Valerie Renaudin, Miguel Ortiz, Johan Perul, Joaquin Torres-Sospedra, Antonio Ramon Jimenez, Antoni Perez-Navarro, German Martin Mendoza-Silva, Fernando Seco, Yael Landau, Revital Marbel, Boaz Ben-Moshe, Xingyu Zheng, Feng Ye, Jian Kuang, Yu Li, Xiaoji Niu, Vlad Landa, Shlomi Hacohen, Nir Shvalb, Chuanhua Lu, Hideaki Uchiyama, Diego Thomas, Atsushi Shimada, Rin-Ichiro Taniguchi, Zhenxing Ding, Feng Xu, Nikolai Kronenwett, Blagovest Vladimirov, Soyeon Lee, Eunyoung Cho, Sungwoo Jun, Changeun Lee, Sangjoon Park, Yonghyun Lee, Jehyeok Rew, Changjun Park, Hyeongyo Jeong, Jaeseung Han, Keumryeol Lee, Wenchao Zhang, Xianghong Li, Dongyan Wei, Ying Zhang, So Young Park, Chan Gook Park, Stefan Knauth, Georgios Pipelidis, Nikolaos Tsiamitros, Tomas Lungenstrass, Juan Pablo Morales, Jens Trogh, David Plets, Miroslav Opiela, Shih-Hau Fang, Yu Tsao, Ying-Ren Chien, Shi-Shen Yang, Shih-Jyun Ye, Muhammad Usman Ali, Soojung Hur, Yongwan Park
The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-Time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future.
KSP Keywords
3D scanners, Error metric, Floor detection, High accuracy, Horizontal positioning error, Indoor Positioning System(IPS), Indoor Positioning and Indoor Navigation, Indoor localization system, Lessons learned, Off-site, On-Site
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
Copyright Policy
ETRI KSP Copyright Policy
The materials provided on this website are subject to copyrights owned by ETRI and protected by the Copyright Act. Any reproduction, modification, or distribution, in whole or in part, requires the prior explicit approval of ETRI. However, under Article 24.2 of the Copyright Act, the materials may be freely used provided the user complies with the following terms:
The materials to be used must have attached a Korea Open Government License (KOGL) Type 4 symbol, which is similar to CC-BY-NC-ND (Creative Commons Attribution Non-Commercial No Derivatives License). Users are free to use the materials only for non-commercial purposes, provided that original works are properly cited and that no alterations, modifications, or changes to such works is made. This website may contain materials for which ETRI does not hold full copyright or for which ETRI shares copyright in conjunction with other third parties. Without explicit permission, any use of such materials without KOGL indication is strictly prohibited and will constitute an infringement of the copyright of ETRI or of the relevant copyright holders.
J. Kim et. al, "Trends in Lightweight Kernel for Many core Based High-Performance Computing", Electronics and Telecommunications Trends. Vol. 32, No. 4, 2017, KOGL Type 4: Source Indication + Commercial Use Prohibition + Change Prohibition
J. Sim et.al, “the Fourth Industrial Revolution and ICT – IDX Strategy for leading the Fourth Industrial Revolution”, ETRI Insight, 2017, KOGL Type 4: Source Indication + Commercial Use Prohibition + Change Prohibition
If you have any questions or concerns about these terms of use, or if you would like to request permission to use any material on this website, please feel free to contact us
KOGL Type 4:(Source Indication + Commercial Use Prohibition+Change Prohibition)
Contact ETRI, Research Information Service Section
Privacy Policy
ETRI KSP Privacy Policy
ETRI does not collect personal information from external users who access our Knowledge Sharing Platform (KSP). Unathorized automated collection of researcher information from our platform without ETRI's consent is strictly prohibited.
[Researcher Information Disclosure] ETRI publicly shares specific researcher information related to research outcomes, including the researcher's name, department, work email, and work phone number.
※ ETRI does not share employee photographs with external users without the explicit consent of the researcher. If a researcher provides consent, their photograph may be displayed on the KSP.