Analysis of Human Motion for Humanoid Robots
Gespeichert in:
Deutscher übersetzter Titel: | Analyse menschlicher Bewegung für humanoide Roboter |
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Autor: | Moldenhauer, Jörg; Boesnach, Ingo; Beth, T.; Wank, Veit; Bös, Klaus |
Erschienen in: | 2005 IEEE International Conference on Robotics and Automation (ICRA) : Barcelona, Spain, 18 - 22 April 2005 |
Veröffentlicht: | Piscataway (N.J.): 2005, S. 312-317, Lit. |
Herausgeber: | IEEE Service Center |
Format: | Literatur (SPOLIT) |
Publikationstyp: | Sammelwerksbeitrag |
Medienart: | Gedruckte Ressource |
Sprache: | Englisch |
Schlagworte: | |
Online Zugang: | |
Erfassungsnummer: | PU201108007422 |
Quelle: | BISp |
TY - COLL AU - Moldenhauer, Jörg A2 - Moldenhauer, Jörg A2 - Boesnach, Ingo A2 - Beth, T. A2 - Wank, Veit A2 - Bös, Klaus DB - BISp DP - BISp KW - Bewegungsablauf KW - Bewegungsanalyse KW - Bewegungsmuster KW - Computer KW - Mensch KW - Sportwissenschaft LA - eng PB - IEEE Service Center CY - Piscataway (N.J.) TI - Analysis of Human Motion for Humanoid Robots TT - Analyse menschlicher Bewegung für humanoide Roboter PY - 2005 N2 - A great challange in robotics is to make robots more like humans. One important aspect is to make robots move like humans and recognize their motions. Both tasks are based on human motion trajectories and require a proper modelling. To accomplish these tasks, we acquire data from complex motions like setting the table, pouring water into a cup, or stirring the content of the cup. The objectives of our studies are to identify the subject doing the motion and to detect slight changes in motion constraints with automatic classification methods. For that purpose, we present reliable methods based on Elman networks and hidden Markov models. We develop the model parameters and compare the performance of the methods, especially, the classification results and the suitability for the classification tasks. Verf.-Referat SP - S. 312-317 BT - 2005 IEEE International Conference on Robotics and Automation (ICRA) : Barcelona, Spain, 18 - 22 April 2005 M3 - Gedruckte Ressource ID - PU201108007422 ER -