d'analyse et d'architecture des systèmes
4 MIMETIC - Analysis-Synthesis Approach for Virtual Human Simulation
UR2 - Université de Rennes 2, Inria Rennes – Bretagne Atlantique , IRISA-D6 - MEDIA ET INTERACTIONS
5 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : We present an interactive motion planning algorithm to compute plausible trajectories for high-DOF human-like characters. Given a discrete sequence of contact configurations, we use a three-phase optimization approach to ensure that the resulting trajectory is collision-free, smooth, and satisfies dynamic balancing constraints. Our approach can directly compute dynamically balanced and natural-looking motions at interactive frame rates and is considerably faster than prior methods. We highlight its performance on complex human motion benchmarks corresponding to walking, climbing, crawling, and crouching, where the discrete configurations are generated from a kinematic planner or extracted from motion capture datasets.
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Submitted on : Friday, November 4, 2016 - 2:47:25 PM
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Chonhyon Park, Jae Sung Park, Steve Tonneau, Nicolas Mansard, Franck Multon, et al.. Dynamically balanced and plausible trajectory planning for human-like characters. 20th ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, ACM, Feb 2016, Redmond, United States. pp.39-48, ⟨10.1145/2856400.2856405⟩. ⟨hal-01290368⟩



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