Active and Passive Guidance of the Robot Walking Helper Based on Environment Detection
碩士 === 國立交通大學 === 電控工程研究所 === 100 === Nowadays,the critical issue of aging population is getting more and more serious. It comes to realization that how to care the senior citizen well about their livelihood has grown into an important task for us. Along with the progress of the robot technology, se...
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ndltd-TW-100NCTU54490022015-10-13T20:37:26Z http://ndltd.ncl.edu.tw/handle/46506804542919112970 Active and Passive Guidance of the Robot Walking Helper Based on Environment Detection 基於環境偵測之行動輔具主被動式導引 吳權哲 碩士 國立交通大學 電控工程研究所 100 Nowadays,the critical issue of aging population is getting more and more serious. It comes to realization that how to care the senior citizen well about their livelihood has grown into an important task for us. Along with the progress of the robot technology, several robot walking helpers have been developed. It motivates us to also develop a robot walking helper, named i-go, in our laboratory for assisting the daily lives of the elderly. In the thesis, based on navigation techniques previously proposed, we develop two guidance algorithms to integrate environment information for the passive walking helper, and realize them in the i-go. They are (1) the slope-guidance algorithm and (2) obstacles avoidance and guidance algorithm. The former can guide the user to the desired position and orientation on the slope, and the latter not only guide the user to avoid obstacles, but also to the desired position and orientation. The proposed guidance algorithms have been verified via the experiment. In future, we expect the i-go can assist the elderly for guidance in real environments. We will introduce the i-go to the Alzheimer’s patients, so that they can rely on it for movement to tackle the conditions of memory decline and poor sense in orientation. 楊谷洋 2011 學位論文 ; thesis 61 zh-TW |
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碩士 === 國立交通大學 === 電控工程研究所 === 100 === Nowadays,the critical issue of aging population is getting more and more serious. It comes to realization that how to care the senior citizen well about their livelihood has grown into an important task for us. Along with the progress of the robot technology, several robot walking helpers have been developed. It motivates us to also develop a robot walking helper, named i-go, in our laboratory for assisting the daily lives of the elderly. In the thesis, based on navigation techniques previously proposed, we develop two guidance algorithms to integrate environment information for the passive walking helper, and realize them in the i-go. They are (1) the slope-guidance algorithm and (2) obstacles avoidance and guidance algorithm. The former can guide the user to the desired position and orientation on the slope, and the latter not only guide the user to avoid obstacles, but also to the desired position and orientation. The proposed guidance algorithms have been verified via the experiment. In future, we expect the i-go can assist the elderly for guidance in real environments. We will introduce the i-go to the Alzheimer’s patients, so that they can rely on it for movement to tackle the conditions of memory decline and poor sense in orientation.
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楊谷洋 |
author_facet |
楊谷洋 吳權哲 |
author |
吳權哲 |
spellingShingle |
吳權哲 Active and Passive Guidance of the Robot Walking Helper Based on Environment Detection |
author_sort |
吳權哲 |
title |
Active and Passive Guidance of the Robot Walking Helper Based on Environment Detection |
title_short |
Active and Passive Guidance of the Robot Walking Helper Based on Environment Detection |
title_full |
Active and Passive Guidance of the Robot Walking Helper Based on Environment Detection |
title_fullStr |
Active and Passive Guidance of the Robot Walking Helper Based on Environment Detection |
title_full_unstemmed |
Active and Passive Guidance of the Robot Walking Helper Based on Environment Detection |
title_sort |
active and passive guidance of the robot walking helper based on environment detection |
publishDate |
2011 |
url |
http://ndltd.ncl.edu.tw/handle/46506804542919112970 |
work_keys_str_mv |
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1718050015755108352 |