dc.contributor.author | Agethen, Philipp | en_US |
dc.contributor.author | Neher, Thomas | en_US |
dc.contributor.author | Gaisbauer, Felix | en_US |
dc.contributor.author | Manns, Martin | en_US |
dc.contributor.author | Rukzio, Enrico | en_US |
dc.contributor.editor | Jain, Eakta and Kosinka, Jirí | en_US |
dc.date.accessioned | 2018-04-14T18:29:51Z | |
dc.date.available | 2018-04-14T18:29:51Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 1017-4656 | |
dc.identifier.uri | http://dx.doi.org/10.2312/egp.20181009 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/egp20181009 | |
dc.description.abstract | This paper presents an approach that combines a hybrid A* path planner with a statistical motion graph to effectively generate a rich repertoire of walking trajectories. The motion graph is generated from a comprehensive database (20 000 steps) of captured human motion and covers a wide range of gait variants. The hybrid A* path planner can be regarded as an orchestrationinstance, stitching together succeeding left and right steps, which were drawn from the statistical motion model. Moreover, the hybrid A* planner ensures a collision-free path between a start and an end point. A preliminary evaluation underlines the evident benefits of the proposed algorithm. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.subject | Computing methodologies | |
dc.subject | Animation | |
dc.subject | Model development and analysis | |
dc.subject | Motion capture | |
dc.title | A Probabilistic Motion Planning Algorithm for Realistic Walk Path Simulation | en_US |
dc.description.seriesinformation | EG 2018 - Posters | |
dc.description.sectionheaders | Posters | |
dc.identifier.doi | 10.2312/egp.20181009 | |
dc.identifier.pages | 3-4 | |