The advent of satellite navigation (GNSS) has brought a huge benefit for society. The capability of obtaining highly accurate positioning and tracking of people, items, or vehicles, has led to a large number of applications. However, this location-aware functionality is lost once we get indoors. People spend about 80% of their time in indoor environments, so location awareness is key in many applications. Apart from guiding people inside buildings, new applications have arisen as people monitoring, inventory tracking, rescue, augmented reality, advertising, etc. So, many sectors of the society will benefit from ubiquitous localization technology.

Indoor positioning involves innovations at several level of signal/data processing, from base technology to applications. The project MICROCEBUS poses the challenge of solving specific applications of local positioning systems and aims to make contributions in all the levels of the signal/data processing stack (the MICROCEBUS Workpackages), from base technologies (data collecting/WP1), heterogeneous data integration and communication (data availability/WP2), data analysis (data usability and visualization/WP3), and use in specific applications (WP4). The aim is a holistic approach in which workpackage methods and results are linked and optimized with the final application in mind.

The MICROCEBUS-CSIC subproject, led by the “Localization and Exploration for Intelligent Systems” research group based on the Centre for Automation and Robotics (CAR) from CSIC, will contribute with activities that go from the sensing stage to the analytics phase and beyond into the application. CSIC will propose new advanced technologies, supported by the internationally-recognized background and know-how demonstrated in indoor location technologies. The CSIC subproject will focus its technological development on low-cost MEMS-based wearables, smart-phone-centric sensor fusion and the implementation of solutions in real location-aware problems in the industrial and health sectors. CSIC will provide low-level processing of raw data from inertial sensors placed on smart-shoes and other wearables (smartwatch and smartphone) to detect and analyze personal motion and activities with very high accuracy. Data collection of signal strength measurements and ranging estimates from RF beacons (static or mobile) for both individual and cooperative navigation in indoor areas, as well as other signals of opportunity (light, magnetic) will be proposed for an enhanced localization accuracy. CSIC will advance in sensor fusion techniques for single user localization to multiple/massive user’s cooperative localization. CSIC will propose the development of new indoor floorplan formats to allow real-time map-matching algorithms, and integration of multiple heterogeneous information sources for robust and accurate seamless indoor navigation. Statistical analytical software tools will be developed to examine and assess localization data, and to classify common activities and patterns of motion of individuals and groups of people. CSIC will lead the implementation of demonstrators in the logistic sector, coping with some of the challenges already addressed by companies in the field; specifically, the optimization of the workflow of warehouses. CSIC will also contribute to implement a demonstrator for the analysis of physical activity and user behavior patterns at home, within the field of independent life and active aging.

Sistemas locales de localización enfoque holístico desde el sensado a la analítica-MICROCEBUS


January, 2019


December, 2021


Work Packages considered in  MICROCEBUS

Pedestrian Dead-reckoning for people tracking

Indoor localization systems for personnel tracking in logistics warehouses

Vitality monitoring using inertial motion estimation


Main expertise and experience are related to:
• Indoor localization
• RFID, UWB WiFi, BLE, inertial sensors and measurement modelling
• Bayesian filters and robust estimation
• Warehouse and Health applications
• Constraint Satisfaction Problems.


 REPNIN+: Red de posicionamiento y navegación de interiores.
TEC2017-90808-REDT; Subvención: 22.000 €
Coordinated project: UAH, CSIC, UPM, UEX, UDE, UGR, UJI, UOC, UAB, UM
IP: Jose Luis Lázaro (UAH) y Fernando Seco Granja (CSIC)
Duración: 01/07/2018 – 30/06/2020.
• TARSIUS. Mejora y robustecimiento de sistemas de localización en interiores para aplicaciones y servicios basados en posicionamiento. Ministerio de Economía y Competitividad – FEDER, TIN2015 – 71564-C4-2-R. Subvención: 53.300 euros (CAR)
Coordinated project: University Alcalá – CSIC – University Extremadura
IP: Dr. D. Jesús Ureña Ureña (UAH) / Dr. D. Fernando Seco Granja (CAR)
January 2016 – December 2018
• LORIS. Sistemas cooperativos de localización para personas y objetos en entornos diversos
Ministerio de Economía y Competitividad, TIN2012-38080-C04-04
172.530 euros (total), 30.000 euros (CAR)
Coordinated project: Universidad de Alcalá – CSIC – Univ.Valladolid – Univ. Extremadura
IP: Dr. D. Jesús Ureña Ureña (UAH) / Dr. D. Fernando Seco Granja (CAR)
January 2013 – December 2015


• AR Jimenez, F Seco, C Prieto, J Guevara, A comparison of pedestrian dead-reckoning algorithms using a low-cost MEMS IMU, Intelligent Signal Processing, 2009. WISP 2009. IEEE International Symposium, (2009) (465 cites in GScholar)
• AR Jiménez, F Seco, JC Prieto, J Guevara, Indoor pedestrian navigation using an INS/EKF framework for yaw drift reduction and a foot-mounted IMU, Positioning Navigation and Communication (WPNC), 7th Workshop on, 135-143, (2010) (cited 358 in GScholar)
• AR Jimenez, F. Seo et al., Accurate pedestrian indoor navigation by tightly coupling foot-mounted IMU and RFID measurements, IEEE Transactions on Instrumentation and measurement 61 (1), 178-189, (2012) (cited 322 times in GScholar).
• A.R. Jiménez and F. Seco, Comparing Ubisense, Bespoon and Decawave UWB location systems: indoor performance analysis, IEEE Transactions on Instrumentation and Measurement , vol. 66, no. 8, pp. 2106-2117, August 2017.
• J. Torres-Sospedra, A.R. Jiménez, et al. “The Smartphone-Based Offline Indoor Location Competition at IPIN 2016: Analysis and Future Work”, Sensors 2017, 17(3), 557; http://dx.doi.org/10.3390/s17030557
• A.R. Jiménez and F. Seco, Finding objects using UWB or BLE localization technology: a museum-like use case, 2017 Indoor Positioning and Indoor Navigation Conference (IPIN), pp. –, Sapporo, Japan, September 18-21 (2017).
• F. Seco and A. R. Jiménez, Autocalibration of a wireless positioning network with a FastSLAM algorithm, 2017 Indoor Positioning and Indoor Navigation Conference (IPIN), pp. –, Sapporo, Japan, September 18-21 (2017).
• F. Seco, A. R. Jiménez and X. Zheng, RFID-based centralized cooperative localization in indoor environments, 2016 Indoor Positioning and Indoor Navigation Conference (IPIN), pp. –, Alcalá de Henares, Spain, October 4-7 (2016).
• F. Zampella, A.R. Jiménez, F. Seco, Improving indoor positioning using an efficient Map Matching and an extended motion model, IEEE Transactions on Vehicular Technology, vol. 64, no. 4, pp. 1304-1317 (2015).

• Localization.
• Sensors.
• Navigation.
• Sensor fusion

CSIC contacts:

Antonio Ramón Jiménez Ruiz
Email: Antonio.jimenez@csic.es

Fernando Seco Granja
Email: fernando.seco@csic.es