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...
保存先:
| 第一著者: | |
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| フォーマット: | Online |
| 言語: | 英語 |
| 出版事項: |
KIT Scientific Publishing
2021
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| 主題: | |
| オンライン･アクセス: | 34486 |
| タグ: |
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| _version_ | 1869521866516856832 |
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| author | Krauthausen, Peter |
| author_browse | Krauthausen, Peter |
| author_facet | Krauthausen, Peter |
| author_sort | Krauthausen, Peter |
| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-51483 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | KIT Scientific Publishing |
| publisherStr | KIT Scientific Publishing |
| record_format | ojs |
| spelling | doab-20.500.12854ir-514832023-12-20T18:40:47Z Learning Dynamic Systems for Intention Recognition in Human-Robot-Cooperation Krauthausen, Peter QA75.5-76.95 Intention Recognition Dynamic Systems (Conditional) Density Estimation Regularization Human-Robot-Cooperation bic Book Industry Communication::U Computing & information technology::UY Computer science 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. 2021-02-11T17:30:32Z 2021-02-11T17:30:32Z 2019-07-30 20:01:58 2013 book 34486 18673813 9783866449527 https://directory.doabooks.org/handle/20.500.12854/51483 eng Karlsruhe Series on Intelligent Sensor-Actuator-Systems / Karlsruher Institut für Technologie, Intelligent Sensor-Actuator-Systems Laboratory image/jpeg Attribution-NonCommercial-NoDerivatives 4.0 International https://www.ksp.kit.edu/9783866449527 KIT Scientific Publishing 10.5445/KSP/1000031356 10.5445/KSP/1000031356 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 9783866449527 XIV, 210 p. open access |
| spellingShingle | QA75.5-76.95 Intention Recognition Dynamic Systems (Conditional) Density Estimation Regularization Human-Robot-Cooperation bic Book Industry Communication::U Computing & information technology::UY Computer science Krauthausen, Peter Learning Dynamic Systems for Intention Recognition in Human-Robot-Cooperation |
| title | Learning Dynamic Systems for Intention Recognition in Human-Robot-Cooperation |
| title_full | Learning Dynamic Systems for Intention Recognition in Human-Robot-Cooperation |
| title_fullStr | Learning Dynamic Systems for Intention Recognition in Human-Robot-Cooperation |
| title_full_unstemmed | Learning Dynamic Systems for Intention Recognition in Human-Robot-Cooperation |
| title_short | Learning Dynamic Systems for Intention Recognition in Human-Robot-Cooperation |
| title_sort | learning dynamic systems for intention recognition in human robot cooperation |
| topic | QA75.5-76.95 Intention Recognition Dynamic Systems (Conditional) Density Estimation Regularization Human-Robot-Cooperation bic Book Industry Communication::U Computing & information technology::UY Computer science |
| topic_facet | QA75.5-76.95 Intention Recognition Dynamic Systems (Conditional) Density Estimation Regularization Human-Robot-Cooperation bic Book Industry Communication::U Computing & information technology::UY Computer science |
| url | 34486 |
| work_keys_str_mv | AT krauthausenpeter learningdynamicsystemsforintentionrecognitioninhumanrobotcooperation |