Towards quantifying false alarms for effective human robot interactions
Human robot teams combining the complementary capabilities of robots and humans towards solving complex tasks are gaining wide spread popularity. Accomplishment of these tasks greatly depends on the quality of interaction between human and the robot thereby requiring models and metrics to evaluate h...
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| Format: | Thesis |
| Language: | English |
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2011
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| Online Access: | https://hdl.handle.net/10356/46289 |
| _version_ | 1811693486413447168 |
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| author | Mohan Rajesh Elara |
| author2 | Wijerupage Sardha Wijesoma |
| author_facet | Wijerupage Sardha Wijesoma Mohan Rajesh Elara |
| author_sort | Mohan Rajesh Elara |
| collection | NTU |
| description | Human robot teams combining the complementary capabilities of robots and humans towards solving complex tasks are gaining wide spread popularity. Accomplishment of these tasks greatly depends on the quality of interaction between human and the robot thereby requiring models and metrics to evaluate human robot interactions (HRI) in relation to performance. The traditional and most popularly adopted approach to this end has been the neglect tolerance model. The major shortcoming of this traditional model is that it presumes ideal conditions in which an operator switches control between robots sequentially based on an acceptable performance level for each robot whilst ignoring any erroneous interactions. In this thesis, the erroneous interactions that inevitably arise in HRI are identified as false alarm interactions, classified and their effects estimated. More specifically, two significant metrics that quantify the effects of false alarm interactions are defined, viz. false alarm time, and false alarm demand. In addition, the neglect tolerance model is extended to accommodate for the additional demands due to false alarm interactions. Extended neglect tolerance model is further expanded for multi-robot systems taking into account the independent or co-operating natures of robots in the team. Traditional neglect tolerance model forms the basis for fan out metric which is adopted as a general index in predicting the maximum number of robots a single operator can handle simultaneously while maintaining performance at acceptable levels. The fan out metric was redefined to account for additional demands due to the occurrence of false alarm interactions. |
| first_indexed | 2024-10-01T06:52:27Z |
| format | Thesis |
| id | ntu-10356/46289 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:52:27Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | ntu-10356/462892023-07-04T17:07:06Z Towards quantifying false alarms for effective human robot interactions Mohan Rajesh Elara Wijerupage Sardha Wijesoma School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics Human robot teams combining the complementary capabilities of robots and humans towards solving complex tasks are gaining wide spread popularity. Accomplishment of these tasks greatly depends on the quality of interaction between human and the robot thereby requiring models and metrics to evaluate human robot interactions (HRI) in relation to performance. The traditional and most popularly adopted approach to this end has been the neglect tolerance model. The major shortcoming of this traditional model is that it presumes ideal conditions in which an operator switches control between robots sequentially based on an acceptable performance level for each robot whilst ignoring any erroneous interactions. In this thesis, the erroneous interactions that inevitably arise in HRI are identified as false alarm interactions, classified and their effects estimated. More specifically, two significant metrics that quantify the effects of false alarm interactions are defined, viz. false alarm time, and false alarm demand. In addition, the neglect tolerance model is extended to accommodate for the additional demands due to false alarm interactions. Extended neglect tolerance model is further expanded for multi-robot systems taking into account the independent or co-operating natures of robots in the team. Traditional neglect tolerance model forms the basis for fan out metric which is adopted as a general index in predicting the maximum number of robots a single operator can handle simultaneously while maintaining performance at acceptable levels. The fan out metric was redefined to account for additional demands due to the occurrence of false alarm interactions. DOCTOR OF PHILOSOPHY (EEE) 2011-11-28T08:37:32Z 2011-11-28T08:37:32Z 2011 2011 Thesis Mohan Rajesh Elara. (2011). Towards quantifying false alarms for effective human robot interactions. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/46289 10.32657/10356/46289 en 232 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics Mohan Rajesh Elara Towards quantifying false alarms for effective human robot interactions |
| title | Towards quantifying false alarms for effective human robot interactions |
| title_full | Towards quantifying false alarms for effective human robot interactions |
| title_fullStr | Towards quantifying false alarms for effective human robot interactions |
| title_full_unstemmed | Towards quantifying false alarms for effective human robot interactions |
| title_short | Towards quantifying false alarms for effective human robot interactions |
| title_sort | towards quantifying false alarms for effective human robot interactions |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics |
| url | https://hdl.handle.net/10356/46289 |
| work_keys_str_mv | AT mohanrajeshelara towardsquantifyingfalsealarmsforeffectivehumanrobotinteractions |