基于動(dòng)態(tài)地標(biāo)的在線室內(nèi)平面圖生成方法
doi: 10.11999/JEIT150926
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2.
(燕山大學(xué)信息科學(xué)與工程學(xué)院 秦皇島 066004) ②(河北省計(jì)算機(jī)虛擬技術(shù)與系統(tǒng)集成重點(diǎn)實(shí)驗(yàn)室 秦皇島 066004)
基金項(xiàng)目:
國家自然科學(xué)基金(61272466, 61303233)，河北省自然科學(xué)基金(F2014203062)
A Dynamic Landmark-based Method for Online Indoor Pathway Mapping
Funds:
The National Natural Science Foundation of China (61272466, 61303233), Natural Science Foundation of Hebei Province (F2014203062)
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摘要: 在應(yīng)急救援、商場(chǎng)導(dǎo)購、患者導(dǎo)醫(yī)、參觀引導(dǎo)等導(dǎo)航應(yīng)用場(chǎng)景中，往往需要室內(nèi)平面圖作為先驗(yàn)知識(shí)，從而使得大量室內(nèi)導(dǎo)航系統(tǒng)缺乏可擴(kuò)展性和魯棒性。針對(duì)該問題，該文提出基于動(dòng)態(tài)地標(biāo)的在線室內(nèi)平面圖生成方法，減少現(xiàn)有方法對(duì)先驗(yàn)知識(shí)的依賴。首先利用智能移動(dòng)設(shè)備內(nèi)置的慣導(dǎo)傳感器數(shù)據(jù)和航位推算法獲取粗粒度移動(dòng)軌跡，繼而提出一個(gè)同步靜態(tài)地標(biāo)(樓梯、電梯以及手扶電梯等)和動(dòng)態(tài)地標(biāo)(軌跡拐點(diǎn))的識(shí)別方法；其次，利用這些地標(biāo)信息提出多用戶參與的軌跡自校正和組合方法實(shí)現(xiàn)室內(nèi)平面圖生成；最后，利用原型系統(tǒng)獲取的數(shù)據(jù)評(píng)價(jià)所提方法。分析結(jié)果顯示，該文方法的最大誤差以及平均誤差分別為1.90 m和0.90 m。
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關(guān)鍵詞:
- 室內(nèi)定位 /
- 靜態(tài)地標(biāo) /
- 動(dòng)態(tài)地標(biāo) /
- 在線生成 /
- 室內(nèi)平面圖
Abstract: In many navigation application scenarios, e.g., emergency rescue, mall shopping, medical guiding, and self-guided tours, the floor plan is regarded as a prior. As a result, these navigation systems are short of scalability and robustness. Focusing on this issue, this paper proposes a dynamic landmark-based method for constructing the indoor map, which mitigates the dependence to a prior with the state-of the-art. First of all, the coarse-grained trajectories are obtained by dead reckoning, meanwhile the static indoor landmarks (such as stairs, elevators, escalators) are captured and dynamic indoor landmarks (three kinds of inflection points) are identified by inertial data. Secondly, the trajectory are constructed calibration and integration is leveraged to implement the indoor pathway mapping. Finally, constructing extensive experiments by means of the prototype to evaluate the proposed design. The analysis results demonstrate that the maximum error and average error are 1.90 m and 0.90 m respectively.-
Key words:
- Indoor localization /
- Static landmark /
- Dynamic landmark /
- Online construction /
- Floor plan
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