Abstract
With the great international popularity and various sensors embedded, smartphone becomes an excellent mobile and indoor navigator. Pedestrian Dead Reckoning (PDR) is one of the most common technologies for pedestrian and indoor navigation which is based upon pedometer and orientation sensor. But various errors tend to accumulated step by step in its present form. Therefore, this study proposes a novel map aided Fuzzy Decision Tree (FDT) without complex algorithm and individually tuning process to reduce the accumulated error, improve the generation ability and minimize the use of infrastructure. The rule-based FDT algorithm estimates the location based upon the map, sensors and expert knowledge after training once then for other new experiments. Various scenarios consisted of different test sites, smartphones and users are implemented in order to verify the performance of proposed algorithm. The results verify that once the proposed algorithm is well trained, it is able to maintain good position performance regardless of the users, fields and smartphones. In addition, the positioning solution can output the global coordinate because of the use of self-produced map for seamless navigation in both indoor and outdoor environments.
| Original language | English |
|---|---|
| Title of host publication | 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781509024254 |
| DOIs | |
| Publication status | Published - 2016 Nov 14 |
| Event | 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016 - Madrid, Spain Duration: 2016 Oct 4 → 2016 Oct 7 |
Publication series
| Name | 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016 |
|---|
Other
| Other | 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016 |
|---|---|
| Country | Spain |
| City | Madrid |
| Period | 16-10-04 → 16-10-07 |
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All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Control and Optimization
- Instrumentation
Cite this
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A low complexity map-aided Fuzzy Decision Tree for pedestrian indoor/outdoor navigation using smartphone. / Liao, Jhen Kai; Chiang, Kai-Wei; Tsai, Guang Je; Chang, Hsiu-Wen.
2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7743640 (2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A low complexity map-aided Fuzzy Decision Tree for pedestrian indoor/outdoor navigation using smartphone
AU - Liao, Jhen Kai
AU - Chiang, Kai-Wei
AU - Tsai, Guang Je
AU - Chang, Hsiu-Wen
PY - 2016/11/14
Y1 - 2016/11/14
N2 - With the great international popularity and various sensors embedded, smartphone becomes an excellent mobile and indoor navigator. Pedestrian Dead Reckoning (PDR) is one of the most common technologies for pedestrian and indoor navigation which is based upon pedometer and orientation sensor. But various errors tend to accumulated step by step in its present form. Therefore, this study proposes a novel map aided Fuzzy Decision Tree (FDT) without complex algorithm and individually tuning process to reduce the accumulated error, improve the generation ability and minimize the use of infrastructure. The rule-based FDT algorithm estimates the location based upon the map, sensors and expert knowledge after training once then for other new experiments. Various scenarios consisted of different test sites, smartphones and users are implemented in order to verify the performance of proposed algorithm. The results verify that once the proposed algorithm is well trained, it is able to maintain good position performance regardless of the users, fields and smartphones. In addition, the positioning solution can output the global coordinate because of the use of self-produced map for seamless navigation in both indoor and outdoor environments.
AB - With the great international popularity and various sensors embedded, smartphone becomes an excellent mobile and indoor navigator. Pedestrian Dead Reckoning (PDR) is one of the most common technologies for pedestrian and indoor navigation which is based upon pedometer and orientation sensor. But various errors tend to accumulated step by step in its present form. Therefore, this study proposes a novel map aided Fuzzy Decision Tree (FDT) without complex algorithm and individually tuning process to reduce the accumulated error, improve the generation ability and minimize the use of infrastructure. The rule-based FDT algorithm estimates the location based upon the map, sensors and expert knowledge after training once then for other new experiments. Various scenarios consisted of different test sites, smartphones and users are implemented in order to verify the performance of proposed algorithm. The results verify that once the proposed algorithm is well trained, it is able to maintain good position performance regardless of the users, fields and smartphones. In addition, the positioning solution can output the global coordinate because of the use of self-produced map for seamless navigation in both indoor and outdoor environments.
UR - http://www.scopus.com/inward/record.url?scp=85004091116&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85004091116&partnerID=8YFLogxK
U2 - 10.1109/IPIN.2016.7743640
DO - 10.1109/IPIN.2016.7743640
M3 - Conference contribution
T3 - 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016
BT - 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016
PB - Institute of Electrical and Electronics Engineers Inc.
ER -