Inertial measurement unit based indoor localization for construction applications

Abstract Localization and tracking of resources on construction jobsites are an emerging area where the location of materials, labor, and equipment is used to estimate productivity, measure project's progress and/or enhance jobsite safety. GPS has been widely used for outdoor tracking of construction operations. However, GPS is not suitable for indoor applications due to the lack of signal coverage; particularly inside tunnels or buildings. Several indoor localization research studies had been attempted, however such developments rely heavily on extensive external communication network infrastructures. These developments also are susceptible to electromagnetic interference in noisy construction jobsites. This paper presents indoor localization system using a microcontroller equipped with an inertial measurement unit (IMU). The IMU contains a cluster of sensors: accelerometer, gyroscope and magnetometer. The microcontroller uses a direct cosine matrix algorithm to fuse sensors data and calculate non-gravitational acceleration using nine-degrees-of-freedom motion equations. Current position is calculated based on measured acceleration and heading, while accounting for growing error in speed estimation utilizing jerk integration algorithm. Experimental results are presented to illustrate the relative effectiveness of the developed system, which is able to operate independently of any external aids and visibility conditions.

[1]  B. Anderson,et al.  Optimal Filtering , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[2]  R. Clough,et al.  Dynamics Of Structures , 1975 .

[3]  Burcu Akinci,et al.  Analysis of Three Indoor Localization Technologies for Supporting Operations and Maintenance Field Tasks , 2012, J. Comput. Civ. Eng..

[4]  Jong-suk Choi,et al.  Active beacon system with the fast processing architecture for indoor localization , 2007, 2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007).

[5]  Rönne Reimann,et al.  Locating Technology for AAL Applications with Direction Finding and Distance Measurement by Narrow Bandwidth Phase Analysis , 2012, EvAAL.

[6]  Gaetano Borriello,et al.  SpotON: An Indoor 3D Location Sensing Technology Based on RF Signal Strength , 2000 .

[7]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[8]  Klaus Finkenzeller,et al.  Book Reviews: RFID Handbook: Fundamentals and Applications in Contactless Smart Cards and Identification, 2nd ed. , 2004, ACM Queue.

[9]  Toshiyuki Aoki,et al.  Cycle Slip Detection in Kinematic GPS with a Jerk Model for Land Vehicles , 2008 .

[10]  Anu Pradhan,et al.  Technological Assessment of Radio Frequency Identification Technology for Indoor Localization , 2009 .

[11]  Thomas Bernoulli,et al.  Semi-autonomous indoor positioning using MEMS-based inertial measurement units and building information , 2009, 2009 6th Workshop on Positioning, Navigation and Communication.

[12]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[13]  Paul M. Goodrum,et al.  The application of active radio frequency identification technology for tool tracking on construction job sites , 2006 .

[14]  Carlos H. Caldas,et al.  Using Global Positioning System to Improve Materials-Locating Processes on Industrial Projects , 2006 .

[15]  Jing Liu,et al.  Survey of Wireless Indoor Positioning Techniques and Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[16]  Gaetano Borriello,et al.  Location Systems for Ubiquitous Computing , 2001, Computer.

[17]  S. Schot,et al.  Jerk: The time rate of change of acceleration , 1978 .

[18]  Burcu Akinci,et al.  Tracking and locating components in a precast storage yard utilizing radio frequency identification technology and GPS , 2007 .

[19]  Miroslaw J. Skibniewski,et al.  A wireless network system for automated tracking of construction materials on project sites , 2008 .

[20]  Won-Suk Jang,et al.  Localization Technique for Automated Tracking of Construction Materials Utilizing Combined RF and Ultrasound Sensor Interfaces , 2007 .

[21]  Gregory Dudek,et al.  Comparing image-based localization methods , 2003, IJCAI.

[22]  Yunhao Liu,et al.  LANDMARC: Indoor Location Sensing Using Active RFID , 2004, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[23]  Henk L. Muller,et al.  Personal position measurement using dead reckoning , 2003, Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings..

[24]  M. Hubbard,et al.  A comparison between jerk optimal and acceleration optimal vibration isolation , 1987 .

[25]  Denos C. Gazis,et al.  Human Judgment and Analytical Derivation of Ride Quality , 1999, Transp. Sci..

[26]  Manu Venugopal,et al.  Ultrawideband for Automated Real-Time Three-Dimensional Location Sensing for Workforce, Equipment, and Material Positioning and Tracking , 2008 .

[27]  Burcu Akinci,et al.  Automating the task of tracking the delivery and receipt of fabricated pipe spools in industrial projects , 2006 .

[28]  Carl T. Haas,et al.  Multisensor data fusion for on-site materials tracking in construction , 2010 .

[29]  Richard P. Martin,et al.  The limits of localization using signal strength: a comparative study , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[30]  M.H. Francis,et al.  RFID-assisted indoor localization and communication for first responders , 2006, 2006 First European Conference on Antennas and Propagation.

[31]  Koshy Varghese,et al.  Accelerometer-Based Activity Recognition in Construction , 2011, J. Comput. Civ. Eng..

[32]  Vineet R. Kamat,et al.  High-precision identification of contextual information in location-aware engineering applications , 2009, Adv. Eng. Informatics.

[33]  Jin Yue,et al.  Compensation for Stochastic Error of Gyros in a Dual-axis Rotational Inertial Navigation System , 2016 .

[34]  Carlos H. Caldas,et al.  Methodology for Automating the Identification and Localization of Construction Components on Industrial Projects , 2009 .

[35]  Anil K. Chopra,et al.  Dynamics of Structures: Theory and Applications to Earthquake Engineering , 1995 .

[36]  Paul M. Goodrum,et al.  Field trial of automated material tracking in construction , 2008 .

[37]  Arthur Gelb,et al.  Applied Optimal Estimation , 1974 .

[38]  E. Edwan,et al.  Enhanced Indoor Navigation Using Fusion of IMU and RGB-D Camera , 2015 .

[39]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[40]  William G. Scanlon,et al.  Stepwise Algorithms for Improving the Accuracy of Both Deterministic and Probabilistic Methods in WLAN-based Indoor User Localisation , 2004, Int. J. Wirel. Inf. Networks.