Motion planning for digital actors

Mylène Campana 1
1 LAAS-GEPETTO - Équipe Mouvement des Systèmes Anthropomorphes
LAAS - Laboratoire d'analyse et d'architecture des systèmes [Toulouse]
Abstract : Probabilistic algorithms offer powerful possibilities as for solving motion planning problems for complex robots in arbitrary environments. However, the quality of obtained solution paths is questionable. This thesis presents a tool to optimize these paths and improve their quality. The method is based on constrained numerical optimization and on collision checking to reduce the path length while avoiding collisions. The modularity of probabilistic methods also inspired us to design a motion generation algorithm for jumping characters. This algorithm is described by three steps of motion planning, from the trajectory of the character’s center to the wholebody motion. Each step benefits from the rigor of motion planning to avoid collisions and to constraint the path. We proposed physics-inspired constraints to increase the plausibility of motions, such as slipping avoidance, velocity limitation and contact maintaining. The thesis works have been implemented in the software ‘Humanoid Path Planner’ and the graphical renderings have been done with Blender.
Document type :
Automatic. Université Paul Sabatier (Toulouse 3), 2017. English
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Submitted on : Thursday, September 21, 2017 - 2:20:48 PM
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  • HAL Id : tel-01591472, version 1


Mylène Campana. Motion planning for digital actors. Automatic. Université Paul Sabatier (Toulouse 3), 2017. English. 〈tel-01591472〉



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