Learning Dynamic Systems for Intention Recognition in Human-Robot-Cooperation
This thesis is concerned with intention recognition for a humanoid robot and investigates how the challenges of uncertain and incomplete observations, a high degree of detail of the used models, and real-time inference may be addressed by modeling the human rationale as hybrid, dynamic Bayesian netw...
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| Format: | eBook |
| Language: | English |
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KIT Scientific Publishing
2013
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| Series: | Karlsruhe Series on Intelligent Sensor-Actuator-Systems / Karlsruher Institut für Technologie, Intelligent Sensor-Actuator-Systems Laboratory
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| Collection: | Directory of Open Access Books - Collection details see MPG.ReNa |
| Summary: | This thesis is concerned with intention recognition for a humanoid robot and investigates how the challenges of uncertain and incomplete observations, a high degree of detail of the used models, and real-time inference may be addressed by modeling the human rationale as hybrid, dynamic Bayesian networks and performing inference with these models. The key focus lies on the automatic identification of the employed nonlinear stochastic dependencies and the situation-specific inference. |
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| Item Description: | Creative Commons (cc), https://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Physical Description: | 1 electronic resource (XIV, 210 p. p.) |
| ISBN: | 9783866449527 1000031356 |